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Your search keyword '"CHEN CHENG, Kuo"' showing total 28 results
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28 results on '"CHEN CHENG, Kuo"'

1. Miscellaneous Disorder of the Small Intestines

Author

Chung, Chen-Shuan, Lee, Tzong-His, Chou, Jen-Wei, Feng, Chun-Lung, Huang, Shang-Fen, Chen, Cheng-Kuo, Shih, Yi-Sing, Huang, Wen-Hsin, Yen, Hsu-Heng, Chen, Yang-Yuan, Su, M. Y., Lin, W. P., Chiu, Cheng-Tang, Tai, Chi-Ming, Chang, I-Wei, Wang, Hsiu-Po, Huang, H. C., Lin, Te-Yu, Huang, Tien-Yu, Hu, Chi-Tan, Chen, C. L., Chang, Chen-Wang, Chang, Ching-Wei, Lai, Jian-Han, Chen, Ming-Jen, Liu, Chia-Yuan, Shih, Shou-Chuan, Wang, Horng-Yuan, Cheng, Ken-Sheng, Chuang, Shih-Chieh, Chiu, Cheng-Tang, editor, Wang, Hsiu-Po, editor, and Chen, Yang-Yuan, editor

Published
2023
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2. Applying Deep Learning Model to Predict Diagnosis Code of Medical Records

Author

Jakir Hossain Bhuiyan Masud, Chen-Cheng Kuo, Chih-Yang Yeh, Hsuan-Chia Yang, and Ming-Chin Lin

Subjects
clinical note, natural language processing, deep learning, convolutional neural network, diagnosis code, Medicine (General), R5-920
Abstract

The International Classification of Diseases (ICD) code is a diagnostic classification standard that is frequently used as a referencing system in healthcare and insurance. However, it takes time and effort to find and use the right diagnosis code based on a patient’s medical records. In response, deep learning (DL) methods have been developed to assist physicians in the ICD coding process. Our findings propose a deep learning model that utilized clinical notes from medical records to predict ICD-10 codes. Our research used text-based medical data from the outpatient department (OPD) of a university hospital from January to December 2016. The dataset used clinical notes from five departments, and a total of 21,953 medical records were collected. Clinical notes consisted of a subjective component, objective component, assessment, plan (SOAP) notes, diagnosis code, and a drug list. The dataset was divided into two groups: 90% for training and 10% for test cases. We applied natural language processing (NLP) technique (word embedding, Word2Vector) to process the data. A deep learning-based convolutional neural network (CNN) model was created based on the information presented above. Three metrics (precision, recall, and F-score) were used to calculate the achievement of the deep learning CNN model. Clinically acceptable results were achieved through the deep learning model for five departments (precision: 0.53–0.96; recall: 0.85–0.99; and F-score: 0.65–0.98). With a precision of 0.95, a recall of 0.99, and an F-score of 0.98, the deep learning model performed the best in the department of cardiology. Our proposed CNN model significantly improved the prediction performance for an automated ICD-10 code prediction system based on prior clinical information. This CNN model could reduce the laborious task of manual coding and could assist physicians in making a better diagnosis.

Published
2023
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4. Applying Deep Learning Model to Predict Diagnosis Code of Medical Records

Author

Lin, Jakir Hossain Bhuiyan Masud, Chen-Cheng Kuo, Chih-Yang Yeh, Hsuan-Chia Yang, and Ming-Chin

Subjects
clinical note, natural language processing, deep learning, convolutional neural network, diagnosis code
Abstract

The International Classification of Diseases (ICD) code is a diagnostic classification standard that is frequently used as a referencing system in healthcare and insurance. However, it takes time and effort to find and use the right diagnosis code based on a patient’s medical records. In response, deep learning (DL) methods have been developed to assist physicians in the ICD coding process. Our findings propose a deep learning model that utilized clinical notes from medical records to predict ICD-10 codes. Our research used text-based medical data from the outpatient department (OPD) of a university hospital from January to December 2016. The dataset used clinical notes from five departments, and a total of 21,953 medical records were collected. Clinical notes consisted of a subjective component, objective component, assessment, plan (SOAP) notes, diagnosis code, and a drug list. The dataset was divided into two groups: 90% for training and 10% for test cases. We applied natural language processing (NLP) technique (word embedding, Word2Vector) to process the data. A deep learning-based convolutional neural network (CNN) model was created based on the information presented above. Three metrics (precision, recall, and F-score) were used to calculate the achievement of the deep learning CNN model. Clinically acceptable results were achieved through the deep learning model for five departments (precision: 0.53–0.96; recall: 0.85–0.99; and F-score: 0.65–0.98). With a precision of 0.95, a recall of 0.99, and an F-score of 0.98, the deep learning model performed the best in the department of cardiology. Our proposed CNN model significantly improved the prediction performance for an automated ICD-10 code prediction system based on prior clinical information. This CNN model could reduce the laborious task of manual coding and could assist physicians in making a better diagnosis.

Published
2023
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5. Combined CRAFITY score and α-fetoprotein response predicts treatment outcomes in patients with unresectable hepatocellular carcinoma receiving anti-programmed death-1 blockade-based immunotherapy

Author

Hsu, Wei-Fan, Lai, Hsueh-Chou, Chen, Cheng-Kuo, Wang, Hung-Wei, Chuang, Po-Heng, Tsai, Ming-Hung, Chen, Sheng-Hung, Chu, Chia-Sheng, Su, Wen-Pang, Chou, Jen-Wei, Kao, Jung-Ta, Chen, Hung-Yao, Chuang, Shih-Chieh, Tsai, Tsung-Yu, Hsiao, Wang-De, Huang, Guan-Tarn, and Peng, Cheng-Yuan

Subjects
Original Article
Abstract

Biomarkers for predicting the treatment efficacy of immune checkpoint inhibitor (ICI)-based therapy in patients with unresectable hepatocellular carcinoma (uHCC) are crucial. Previous studies demonstrated that C-reactive protein and alpha-fetoprotein (AFP) in immunotherapy (CRAFITY) score at baseline predicted treatment outcomes and that patients with uHCC with AFP response, defined as > 15% decline in AFP level within the initial 3 months of ICI-based therapy, had favorable outcomes when receiving ICI-based therapy. However, whether the combination of CRAFITY score and AFP response could be used to predict treatment efficacy of programmed death-1 (PD-1) blockade-based therapy in uHCC patients remains unclear. We retrospectively enrolled 110 consecutive uHCC patients from May 2017 to March 2022. The median ICI treatment duration was 2.85 (1.67-6.63) months, and 87 patients received combination therapies. The objective response and disease control rates were 21.8% and 46.4%, respectively. The duration of progression-free survival (PFS) and overall survival (OS) was 2.87 (2.16-3.58) months and 8.20 (4.23-12.17) months, respectively. We categorized patients into three groups based on CRAFITY score (2 vs 0/1) and AFP response: patients with a CRAFITY score of 0/1 and AFP response (Group 1), those with a CRAFITY score of 2 and no AFP response (group 3), and those who did not belong to Group 1 and 3 (i.e., Group 2). The combination of CRAFITY score and AFP response could predict disease control and could predict PFS compared with CRAFITY score or AFP response alone. The combination of CRAFITY score and AFP response was an independent predictor of OS (Group 2 vs Group 1, HR: 4.513, 95% CI 1.990-10.234; Group 3 vs Group 1, HR: 3.551, 95% CI 1.544-8.168). Our findings indicated that the combination of CRAFITY score and AFP response could predict disease control, PFS, and OS in uHCC patients receiving PD-1 blockade-based immunotherapy.

Published
2023

8. Deep-ADCA: Development and Validation of Deep Learning Model for Automated Diagnosis Code Assignment Using Clinical Notes in Electronic Medical Records

Author

Jakir Hossain Bhuiyan Masud, Chiang Shun, Chen-Cheng Kuo, Md. Mohaimenul Islam, Chih-Yang Yeh, Hsuan-Chia Yang, and Ming-Chin Lin

Subjects
clinical note, diagnosis codes, medication lists, natural language processing, convolutional neural network, Medicine (miscellaneous)
Abstract

Currently, the International Classification of Diseases (ICD) codes are being used to improve clinical, financial, and administrative performance. Inaccurate ICD coding can lower the quality of care, and delay or prevent reimbursement. However, selecting the appropriate ICD code from a patient’s clinical history is time-consuming and requires expert knowledge. The rapid spread of electronic medical records (EMRs) has generated a large amount of clinical data and provides an opportunity to predict ICD codes using deep learning models. The main objective of this study was to use a deep learning-based natural language processing (NLP) model to accurately predict ICD-10 codes, which could help providers to make better clinical decisions and improve their level of service. We retrospectively collected clinical notes from five outpatient departments (OPD) from one university teaching hospital between January 2016 and December 2016. We applied NLP techniques, including global vectors, word to vectors, and embedding techniques to process the data. The dataset was split into two independent training and testing datasets consisting of 90% and 10% of the entire dataset, respectively. A convolutional neural network (CNN) model was developed, and the performance was measured using the precision, recall, and F-score. A total of 21,953 medical records were collected from 5016 patients. The performance of the CNN model for the five different departments was clinically satisfactory (Precision: 0.50~0.69 and recall: 0.78~0.91). However, the CNN model achieved the best performance for the cardiology department, with a precision of 69%, a recall of 89% and an F-score of 78%. The CNN model for predicting ICD-10 codes provides an opportunity to improve the quality of care. Implementing this model in real-world clinical settings could reduce the manual coding workload, enhance the efficiency of clinical coding, and support physicians in making better clinical decisions.

Published
2022

11. Measurement of hadronic cross-section and preliminary results on the pion form-factor using the radiative return at DAPHNE

Author

A. ALOISIO, F. AMBROSINO, A. ANTONELLI, M. ANTONELLI, C. BACCI, G. BENCIVENNI, S. BERTOLUCCI, C. BINI, C. BLOISE, V. BOCCI, F. BOSSI, P. BRANCHINI, S. A. BULYCHJOV, R. CALOI, P. CAMPANAN, G. CAPON, G. CARBONI, M. CASARSA, V. CASAVOLA, G. CATALDI, F. CERADINI, F. CERVELLI, F. CEVENINI, G. CHIEFARI, P. CIAMBRONE, S. CONETTI, E. DE LUCIA, G. DE ROBERTIS, P. DE SIMONE, G. DE ZORZI, S. DELL'AGNELLO, A. DENIG, A. DI DOMENICO, C. DI DONATO, S. DI FALCO, A. DORIA, M. DREUCCI, O. ERRIQUEZ, A. FARILLA, G. FELICI, A. FERRARI, M. L. FERRER, G. FINOCCHIARO, C. FORTI, A. FRANCESCHI, P. FRANZINI, C. GATTI, P. GAUZZI, S. GIOVANNELLA, E. FORINI, F. GRANCAGNOLO, E. GRAZIANI, S. W. HAN, M. INCAGLI, L. INGROSSO, W. KLUGE, CHEN CHENG KUO, V. KULIKOV, F. LACAVA, G. LANFRANCHI, J. LEE FRANZINI, D. LEONE, F. LU, M. MARTEMIANOV, M. MATSYUK, W. MEI, L. MEROLA, R. MESSI, S. MISCETTI, M. MOULSON, S. MULLER, F. MURTAS, M. NAPOLITANO, A. NEDOSEKIN, F. NGUYEN, M. PALUTAN, L. PAOLUZI, E. PASQUALUCCI, L. PASSALACQUA, A. PASSERI, V. PATERA, E. PETROLO, L. PONTECORVO, M. PRIMAVERA, F. RUGGIERI, P. SANTANGELO, E. SANTOVETTI, G. SARACINO, R. D. SCHAMBERGER, B. SCIASCIA, A. SCIUBBA, F. SCURI, I. SFILIGOI, T. SPADARO, E. SPIRITI, G. L. TONG, L. TORTORA, E. VALENTE, P. VALENTE, B. VALERIANI, G. VENANZONI, S. VENEZIANO, G. XU, G. W. YU, VENTURA, Andrea, A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, R., Caloi, P., Campanan, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, E., Forini, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kluge, CHEN CHENG, Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., LEE FRANZINI, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, F., Nguyen, M., Palutan, L., Paoluzi, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, L., Pontecorvo, M., Primavera, F., Ruggieri, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, Ventura, Andrea, G., Xu, and G. W., Yu

Abstract

eConf C0209101:WE07

Published
2003

12. Study of the decay phi -> pi(+)pi(-)pi(0) with the KLOE detector

Author

A. ALOISIO, F. AMBROSINO, A. ANTONELLI, M. ANTONELLI, C. BACCI, F. BELLINI, G. BENCIVENNI, S. BERTOLUCCI, C. BINI, C. BLOISE, V. BOCCI, F. BOSSI, P. BRANCHINI, S. A. BULYCHJOV, G. CABIBBO, R. CALOI, P. CAMPANA, G. CAPON, T. CAPUSSELA, G. CARBONI, M. CASARSA, V. CASAVOLA, G. CATALDI, F. CERADINI, F. CERVELLI, F. CEVENINI, G. CHIEFARI, P. CIAMBRONE, S. CONETTI, E. DE LUCIA, G. DE ROBERTIS, P. DE SIMONE, G. DE ZORZI, S. DELL'AGNELLO, A. DENIG, A. DI DOMENICO, C. DI DONATO, S. DI FALCO, B. DI MICCO, A. DORIA, M. DREUCCI, O. ERRIQUEZ, A. FARILLA, G. FELICI, A. FERRARI, M. L. FERRER, G. FINOCCHIARO, C. FORTI, A. FRANCESCHI, P. FRANZINI, C. GATTI, P. GAUZZI, S. GIOVANNELLA, F. GRANCAGNOLO, E. GRAZIANI, S. W. HAN, M. INCAGLI, L. INGROSSO, W. KLUGE, CHEN CHENG KUO, V. KULIKOV, F. LACAVA, G. LANFRANCHI, J. LEE FRANZINI, D. LEONE, F. LU, M. MARTEMIANOV, M. MATSYUK, W. MEI, L. MEROLA, R. MESSI, S. MISCETTI, M. MOULSON, S. MULLER, F. MURTAS, M. NAPOLITANO, A. NEDOSEKIN, F. NGUYEN, M. PALUTAN, E. PASQUALUCCI, L. PASSALACQUA, A. PASSERI, V. PATERA, F. PERFETTO, E. PETROLO, G. PIROZZI, L. PONTECORVO, F. RUGGIERI, P. SANTANGELO, E. SANTOVETTI, G. SARACINO, R. D. SCHAMBERGER, B. SCIASCIA, A. SCIUBBA, F. SCURI, I. SFILIGOI, A. SIBIDANOV, P. SILANO, T. SPADARO, E. SPIRITI, G. L. TONG, L. TORTORA, E. VALENTE, P. VALENTE, B. VALERIANI, G. VENANZONI, S. VENEZIANO, S. VENTURA, R. VERSACI, Y. XU, G. W. YU, GORINI, Edoardo, PRIMAVERA, Margherita, VENTURA, Andrea, A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, F., Bellini, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, T., Capussela, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, B., DI MICCO, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, Gorini, Edoardo, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kluge, CHEN CHENG, Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., LEE FRANZINI, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, F., Nguyen, M., Palutan, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, F., Perfetto, E., Petrolo, G., Pirozzi, L., Pontecorvo, Primavera, Margherita, F., Ruggieri, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, A., Sibidanov, P., Silano, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, Ventura, Andrea, S., Ventura, R., Versaci, Y., Xu, and G. W., Yu

Subjects
e(+)e(-) collisions, KLOE phi meson, rho meson masses and widths, +pi%28%2B%29pi%28-%29pi%280%29%22">phi -> pi(+)pi(-)pi(0)
Abstract

We present a study of the reaction e+e- --> pi+pi-pi0 at the phi peak W=M(phi)=1019.4 MeV observed with the KLOE detector at Dafne. The reaction is dominated by phi production and decay, e+e- --> phi --> pi+pi-pi0. From a fit to the Dalitz plot density distribution we obtain the rho-meson parameters for its three charge states. We also find the relative amplitudes for phi --> rhopi and phi -> pi+pi-pi0 and the cross-section for e+e- --> omega pi0 with omega --> pi+pi-.

Published
2003

13. Measurement of Gamma (phi-> eta-prime gamma) / Gamma (phi -> eta gamma) and the pseudoscalar mixing angle

Author

A. ALOISIO, F. AMBROSINO, A. ANTONELLI, M. ANTONELLI, C. BACCI, G. BENCIVENNI, S. BERTOLUCCI, C. BINI, C. BLOISE, V. BOCCI, F. BOSSI, P. BRANCHINI, S. A. BULYCHJOV, G. CABIBBO, R. CALOI, P. CAMPANA, G. CAPON, G. CARBONI, M. CASARSA, V. CASAVOLA, G. CATALDI, F. CERADINI, F. CERVELLI, F. CEVENINI, G. CHIEFARI, P. CIAMBRONE, S. CONETTI, E. DE LUCIA, G. DE ROBERTIS, P. DE SIMONE, G. DE ZORZI, S. DELL'AGNELLO, A. DENIG, A. DI DOMENICO, C. DI DONATO, S. DI FALCO, A. DORIA, M. DREUCCI, O. ERRIQUEZ, A. FARILLA, G. FELICI, A. FERRARI, M. L. FERRER, G. FINOCCHIARO, C. FORTI, A. FRANCESCHI, P. FRANZINI, C. GATTI, P. GAUZZI, S. GIOVANNELLA, F. GRANCAGNOLO, E. GRAZIANI, S. W. HAN, M. INCAGLI, L. INGROSSO, W. KLUGE, CHEN CHENG KUO, V. KULIKOV, F. LACAVA, G. LANFRANCHI, J. LEE FRANZINI, D. LEONE, F. LU, M. MARTEMIANOV, M. MATSYUK, W. MEI, L. MEROLA, R. MESSI, S. MISCETTI, M. MOULSON, S. MULLER, F. MURTAS, M. NAPOLITANO, A. NEDOSEKIN, F. NGUYEN, M. PALUTAN, L. PAOLUZI, E. PASQUALUCCI, L. PASSALACQUA, A. PASSERI, V. PATERA, E. PETROLO, G. PIROZZI, C. PISTILLO, L. PONTECORVO, F. RUGGIERI, P. SANTANGELO, E. SANTOVETTI, G. SARACINO, R. D. SCHAMBERGER, B. SCIASCIA, A. SCIUBBA, F. SCURI, I. SFILIGOI, T. SPADARO, E. SPIRITI, G. L. TONG, L. TORTORA, E. VALENTE, P. VALENTE, B. VALERIANI, G. VENANZONI, S. VENEZIANO, Y. XU, Y. YU, GORINI, Edoardo, PRIMAVERA, Margherita, VENTURA, Andrea, A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, Gorini, Edoardo, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kluge, CHEN CHENG, Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., LEE FRANZINI, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, F., Nguyen, M., Palutan, L., Paoluzi, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, G., Pirozzi, C., Pistillo, L., Pontecorvo, Primavera, Margherita, F., Ruggieri, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, Ventura, Andrea, Y., Xu, and Y., Yu

Subjects
KLOE phi meson
Abstract

We have measured the radiative decays phi --> etagamma, phi --> eta'gamma selecting pi(+)pi(-)gammagammagamma final state in a sample of similar to 5 x 10(7) phi-mesons produced at the Frascati phi-factory DAPhiNE. We obtain Gamma(phi --> eta'gamma)/Gamma(phi --> etagamma) = (4.70 +/- 0.47 +/- 0.31) x 10(-3). From this result we derive new accurate values for the branching ratio BR(phi --> eta'gamma) = (6.10 +/- 0.61 +/- 0.43) x 10(-5) and the mixing angle of pseudoscalar mesons in the flavour basis phi(P) = (41.8(-1.6)(+1.9))degrees.

Published
2002

14. Study of the decay phi ->pi(0)pi(0)gamma with the KLOE detector

Author

A. ALOISIO, F. AMBROSINO, A. ANTONELLI, M. ANTONELLI, C. BACCI, G. BENCIVENNI, S. BERTOLUCCI, C. BINI, C. BLOISE, V. BOCCI, F. BOSSI, P. BRANCHINI, S. A. BULYCHJOV, G. CABIBBO, R. CALOI, P. CAMPANA, G. CAPON, G. CARBONI, M. CASARSA, V. CASAVOLA, G. CATALDI, F. CERADINI, F. CERVELLI, F. CEVENINI, G. CHIEFARI, P. CIAMBRONE, S. CONETTI, E. DE LUCIA, G. DE ROBERTIS, P. DE SIMONE, G. DE ZORZI, S. DELL'AGNELLO, A. DENIG, A. DI DOMENICO, C. DI DONATO, S. DI FALCO, A. DORIA, M. DREUCCI, O. ERRIQUEZ, A. FARILLA, G. FELICI, A. FERRARI, M. L. FERRER, G. FINOCCHIARO, C. FORTI, A. FRANCESCHI, P. FRANZINI, C. GATTI, P. GAUZZI, S. GIOVANNELLA, F. GRANCAGNOLO, E. GRAZIANI, S. W. HAN, M. INCAGLI, L. INGROSSO, W. KIM, W. KLUGE, CHEN CHENG KUO, V. KULIKOV, F. LACAVA, G. LANFRANCHI, J. LEE FRANZINI, D. LEONE, F. LU, M. MARTEMIANOV, M. MATSYUK, W. MEI, L. MEROLA, R. MESSI, S. MISCETTI, M. MOULSON, S. MULLER, F. MURTAS, M. NAPOLITANO, A. NEDOSEKIN, F. NGUYEN, M. PALUTAN, L. PAOLUZI, E. PASQUALUCCI, L. PASSALACQUA, A. PASSERI, V. PATERA, E. PETROLO, G. PIROZZI, L. PONTECORVO, F. RUGGIERI, P. SANTANGELO, E. SANTOVETTI, G. SARACINO, R. D. SCHAMBERGER, B. SCIASCIA, A. SCIUBBA, F. SCURI, I. SFILIGOI, T. SPADARO, E. SPIRITI, G. L. TONG, L. TORTORA, E. VALENTE, P. VALENTE, B. VALERIANI, G. VENANZONI, S. VENEZIANO, Y. XU, Y. YU, Y. WU, GORINI, Edoardo, PRIMAVERA, Margherita, VENTURA, Andrea, Aloisio, Alberto, Ambrosino, Fabio, A., Antonelli, M., Antonelli, C., Bacci, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, Chiefari, Giovanni, P., Ciambrone, S., Conetti, E. D., Lucia, G. D., Roberti, P. D., Simone, G. D., Zorzi, S., Dell'Agnello, A., Denig, A. D., Domenico, C. D., Donato, S. D., Falco, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, E., Gorini, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kim, W., Kluge, C., Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., Lee Franzini, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, Merola, Leonardo, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, Napolitano, Marco, A., Nedosekin, F., Nguyen, M., Palutan, L., Paoluzi, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, G., Pirozzi, L., Pontecorvo, M., Primavera, F., Ruggieri, P., Santangelo, E., Santovetti, Saracino, Giulio, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, A., Ventura, Y., Xu, Y., Yu, Y., Wu, A., Aloisio, F., Ambrosino, G., Chiefari, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, Gorini, Edoardo, CHEN CHENG, Kuo, J., LEE FRANZINI, L., Merola, M., Napolitano, Primavera, Margherita, G., Saracino, and Ventura, Andrea

Subjects
e(+)e(-) collisions, KLOE phi meson, SCALAR MESONS, +PI%28-%29PI%28%2B%29PI%28%2B%29+DECAY%22">> PI(-)PI(+)PI(+) DECAY, phi radiative decays, PHI RADIATIVE DECAY, PI(0)PI(0)GAMMA, FINAL-STATES, scalar mesons
Abstract

We have measured the branching ratio BR(phi-->pi(0)pi(0)gamma) with the KLOE detector using a sample of similar to5x10(7) phi decays. phi mesons are produced at DAPhiNE, the Frascati phi-factory. We find BR(phi-->pi(0)pi(0)gamma) = (1.09+/-0.03(stat)+/-0.05(syst)) x 10(-4). We fit the two-pion mass spectrum to models to disentangle contributions from various sources. (C) 2002 Elsevier Science B.V. All rights reserved.

Published
2002

15. Measurement of Gamma(KS->pi+pi-gamma)/Gamma(KS->pi0pi0)

Author

A. ALOISIO, F. AMBROSINO, A. ANTONELLI, M. ANTONELLI, C. BACCI, R. BALDINI FERROLI, G. BENCIVENNI, S. BERTOLUCCI, C. BINI, C. BLOISE, V. BOCCI, F. BOSSI, P. BRANCHINI, S. A. BULYCHJOV, G. CABIBBO, R. CALOI, P. CAMPANA, G. CAPON, G. CARBONI, M. CASARSA, V. CASAVOLA, G. CATALDI, F. CERADINI, F. CERVELLI, F. CEVENINI, G. CHIEFARI, P. CIAMBRONE, S. CONETTI, E. DE LUCIA, G. DE ROBERTIS, P. DE SIMONE, G. DE ZORZI, S. DELL'AGNELLO, A. DENIG, A. DI DOMENICO, C. DI DONATO, S. DI FALCO, A. DORIA, M. DREUCCI, O. ERRIQUEZ, A. FARILLA, G. FELICI, A. FERRARI, M. L. FERRER, G. FINOCCHIARO, C. FORTI, A. FRANCESCHI, P. FRANZINI, C. GATTI, P. GAUZZI, S. GIOVANNELLA, F. GRANCAGNOLO, E. GRAZIANI, S. W. HAN, M. INCAGLI, L. INGROSSO, W. KLUGE, CHEN CHENG KUO, V. KULIKOV, F. LACAVA, G. LANFRANCHI, J. LEE FRANZINI, D. LEONE, F. LU, M. MARTEMIANOV, M. MATSYUK, W. MEI, L. MEROLA, R. MESSI, S. MISCETTI, M. MOULSON, S. MULLER, F. MURTAS, M. NAPOLITANO, A. NEDOSEKIN, F. NGUYEN, M. PALUTAN, L. PAOLUZI, E. PASQUALUCCI, L. PASSALACQUA, A. PASSERI, V. PATERA, E. PETROLO, G. PIROZZI, L. PONTECORVO, F. RUGGIERI, P. SANTANGELO, E. SANTOVETTI, G. SARACINO, R. D. SCHAMBERGER, B. SCIASCIA, A. SCIUBBA, F. SCURI, I. SFILIGOI, T. SPADARO, E. SPIRITI, G. L. TONG, L. TORTORA, E. VALENTE, P. VALENTE, B. VALERIANI, G. VENANZONI, S. VENEZIANO, Y. XU, Y. YU, GORINI, Edoardo, PRIMAVERA, Margherita, VENTURA, Andrea, A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, R., BALDINI FERROLI, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, Gorini, Edoardo, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kluge, CHEN CHENG, Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., LEE FRANZINI, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, F., Nguyen, M., Palutan, L., Paoluzi, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, G., Pirozzi, L., Pontecorvo, Primavera, Margherita, F., Ruggieri, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, Ventura, Andrea, Y., Xu, and Y., Yu

Subjects
KLOE KS meson
Abstract

We have measured the ratio R-S(pi) = Gamma(K-S --> pi(+)pi(-)(gamma))/Gamma(K-S --> pi(0)pi(0)) with the KLOE detector at the DAPhiNE e(+)e(-) collider. This measurement is fully inclusive with respect to the pi(+)pi(-)gamma final state. The sample of over 106 two-pion decays of tagged K-S mesons allows a statistical error as low as similar to 0.1% to be obtained. The accuracy is limited by systematic uncertainties, which are estimated primarily from data. We find R-S(pi) = 2.236 +/- 0.003(stat) +/- 0.015(syst).

Published
2002

16. Detection of phi -> eta' gamma, phi -> eta gamma in pi+ pi- gamma gamma gamma final state with KLOE at DAPHNE

Author

Aloisio, A., Ambrosino, F., Antonelli, A., Antonelli, M., Bacci, C., Barbiellini, G., Bellini, F., Bencivenni, G., Bertolucci, S., Bini, C., Bloise, C., Bocci, V., Bossi, F., Branchini, P., Bulychjov, S. A., Cabibbo, G., Caloi, R., Campana, P., Capon, G., Carboni, G., Casarsa, M., Casavola, V., Cataldi, G., Ceradini, F., Cervelli, F., Cevenini, F., Chiefari, G., Ciambrone, P., Conetti, S., Luciak, E., Robertis, G., Simone, P., Zorzi, G., Agnello, S., Denig, A., Di Domenico, A., Di Donato, C., Di Falco, S., Doria, A., Dreucci, M., Erriquez, O., Farilla, A., Felici, G., Ferrari, A., Ferrer, M. L., Finocchiaro, G., Forti, C., Franceschi, A., Franzini, P., Gatti, C., Gauzzi, P., Giannasi, A., Giovannella, S., Edoardo Gorini, Grancagnolo, F., Graziani, E., Han, S. W., Incagli, M., Ingrosso, L., Kluge, W., CHEN CHENG KUO, Kulikov, V., Lacava, F., Lanfranchi, G., Lee Franzini, J., Leone, D., Lu, F., Martemianov, M., Matsyuk, M., Mei, W., Menicucci, A., Merola, L., Messi, R., Miscetti, S., Moulson, M., Muller, S., Murtas, F., Napolitano, M., Nedosekin, A., Palutan, M., Pasqualucci, E., Passalacqua, L., Passeri, A., Patera, V., Petrolo, E., Picca, D., Pirozzi, G., Pontecorvo, L., Primavera, M., Ruggieri, F., Santangelo, P., Saracino, G., Schamberger, R. D., Sciascia, B., Sciubba, A., Scuri, F., Sfiligoi, I., Shan, J., Silano, P., Spadaro, T., Spiriti, E., Tong, G. L., Tortora, L., Valente, E., Valente, P., Valeriani, B., Venanzoni, G., Veneziano, S., Andrea Ventura, Wu, Y., Xu, G., G W, Yu, Zema, P. F., Zhou, Y., A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, G., Barbiellini, F., Bellini, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E., DE LUCIAK, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, A., Giannasi, S., Giovannella, Gorini, Edoardo, F., Grancagnolo, E., Graziani, S. W., Han, M., Incagli, L., Ingrosso, W., Kluge, CHEN CHENG, Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., LEE FRANZINI, D., Leone, F., Lu, M., Martemianov, M., Matsyuk, W., Mei, A., Menicucci, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, M., Palutan, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, D., Picca, G., Pirozzi, L., Pontecorvo, M., Primavera, F., Ruggieri, P., Santangelo, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, J., Shan, P., Silano, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, Ventura, Andrea, Y., Wu, G., Xu, G. W., Yu, P. F., Zema, and Y., Zhou

Published
2001

20. Extension of deep-ultraviolet lithography for patterning logic gates using alternating phase shifting masks

Author

Chia-Hui Lin, Anthony Yen, Hua-Tai Lin, and Chen-Cheng Kuo

Subjects
Depth of focus, Optics, Materials science, Optical proximity correction, Resist, business.industry, General Engineering, Multiple patterning, Process window, business, Lithography, Exposure latitude, Next-generation lithography
Abstract

We present the combination of alternating phase-shifting masks and rule-based optical proximity correction (OPC) for the patterning of 0.13 μm polysilicon gate lines. Using the optimal process condition, a process window with 1.2 μm of depth of focus (DOF) and 15% exposure latitude is obtained for 0.13 μm isolated lines in resist. In addition, with the application of rule-based OPC, the common DOF for 0.13 μm lines of various line-to-space ratios can be improved from 0 to 0.6 μm.

Published
1999
Full Text
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21. Data acquisition and monitoring for the KLOE detector

Author

Alberto Aloisio, W. Mei, G. Saracino, Alessandro Cardini, G. Finocchiaro, F. Bossi, Enrico Pasqualucci, T. Spadaro, Giuseppe Pirozzi, G. Cataldi, F. Pelucchi, Stefan E. Müller, Margherita Primavera, M. Palutan, S. Miscetti, M. Incagli, D. Fiore, Y. Zhou, Paolo Santangelo, M. Moulson, F. Murtas, A. Di Domenico, Claudio Gatti, Alberto Martini, L. Pacciani, D. Picca, G. Cabibbo, C. Di Donato, S. Di Falco, E. Graziani, E. Santovetti, Cesare Bini, G. Lanfranchi, Leonardo Merola, C. Forti, Alessandra Doria, E. Spiriti, S. Dell'Agnello, Ludovico Pontecorvo, G. Venanzoni, Massimo Antonelli, Barbara Sciascia, M. Martemianov, P. Guarnaccia, Juliet Lee-Franzini, M. L. Ferrer, G. De Robertis, L. Passalacqua, F. Ambrosino, S. Giovannella, L. Tortora, C. Kuo, Stefano Veneziano, A. Passeri, E. Valente, Paolo Ciambrone, B. Valeriani, R. Caloi, P. Gauzzi, P. De Simone, F. Cevenini, Igor Sfiligoi, Cristian Stanescu, P. Branchini, M. Passaseo, Andrea Ferrari, E. De Lucia, Massimo Casarsa, P. Valente, Sergio Cavaliere, Edoardo Gorini, J. Shan, A. Denig, W. Grandegger, R. Messi, V. Bocci, A. Ventura, A., Aloisio, F., Ambrosino, S., Cavaliere, F., Cevenini, C., DI DONATO, A., Doria, D., Fiore, L., Merola, G., Pirozzi, G., Saracino, M., Antonelli, F., Bossi, P., Ciambrone, P., DE SIMONE, S., Dell'Agnello, M. L., Ferrer, G., Finocchiaro, C., Forti, C., Gatti, S., Giovannella, W., Grandegger, G., Lanfranchi, B., Martini, W., Mei, S., Miscetti, M., Moulson, F., Murta, M., Palutan, L., Passalacqua, F., Pelucchi, P., Santangelo, B., Sciascia, I., Sfiligoi, J., Shan, T., Spadaro, P., Valente, Y., Zhou, C., Bini, V., Bocci, G., Cabibbo, R., Caloi, A., Cardini, E., DE LUCIA, A., DI DOMENICO, P., Gauzzi, E., Pasqualucci, M., Passaseo, D., Picca, L., Pontecorvo, E., Valente, S., Veneziano, P., Branchini, E., Graziani, A., Passeri, A., Ferrari, E., Spiriti, C., Stanescu, L., Tortora, M., Casarsa, G., Cataldi, Gorini, Edoardo, Primavera, Margherita, Ventura, Andrea, G., DE ROBERTIS, P., Guarnaccia, A., Denig, CHEN CHENG, Kuo, S., Muller, B., Valeriani, S., DI FALCO, M., Incagli, G., Venanzoni, R., Messi, L., Pacciani, E., Santovetti, J., LEE FRANZINI, M., Martemianov, Cevenini, Francesco, Merola, Leonardo, Napolitano, Marco, Cavaliere, Sergio, Ambrosino, Fabio, C., Di Donato, Aloisio, Alberto, and Saracino, Giulio

Subjects
Physics, Nuclear and High Energy Physics, business.industry, Data management, Detector, Analog-to-digital converter, law.invention, Front and back ends, Data acquisition, law, Data quality, business, Collider, Instrumentation, Throughput (business), Computer hardware, data acquisition, data archiving, database, high throughput, online monitoring
Abstract

The Data Acquisition system for the KLOE experiment, presently running at the Laboratori Nazionali di Frascati DAΦNE collider, has been designed to sustain an acquisition throughput of 50 Mbyte / s for an event rate of 10 kHz . Its two major components are the front end data readout, based on custom buses, and a complex network of computers and storage devices hosting a set of distributed processes. The end result is a seamless data transport from the readout system to the storage library, accompanied by concurrent on line calibrations and data quality control.

Published
2004

22. The KLOE electromagnetic calorimeter

Author

A. Franceschi, Paolo Santangelo, G. Saracino, Alessandra Doria, Ludovico Pontecorvo, M. Martemianov, A. Giannasi, A. G. Denig, P.P. Zhao, Cesare Bini, G. Barbiellini, W. Mei, W. Kim, L. Passalacqua, C. Di Donato, P. Campana, Teimuraz Lomtadze, S. Dell'Agnello, R. Caloi, C. Kuo, G. Cabibbo, G. Venanzoni, Marco Adinolfi, M. Incagli, P. Gauzzi, M. L. Ferrer, G. De Zorzi, Andrea Ferrari, Fabrizio Scuri, Claudio Gatti, C. Bloise, A. Ventura, Margherita Primavera, P. Silano, G. Lanfranchi, D. Picca, L. Pacciani, F. Anulli, F. Ambrosino, S. Di Falco, Chao Zhang, S. Moccia, M.L. Gao, Yican Wu, Paolo Franzini, S. Wölfle, E. Santovetti, A. Passeri, S. Miscetti, Enrico Pasqualucci, Massimo Casarsa, P. Valente, Stefan E. Müller, L. Keeble, Barbara Sciascia, G. Cataldi, E. De Lucia, E. Spiriti, A. Di Domenico, T. Spadaro, L. Tortora, L. Ingrosso, Juliet Lee-Franzini, F. Murtas, Yuehong Xie, C.S. Mao, R. Messi, A. Antonelli, P. F. Zema, V. Bocci, H.G. Han, F. Bossi, S. Giovannella, S. Bertolucci, B. Valeriani, F. Cervelli, P. Branchini, M. Palutan, J.Q. Zhang, G. Finocchiaro, O. Erriquez, Giuseppe Pirozzi, M. Moulson, C. Forti, S.W. Han, P. De Simone, M. Palomba, A. Farilla, Igor Sfiligoi, Filippo Ceradini, Paolo Ciambrone, G. Bencivenni, Xiaojing Huang, Massimo Antonelli, E. Graziani, R. D. Schamberger, M., Adinolfi, F., Ambrosino, A., Antonelli, M., Antonelli, F., Anulli, G., Barbiellini, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, G., Cabibbo, R., Caloi, P., Campana, M., Casarsa, G., Cataldi, F., Ceradini, F., Cervelli, P., Ciambrone, E., DE LUCIA, P., DE SIMONE, G., DE ZORZI, S., Dell'Agnello, A., Denig, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, A., Doria, O., Erriquez, A., Farilla, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, M. L., Gao, C., Gatti, P., Gauzzi, A., Giannasi, S., Giovannella, E., Graziani, H. G., Han, S. W., Han, X., Huang, M., Incagli, L., Ingrosso, L., Keeble, W., Kim, CHEN CHENG, Kuo, G., Lanfranchi, J., LEE FRANZINI, T., Lomtadze, C. S., Mao, M., Martemyanov, W., Mei, R., Messi, S., Miscetti, S., Moccia, M., Moulson, S., Muller, F., Murta, L., Pacciani, M., Palomba, M., Palutan, E., Pasqualucci, L., Passalacqua, A., Passeri, D., Picca, G., Pirozzi, L., Pontecorvo, Primavera, Margherita, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, F., Scuri, I., Sfiligoi, P., Silano, T., Spadaro, E., Spiriti, L., Tortora, P., Valente, B., Valeriani, G., Venanzoni, Ventura, Andrea, S., Wolfle, Y., Wu, Y. G., Xie, P. F., Zema, C. D., Zhang, J. Q., Zhang, P. P., Zhao, Ambrosino, Fabio, E. D., Lucia, P. D., Sinione, G. D., Zorzi, A. D., Domenico, C. D., Donato, S. D., Falco, C., Kuo, J., Lee Franzini, M., Martemianov, M., Primavera, Saracino, Giulio, A., Ventura, Adinolfi, M., Antonelli, A., Antonelli, M., Anulli, F., Barbiellini, G., Bencivenni, G., Bertolucci, S., Bini, C., Bloise, C., Bocci, V., Bossi, F., Branchini, P., Cabibbo, G., Caloi, R., Campana, P., Casarsa, M., Cataldi, G., Ceradini, F., Cervelli, F., Ciambrone, P., De Lucia, E., De Simone, P., De Zorzi, G., Dell'Agnello, S., Denig, A., Di Domenico, A., Di Donato, C., Di Falco, S., Doria, A., Erriquez, O., Farilla, A., Ferrari, A., Ferrer, M. L., Finocchiaro, G., Forti, C., Franceschi, A., Franzini, P., Gao, M. L., Gatti, C., Gauzzi, P., Giannasi, A., Giovannella, S., Graziani, E., Han, H. G., Han, S. W., Huang, X., Incagli, M., Ingrosso, L., Keeble, L., Kim, W., Kuo, C., Lanfranchi, G., Lee Franzini, J., Lomtadze, T., Mao, C. S., Martemianov, M., Mei, W., Messi, R., Miscetti, S., Moccia, S., Moulson, M., Muller, S., Murtas, F., Pacciani, L., Palomba, M., Palutan, M., Pasqualucci, E., Passalacqua, L., Passeri, A., Picca, D., Pirozzi, G., Pontecorvo, L., Primavera, M., Santangelo, P., Santovetti, E., Schamberger, R. D., Sciascia, B., Scuri, F., Sfiligoi, I., Silano, P., Spadaro, T., Spiriti, E., Tortora, L., Valente, P., Valeriani, B., Venanzoni, G., Ventura, A., Wolfle, S., Wu, Y., Xie, Y. G., Zema, P. F., Zhang, C. D., Zhang, J. Q., and Zhao, P. P.

Subjects
Physics, Particle physics, Electrogmanetic calorimeter, Nuclear and High Energy Physics, Photon, Luminosity (scattering theory), KLOE Dafne, Calorimeter (particle physics), electromagnetic calorimeter, scintillating fibres, time resolution, Physics::Instrumentation and Detectors, Astrophysics::High Energy Astrophysical Phenomena, Elementary particle, Particle detector, Nuclear physics, KLOE, Scintillation counter, Calibration, Measuring instrument, Physics::Accelerator Physics, High Energy Physics::Experiment, Instrumentation
Abstract

The KLOE detector was designed primarily For the study of CP violation in neutral kaon decays at DAPhiNE, the Frascati Phi-factory. The detector consists of a tracker and an electromagnetic calorimeter. A lead-scintillating-fiber sampling calorimeter satisfies best the requirements of the experiment. providing adequate energy resolution and superior timing accuracy. We describe in the following the construction of the calorimeter, its calibration and how the calorimeter information is used to obtain energy, point of entry and time of the arrival of photons, electrons and charged particles. With e(+)e(-) collision data at DAPhiNE for an integrated luminosity of some 2 pb(-1) we find for electromagnetic showers, an energy resolution of 5.7%/rootE(GeV) and a time resolution of 54/rootE(GeV) ps. We also present a measurement of efficiency for low energy photons. (C) 2002 Elsevier Science B.V. All rights reserved.

Published
2002

23. The QCAL tile calorimeter of KLOE

Author

M. Adinolfi, M. Antonelli, C. Bini, V. Bocci, F. Bossi, P. Branchini, 1, G. Cabibbo, R. Caloi, G. Carboni, M. Casarsa, G. Cataldi, P. Ciambrone, S. Conetti, E. De Lucia, P. De Simone, S. Dell’ Agnello, A. Denig, A. Di Domenico, S. Di Falco, A. Doria, A. Ferrari, G. Finocchiaro, C. Forti, A. Franceschi, P. Franzini, C. Gatti, P. Gauzzi, S. Giovannella, E. Graziani, M. Incagli, C. Kuo, G. Lanfranchi, M. Martemianov, W. Mei, R. Messi, S. Moccia, M. Moulson, S. Müller, C. T. Murphy, F. Murtas, L. Pacciani, M. Palutan, E. Pasqualucci, L. Passalacqua, A. Passerie, D. Picca, G. Pirozzi, L. Pontecorvo, M. Primavera, E. Santovetti, B. Sciascia, I. Sfiligoi, T. Spadaro, E. Spiriti, P. Valente, B. Valeriani, G. Venanzoni, A. Ventura, AMBROSINO, FABIO, DI DONATO, CAMILLA, SARACINO, GIULIO, M., Adinolfi, Ambrosino, Fabio, M., Antonelli, C., Bini, V., Bocci, F., Bossi, P., Branchini, G., Cabibbo, R., Caloi, G., Carboni, M., Casarsa, G., Cataldi, P., Ciambrone, S., Conetti, E., De Lucia, P., De Simone, S., Dell’ Agnello, A., Denig, A., Di Domenico, DI DONATO, Camilla, S., Di Falco, A., Doria, A., Ferrari, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, E., Graziani, M., Incagli, C., Kuo, G., Lanfranchi, M., Martemianov, W., Mei, R., Messi, S., Moccia, M., Moulson, S., Müller, C. T., Murphy, F., Murta, L., Pacciani, M., Palutan, E., Pasqualucci, L., Passalacqua, A., Passerie, D., Picca, G., Pirozzi, L., Pontecorvo, M., Primavera, E., Santovetti, Saracino, Giulio, B., Sciascia, I., Sfiligoi, T., Spadaro, E., Spiriti, P., Valente, B., Valeriani, G., Venanzoni, A., Ventura, F., Ambrosino, E., DE LUCIA, P., DE SIMONE, S., Dell'Agnello, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, CHEN CHENG, Kuo, M., Martemyanov, S., Mueller, A., Passeri, Primavera, Margherita, G., Saracino, and Ventura, Andrea

Subjects
Physics, Nuclear and High Energy Physics, Photomultiplier, Calorimeter, KLOE Dafne, Spectrometer, Interaction point, Physics::Instrumentation and Detectors, Cosmic ray, Scintillator, Wavelength shifter, Nuclear physics, calorimeters in nuclear and particle physics, Time of flight, Measuring instrument, Physics::Accelerator Physics, High Energy Physics::Experiment, veto, Instrumentation, tile
Abstract

The quadrupole tile calorimeters of KLOE (QCAL) are two compact detectors placed close to the interaction point and surrounding the focusing quadrupoles. Their purpose is to increase the hermeticity of KLOE calorimetry. Each QCAL consists of a sampling structure of lead plates and scintillator tiles with wavelength shifter (WLS) fibers and mesh photomultiplier readout arranged in 16 azimuthal sectors. The arrangement of WLS fibers allows the measurement of the longitudinal position of the showers from time of flight. In this paper we describe the QCAL design and assembly and present preliminary results obtained with both cosmic rays and photons from KL decays. The time and energy calibration procedures are also discussed in detail.

Published
2002

24. Study of the decay phi ->eta pi(0)gamma with the KLOE detector

Author

Aloisio, A, Ambrosino, F, Antonelli, A, Antonelli, M, Bacci, C, Bencivenni, G, Bertolucci, S, Bini, C, Bloise, C, Bocci, V, Bossi, F, Branchini, P, Bulychjov, Sa, Cabibbo, G, Caloi, R, Campana, P, Capon, G, Carboni, G, Casarsa, M, Casavola, V, Cataldi, G, Ceradini, F, Cervelli, F, Cevenini, F, Chiefari, G, Ciambrone, P, Conetti, S, De Lucia, E, De Robertis, G, De Simone, P, De Zorzi, G, Dell'Agnello, S, Denig, A, Di Domenico, A, Di Donato, C, Di Falco, S, Doria, A, Dreucci, M, Erriquez, O, Farilla, A, Felici, G, Ferrari, A, Ferrer, Ml, Finocchiaro, G, Forti, C, Franceschi, A, Franzini, P, Gatti, C, Gauzzi, P, Giovannella, S, Gorini, E, Grancagnolo, F, Graziani, E, Han, Sw, Huang, X, Incagli, M, Ingrosso, L, Kluge, W, Kuo, C, Kulikov, V, Lacava, F, Lanfranchi, G, Lee Franzini, J, Leone, D, Lu, F, Luisi, C, Martemianov, M, Matsyuk, M, Mei, W, Merola, L, Messi, R, Miscetti, S, Moulson, M, Muller, S, Murtas, F, Napolitano, M, Nedosekin, A, Nguyen, F, Palutan, M, Paoluzi, L, Pasqualucci, E, Passalacqua, L, Passeri, A, Patera, V, Petrolo, E, Pirozzi, G, Pontecorvo, L, Primavera, M, Ruggieri, F, Santangelo, P, Santovetti, E, Saracino, G, Schamberger, Rd, Sciascia, B, Sciubba, A, Scuri, Fabrizio, Sfiligoi, I, Spadaro, T, Spiriti, E, Tong, Gl, Tortora, L, Valente, E, Valente, P, Valeriani, B, Venanzoni, G, Veneziano, S, Ventura, A, Xu, Y, Yu, Y., A., Aloisio, F., Ambrosino, A., Antonelli, M., Antonelli, C., Bacci, G., Bencivenni, S., Bertolucci, C., Bini, C., Bloise, V., Bocci, F., Bossi, P., Branchini, S. A., Bulychjov, G., Cabibbo, R., Caloi, P., Campana, G., Capon, G., Carboni, M., Casarsa, V., Casavola, G., Cataldi, F., Ceradini, F., Cervelli, F., Cevenini, G., Chiefari, P., Ciambrone, S., Conetti, E. D., Lucia, G. D., Roberti, P. D., Simone, G. D., Zorzi, S., Dell'Agnello, A., Denig, A. D., Domenico, C. D., Donato, S. D., Falco, A., Doria, M., Dreucci, O., Erriquez, A., Farilla, G., Felici, A., Ferrari, M. L., Ferrer, G., Finocchiaro, C., Forti, A., Franceschi, P., Franzini, C., Gatti, P., Gauzzi, S., Giovannella, Gorini, Edoardo, F., Grancagnolo, E., Graziani, S. W., Han, X., Huang, M., Incagli, L., Ingrosso, W., Kluge, C., Kuo, V., Kulikov, F., Lacava, G., Lanfranchi, J., Lee Franzini, D., Leone, F., Lu, C., Luisi, M., Martemianov, M., Matsyuk, W., Mei, L., Merola, R., Messi, S., Miscetti, M., Moulson, S., Muller, F., Murta, M., Napolitano, A., Nedosekin, F., Nguyen, M., Palutan, L., Paoluzi, E., Pasqualucci, L., Passalacqua, A., Passeri, V., Patera, E., Petrolo, G., Pirozzi, L., Pontecorvo, Primavera, Margherita, F., Ruggieri, P., Santangelo, E., Santovetti, G., Saracino, R. D., Schamberger, B., Sciascia, A., Sciubba, F., Scuri, I., Sfiligoi, T., Spadaro, E., Spiriti, G. L., Tong, L., Tortora, E., Valente, P., Valente, B., Valeriani, G., Venanzoni, S., Veneziano, A., Ventura, Y., Xu, Y., Yu, E., DE LUCIA, G., DE ROBERTIS, P., DE SIMONE, G., DE ZORZI, A., DI DOMENICO, C., DI DONATO, S., DI FALCO, CHEN CHENG, Kuo, J., LEE FRANZINI, and Ventura, Andrea

Subjects
scalar mesons, phi radiative decays, e(+)e(-), collisions
Abstract

In a sample of 5.3 x 10(7), phi-decays observed with the KLOE detector at the Frascati phi-factory DAPhiDNE we find 605 etapi(o)gamma events with eta --> gammagamma and 197 etapi(o)gamma events with eta --> pi(+)pi(-)pi(o). The decay etapi(o)gamma is dominated by the process phi --> a(o)gamma. From a fit to the etapi(o) mass spectrum we find BR(phi --> a(o)(980)gamma) = (7.4 +/- 0.7) x 10(-5).

Published
2002

26. Combined CRAFITY score and α-fetoprotein response predicts treatment outcomes in patients with unresectable hepatocellular carcinoma receiving anti-programmed death-1 blockade-based immunotherapy.

Author

Hsu WF, Lai HC, Chen CK, Wang HW, Chuang PH, Tsai MH, Chen SH, Chu CS, Su WP, Chou JW, Kao JT, Chen HY, Chuang SC, Tsai TY, Hsiao WD, Huang GT, and Peng CY

Abstract

Biomarkers for predicting the treatment efficacy of immune checkpoint inhibitor (ICI)-based therapy in patients with unresectable hepatocellular carcinoma (uHCC) are crucial. Previous studies demonstrated that C-reactive protein and alpha-fetoprotein (AFP) in immunotherapy (CRAFITY) score at baseline predicted treatment outcomes and that patients with uHCC with AFP response, defined as > 15% decline in AFP level within the initial 3 months of ICI-based therapy, had favorable outcomes when receiving ICI-based therapy. However, whether the combination of CRAFITY score and AFP response could be used to predict treatment efficacy of programmed death-1 (PD-1) blockade-based therapy in uHCC patients remains unclear. We retrospectively enrolled 110 consecutive uHCC patients from May 2017 to March 2022. The median ICI treatment duration was 2.85 (1.67-6.63) months, and 87 patients received combination therapies. The objective response and disease control rates were 21.8% and 46.4%, respectively. The duration of progression-free survival (PFS) and overall survival (OS) was 2.87 (2.16-3.58) months and 8.20 (4.23-12.17) months, respectively. We categorized patients into three groups based on CRAFITY score (2 vs 0/1) and AFP response: patients with a CRAFITY score of 0/1 and AFP response (Group 1), those with a CRAFITY score of 2 and no AFP response (group 3), and those who did not belong to Group 1 and 3 (i.e., Group 2). The combination of CRAFITY score and AFP response could predict disease control and could predict PFS compared with CRAFITY score or AFP response alone. The combination of CRAFITY score and AFP response was an independent predictor of OS (Group 2 vs Group 1, HR: 4.513, 95% CI 1.990-10.234; Group 3 vs Group 1, HR: 3.551, 95% CI 1.544-8.168). Our findings indicated that the combination of CRAFITY score and AFP response could predict disease control, PFS, and OS in uHCC patients receiving PD-1 blockade-based immunotherapy., Competing Interests: Cheng-Yuan Peng has served as an advisory committee member for AbbVie, Bristol-Myers Squibb, Gilead, and Roche. All other coauthors have no conflicts of interest to declare., (AJCR Copyright © 2023.)

Published
2023

27. Alpha-fetoprotein response predicts treatment outcomes in patients with unresectable hepatocellular carcinoma receiving immune checkpoint inhibitors with or without tyrosine kinase inhibitors or locoregional therapies.

Author

Hsu WF, Wang HW, Chen CK, Lai HC, Chuang PH, Tsai MH, Su WP, Chen HY, Chu CS, Chou JW, Chen SH, Tsai TY, Hsiao WD, Lin CC, Huang GT, Lin JT, and Peng CY

Abstract

Combined immune checkpoint inhibitors (ICIs) along with tyrosine kinase inhibitors (TKIs) and locoregional therapies have been used increasingly to treat hepatocellular carcinoma (HCC). Biomarkers are required to predict the treatment efficacy of ICIs with or without combination therapies in patients with unresectable HCC. This study enrolled 95 consecutive patients with unresectable HCC from May 2017 to June 2021 from two hospitals retrospectively. Of the 95 patients, 15 and 80 had Barcelona Clinic Liver Cancer stages B and C, respectively. The median ICI treatment duration was 3.43 (1.87-7.87) months, and 77 patients received combination therapies. Radiological imaging was not performed in 13 patients. Objective response and disease control rates were 27.4% and 53.7%, respectively. The duration of progression-free survival (PFS) and overall survival (OS) was 4.07 (1.59-6.54) months and 14.53 (6.93-22.14) months, respectively. Alpha-fetoprotein (AFP) response was defined as a decline of >15% in the serum AFP level within the initial 3 months of ICI therapy according to Youden's index. AFP response was determined to be a predictor of disease control (odds ratio: 11.657, 95% confidence interval [CI]: 2.834-47.941, P=.001). Macrovascular invasion (MVI), AFP response (hazard ratio [HR]: 0.488, 95% CI: 0.255-0.934, P=.030), combination therapy, and disease control were predictors of PFS, and MVI, AFP response (HR: 0.344, 95% CI: 0.160-0.737, P=.006), and disease control were predictors of OS. AFP response was a predictor of disease control, PFS, and OS. These findings indicate that AFP response can serve as a biomarker to predict treatment outcomes in patients with unresectable HCC receiving ICIs with or without TKIs or locoregional therapies., Competing Interests: Cheng-Yuan Peng has served as an advisory committee member for AbbVie, Bristol-Myers Squibb, Gilead, and Merck Sharp & Dohme. All other coauthors have any conflicts of interest to declare., (AJCR Copyright © 2021.)

Published
2021

28. Predictors of response and survival in patients with unresectable hepatocellular carcinoma treated with nivolumab: real-world experience.

Author

Hsu WF, Chuang PH, Chen CK, Wang HW, Tsai MH, Su WP, Chen HY, Yang CY, Lin CC, Huang GT, Lin JT, Lai HC, and Peng CY

Abstract

Real-world predictors of the treatment efficacy of immune checkpoint inhibitors for hepatocellular carcinoma (HCC) are unknown. This retrospective study enrolled 87 consecutive patients with unresectable HCC from May 2017 to December 2019 at two hospitals. Of the 87 patients, 7, 9, 60, and 11 patients had Barcelona Clinic Liver Cancer stages A, B, C, and D, respectively, and 45, 30, and 10 patients were Child-Pugh class A, B, and C, respectively. The median injection numbers of nivolumab and treatment duration were 6 (3-8) and 2.53 (1.47-4.23) months, respectively, and 64.4% of patients received combination therapy. Radiological imaging was not assessed for 25 patients. Objective response (OR) and disease control rates were 19.5% and 39.1%, respectively. A single tumor (odds ratio: 9.542, P = .015) and ≥20% decline in serum α-fetoprotein protein (AFP) levels within the first 3 months of treatment (defined as AFP response, odds ratio: 5.997, P = .042) were predictors of OR. Lack of macrovascular invasion, combination therapy, and AFP response were predictors of progression-free survival. A Cancer of the Liver Italian Program (CLIP) score of 0-2 (hazard ratio [HR]: 3.717, P = .004) and grade 1-2 immune-related adverse events (irAEs, HR: 2.217, P = .049) were predictors of overall survival (OS) in the entire cohort, and a CLIP score of 0-2 (HR: 3.257, P = .009) was a predictor of OS in evaluable patients. IrAEs ≥ grade 3 were noted in 14 patients, and three died as a result. Having a single tumor and AFP response were predictors of OR, and CLIP score was a predictor of OS., Competing Interests: None., (AJCR Copyright © 2020.)

Published
2020

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