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1. Engagement Dynamics in Information Technology Education: A Comparative Analysis of Online vs. Face-to-Face Instruction

Author

Semiral Öncü, Merve Çolakoglu, and Huseyin Colak

Abstract

The purpose of this study was to investigate whether taking a course online or face-to-face matters in terms of student engagement and achievement. Gender differences were also examined. The level of student engagement in an information technology course in a freshman sample from a school of education was surveyed and compared in two consecutive years where the course was taught online in the first year and face-to-face in the second year. There were a total of 129 students, 62 in the online mode and 67 in the face-to-face mode. Data were collected using a survey that included a student engagement scale, as well as midterm and final exams. Nonparametric analyses were used due to data with non-normal distributions for some of the dependent variables, with the Mann-Whitney U test being the main form of analysis for group comparisons. Regarding gender, female students who received face-to-face instruction lost interest in the course toward the final exams, as evidenced by significantly lower engagement scores for both active learning and paying attention. The results show that online versus face-to-face delivery of the computer science course can be more efficient in terms of student engagement, and a similar performance score as in the face-to-face mode can be achieved with less effort to be present at school. In addition, it is evident that female students need more support for greater engagement when the mode of delivery must be face-to-face.

Published
2024

2. Are Social Studies Teachers Ready for Legal Literacy Education?

Author

Gulbahar Ozkaya and Kerem Colak

Abstract

This study aimed to assess social studies teachers' legal literacy levels and their perspectives on legal literacy education. The study was conducted with 160 social studies teachers in the first stage and 10 selected teachers in the second. Instruments were the legal literacy scale and a semi-structured interview form. Quantitative data were analyzed using descriptive and inferential statistics, while qualitative data were analyzed using content analysis. The results indicated that teachers generally possess a high level of legal literacy. However, a notable portion of them do not perceive themselves as legally literate, citing insufficient education, knowledge, experience, and interest in law as reasons. Furthermore, challenges related to the abstract nature of the subject and difficulties in effectively teaching it to students were identified. To address these issues, teachers suggested real-life applications, making the lessons more tangible, developing teaching materials, and enhancing professional development.

Published
2024

3. The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset.

Author

Rudie, Jeffrey, Lin, Hui-Ming, Ball, Robyn, Jalal, Sabeena, Prevedello, Luciano, Nicolaou, Savvas, Marinelli, Brett, Flanders, Adam, Magudia, Kirti, Shih, George, Davis, Melissa, Mongan, John, Chang, Peter, Berger, Ferco, Hermans, Sebastiaan, Law, Meng, Richards, Tyler, Grunz, Jan-Peter, Kunz, Andreas, Mathur, Shobhit, Galea-Soler, Sandro, Chung, Andrew, Afat, Saif, Kuo, Chin-Chi, Aweidah, Layal, Villanueva Campos, Ana, Somasundaram, Arjuna, Sanchez Tijmes, Felipe, Jantarangkoon, Attaporn, Kayat Bittencourt, Leonardo, Brassil, Michael, El Hajjami, Ayoub, Dogan, Hakan, Becircic, Muris, Bharatkumar, Agrahara, Júdice de Mattos Farina, Eduardo, and Colak, Errol

Subjects
CT, Kidney, Large Bowel, Liver, Small Bowel, Spleen, Trauma, Humans, Abdominal Injuries, Tomography, X-Ray Computed, Male, Female, Adult
Abstract

Supplemental material is available for this article.

Published
2024

4. Thinking beyond Deficits in Southwest China: Perspectives of Ethnic Minority Teachers on Academic Achievement Disparities among Students

Author

Qian Liu, Fatma Zehra Colak, and Orhan Agirdag

Abstract

Global and national education agendas are concerned with improving the quality and equality of learning outcomes. School systems involuntarily continue to produce new and perpetuate existing inequities and injustices, particularly for minority students. While previous research has highlighted the potential causes and effects of educational inequity, little is known about the perspectives of teachers with minoritised backgrounds regarding the persistence of and responses to educational disparities. This research draws on the literature on deficit thinking and culturally responsive teaching to explore the views of ethnic minority teachers on students' academic achievement disparities in an ethnically diverse region of China. Interviews with 12 ethnic minority teachers show ethnic, biological and cultural deficit thinking when discussing students' schooling. Participants attributed their deficient-oriented thinking to their earlier teacher education experiences, where they acquired the discourse of "zhiguo minzu" concerning the different sociohistorical developments of minority groups in China. However, teacher participants stated that they also engaged in culturally responsive teaching to support the ethnic identities of their students. These findings draw attention to the multi-layered perspectives of ethnic minority teachers, which comprise both the reproducing and the challenging of inequities about minorities.

Published
2024
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5. The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset

Author

Rudie, Jeffrey D., Lin, Hui-Ming, Ball, Robyn L., Jalal, Sabeena, Prevedello, Luciano M., Nicolaou, Savvas, Marinelli, Brett S., Flanders, Adam E., Magudia, Kirti, Shih, George, Davis, Melissa A., Mongan, John, Chang, Peter D., Berger, Ferco H., Hermans, Sebastiaan, Law, Meng, Richards, Tyler, Grunz, Jan-Peter, Kunz, Andreas Steven, Mathur, Shobhit, Galea-Soler, Sandro, Chung, Andrew D., Afat, Saif, Kuo, Chin-Chi, Aweidah, Layal, Campos, Ana Villanueva, Somasundaram, Arjuna, Tijmes, Felipe Antonio Sanchez, Jantarangkoon, Attaporn, Bittencourt, Leonardo Kayat, Brassil, Michael, Hajjami, Ayoub El, Dogan, Hakan, Becircic, Muris, Bharatkumar, Agrahara G., Farina, Eduardo Moreno Júdice de Mattos, Group, Dataset Curator, Group, Dataset Contributor, Group, Dataset Annotator, and Colak, Errol

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The RSNA Abdominal Traumatic Injury CT (RATIC) dataset is the largest publicly available collection of adult abdominal CT studies annotated for traumatic injuries. This dataset includes 4,274 studies from 23 institutions across 14 countries. The dataset is freely available for non-commercial use via Kaggle at https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection. Created for the RSNA 2023 Abdominal Trauma Detection competition, the dataset encourages the development of advanced machine learning models for detecting abdominal injuries on CT scans. The dataset encompasses detection and classification of traumatic injuries across multiple organs, including the liver, spleen, kidneys, bowel, and mesentery. Annotations were created by expert radiologists from the American Society of Emergency Radiology (ASER) and Society of Abdominal Radiology (SAR). The dataset is annotated at multiple levels, including the presence of injuries in three solid organs with injury grading, image-level annotations for active extravasations and bowel injury, and voxelwise segmentations of each of the potentially injured organs. With the release of this dataset, we hope to facilitate research and development in machine learning and abdominal trauma that can lead to improved patient care and outcomes., Comment: 40 pages, 2 figures, 3 tables

Published
2024

20. Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.

Author

Kitamura, Felipe, Prevedello, Luciano, Colak, Errol, Halabi, Safwan, Lungren, Matthew, Ball, Robyn, Kalpathy-Cramer, Jayashree, Kahn, Charles, Richards, Tyler, Shih, George, Lin, Hui, Andriole, Katherine, Vazirabad, Maryam, Erickson, Bradley, Flanders, Adam, Talbott, Jason, and Mongan, John

Subjects
Artificial Intelligence, Use of AI in Education, Humans, Artificial Intelligence, Radiology, Diagnostic Imaging, Societies, Medical, North America
Abstract

The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organizing these competitions, with a specific emphasis on the creation and curation of high-quality datasets. The collection of diverse and representative medical imaging data involves dealing with issues of patient privacy and data security. Furthermore, ensuring quality and consistency in data, which includes expert labeling and accounting for various patient and imaging characteristics, necessitates substantial planning and resources. Overcoming these obstacles requires meticulous project management and adherence to strict timelines. The article also highlights the potential of crowdsourced annotation to progress medical imaging research. Through the RSNA competitions, an effective global engagement has been realized, resulting in innovative solutions to complex medical imaging problems, thus potentially transforming health care by enhancing diagnostic accuracy and patient outcomes. Keywords: Use of AI in Education, Artificial Intelligence © RSNA, 2024.

Published
2024

21. PV-MPPT Lab: A GUI-Based Education Tool for MPPT Techniques

Author

Korhan Kayisli, Ruhi Zafer Caglayan, and Ilhami Colak

Abstract

This article aims to present the design of a GUI application that serves as an educational and analytical tool. The GUI application is intended for educational purposes, allowing users to learn about the linear and renewable energy sources. This GUI has been designed to explain, teach, and implement maximum power point tracking (MPPT) techniques that enable maximum power extraction from photovoltaic (PV) panels. Contribution: This study introduces a novel educational tool designed to enhance the understanding of different MPPT methods among engineering students. The GUI tool was implemented and utilized throughout a semester in the course named power electronic applications in power systems, specifically aimed at postgraduate level students. Background: Engineering students often encounter challenges in grasping advanced concepts, such as MPPT techniques, which are crucial for optimizing the performance of PV systems. Traditional teaching methods may not fully address the learning needs of students in this complex subject area. Research Question: How does the use of a GUI-based educational tool for MPPT techniques impact the learning outcomes and attitudes of engineering students in a postgraduate course? Methodology: The effectiveness of the GUI was assessed by comparing the performance of students who used this tool with those from the previous year who did not. The study involved a semester-long deployment of the tool in the power electronic applications in power systems course, with participation from students specializing in renewable energy engineering. Findings: Preliminary findings suggest an improvement in the performance of students using the PV-MPPT Lab compared to those from the previous year. The study also indicates positive student attitudes toward the GUI tool, highlighting its potential as an effective learning aid in engineering education.

Published
2024
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23. Service-Learning Projects' Contribution to Students' Development

Author

Bengic-Colak, Gizem, Kabapinar, Yucel, and Ozturk, Cemil

Abstract

The aim of the research is to determine the contribution of the use of the service-learning (SL) approach in social studies courses to the students' development. The participants of this research, which was carried out using qualitative research methodology, are 15 students and two social studies teachers who participated in SL projects within the scope of social studies course. Students had a 16-week experience of SL. Semi-structured interviews were conducted with students and teachers. The content analysis technique was used to analyze the obtained data. The result of the research revealed that the contribution of using SL approach in the social studies course contributed to the academic, personal, social, and citizenship development of the students.

Published
2023

26. Global 30-day morbidity and mortality of surgery for perforated peptic ulcer: GRACE study

Author

Abouelazayem, Mohamed, Jain, Rajesh, Wilson, Michael S. J., Martinino, Alessandro, Balasubaramaniam, Vignesh, Biffl, Walter, Coccolini, Federico, Riera, Manel, Wadhawan, Himanshu, Wazir, Ishaan, Abderaouf, Bettahar, Abramov, Daniil, Abu Jayyab, Mustafa A., Al-Shami, Khayry, Alfarwan, Ahmad, Alhajami, Faris M., Alkaseek, Akram, Alozairi, Ous, Ammar, Ahmed Siddique, Atar, Burak, Baatarjav, Gan-Erdene, Bains, Lovenish, Bakri, Ashraf, Bayramov, Nuru, Bhojwani, Rajesh, Brachini, Gioia, Calini, Giacomo, Campanelli, Michela, Cheng, Shi Yu, Choudhary, Charan Singh, Chowdhury, Sharfuddin, Colak, Elif, Das, Jayanta Kumar, Dawani, Surrendar, Dönmez, Turgut, Elzayat, Ibrahim, Erdene, Sarnai, Faizi, Tashaba Qaiser, Frountzas, Maximos, Gafsi, Besma, Gentileschi, Paolo, Guler, Mert, Gupta, Gaurav, Harkati, Nour Elhouda, Harris, Matthew, Hasan, Doaa M., Irowa, Omorodion Omoruyi, Jafferi, Salman, Jain, Sumita Agarwal, Jun Han, Lai, Kandiboyina, Satyanarayana Murthy, Karabulut, Mehmetu, Khamees, Almu’atasim, Khan, Shahzeb, Khan, Madiha Masood, Khaw, Cheng Jing, Kisielewski, Michal, Klib, Mohamad, Košir, Jurij A., Krawczyk, Wiktor Jan, Lisi, Giorgio, Makama, Jerry Godfrey, Maqbool, Baila, Marques, Cláudia Neves, Meric, Serhat, Mietła, Mateusz Przemysław, Ads, Alaa Mohamed, Muhumuza, Joshua, Mulita, Francesk, Mustafayeva, Matanat, Omar, Mohammed A., Omarov, Taryel, Pathak, Akshant Anil, Paul, Ratnadeep, Pavone, Giovanna, Podda, Mauro, Raja Ram, Novinth Kumar, Rauf, Fatima, Rauf, Sidra, Safy, Ahmed Mohamed, Sandag, Erdene, Şanlı, Ahmet Necati, Siddiqui, Adeela Z., Sotiropoulou, Maria, Talib, Vikash, Tatar, Cihad, Thota, Anuroop, Tokocin, Merve, Tolat, Aditya, Uchikov, Petar Angelov, Valenzuela, José I., Venkatappa, Sunil Kumar, Verras, Georgios-Ioannis, Vlahović, Ivan, Zreeg, Dafer Abdulhakim S., Cardoso, Victor Roth, Gkoutos, Georgios V., Singhal, Rishi, and Mahawar, Kamal

Published
2024
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32. Long-term effects of maxillary skeletal expander treatment on functional breathing.

Author

Combs, Andrew, Paredes, Ney, Dominguez-Mompell, Ramon, Romero-Maroto, Martin, Zhang, Boshi, Elkenawy, Islam, Sfogliano, Luca, Fijany, Layla, Colak, Ozge, Moon, Won, and Wu, Benjamin

Subjects
Bone-anchored maxillary expander, Functional breathing, Maxillary skeletal expander, Microimplant-assisted rapid palatal expansion
Abstract

OBJECTIVE: : To investigate the long-term effects of maxillary skeletal expander (MSE) treatment on functional breathing. OBJECTIVE: measures of breathing, the peak nasal inspiratory flow (PNIF), and peak oral inspiratory flow (POIF), and subjective measures of breathing, the visual analog scale (VAS) and nasal obstruction symptom evaluation (NOSE) survey, were used to investigate the long-term effects of MSE in functional breathing. Seventeen patients, mean age 19.4 ± 3.9 years treated at the UCLA Orthodontics Clinic were assessed on their functional breathing at 3 timepoints: pre-expansion (T0), post-expansion (T1), and post-orthodontic treatment (T2). RESULTS: : Immediately after expansion (T1), all the objective functional breathing values were significantly increased in comparison to T0 (P < 0.05). The VAS total, VAS right and VAS left were significantly lower at T1 in comparison to T0 (P < 0.05). At 26.8 ± 3.9 months after MSE expansion (T2), PNIF total, PNIF right, PNIF left, and POIF were significantly higher when compared to T0 (P < 0.05). Also, VAS total, VAS right and VAS left were significantly lower at T2 when compared to T0 (P < 0.05). Additionally, there was a positive correlation between PNIF and the magnitude of expansion at anterior nasal spine and zygomaticomaxillary point (ZMA). There was a positive correlation between total VAS and the magnitude of expansion at the ZMA. There were no significant changes for the NOSE subjective breathing measurement at all time comparisons. CONCLUSIONS: : Overall, MSE treatment produces an increased objective and subjective airway improvement that continues to remain stable in the long-term post expansion.

Published
2024

33. Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge.

Author

Lee, Ghee, Flanders, Adam, Richards, Tyler, Kitamura, Felipe, Colak, Errol, Lin, Hui, Ball, Robyn, Prevedello, Luciano, and Talbott, Jason

Subjects
Artificial Intelligence Algorithms, CT, Cervical Spine, Fracture Detection, Head/Neck, Machine Learning, Male, Humans, Middle Aged, Artificial Intelligence, Retrospective Studies, Algorithms, Spinal Fractures, Fractures, Bone, Cervical Vertebrae
Abstract

Purpose To evaluate and report the performance of the winning algorithms of the Radiological Society of North America Cervical Spine Fracture AI Challenge. Materials and Methods The competition was open to the public on Kaggle from July 28 to October 27, 2022. A sample of 3112 CT scans with and without cervical spine fractures (CSFx) were assembled from multiple sites (12 institutions across six continents) and prepared for the competition. The test set had 1093 scans (private test set: n = 789; mean age, 53.40 years ± 22.86 [SD]; 509 males; public test set: n = 304; mean age, 52.51 years ± 20.73; 189 males) and 847 fractures. The eight top-performing artificial intelligence (AI) algorithms were retrospectively evaluated, and the area under the receiver operating characteristic curve (AUC) value, F1 score, sensitivity, and specificity were calculated. Results A total of 1108 contestants composing 883 teams worldwide participated in the competition. The top eight AI models showed high performance, with a mean AUC value of 0.96 (95% CI: 0.95, 0.96), mean F1 score of 90% (95% CI: 90%, 91%), mean sensitivity of 88% (95% Cl: 86%, 90%), and mean specificity of 94% (95% CI: 93%, 96%). The highest values reported for previous models were an AUC of 0.85, F1 score of 81%, sensitivity of 76%, and specificity of 97%. Conclusion The competition successfully facilitated the development of AI models that could detect and localize CSFx on CT scans with high performance outcomes, which appear to exceed known values of previously reported models. Further study is needed to evaluate the generalizability of these models in a clinical environment. Keywords: Cervical Spine, Fracture Detection, Machine Learning, Artificial Intelligence Algorithms, CT, Head/Neck Supplemental material is available for this article. © RSNA, 2024.

Published
2024

39. Goodbye Hartmann trial: a prospective, international, multicenter, observational study on the current use of a surgical procedure developed a century ago

Author

Perrone, Gennaro, Giuffrida, Mario, Abu-Zidan, Fikri, Kruger, Vitor F., Livrini, Marco, Petracca, Gabriele Luciano, Rossi, Giorgio, Tarasconi, Antonio, Tian, Brian W. C. A., Bonati, Elena, Mentz, Ricardo, Mazzini, Federico N., Campana, Juan P., Gasser, Elisabeth, Kafka-Ritsch, Reinhold, Felsenreich, Daniel M., Dawoud, Christopher, Riss, Stefan, Gomes, Carlos Augusto, Gomes, Felipe Couto, Gonzaga, Ricardo Alessandro Teixeira, Canton, Cassio Alfred Brattig, Pereira, Bruno Monteiro, Fraga, Gustavo P., Zem, Leticia Gonçalves, Cordeiro-Fonseca, Vinicius, de Mesquita Tauil, Renato, Atanasov, Boyko, Belev, Nikolay, Kovachev, Nikola, Meléndez, L. Juan José, Dimova, Ana, Dimov, Stefan, Zelić, Zdravko, Augustin, Goran, Bogdanić, Branko, Morić, Trpimir, Chouillard, Elie, Bajul, Melinda, De Simone, Belinda, Panis, Yves, Esposito, Francesco, Notarnicola, Margherita, Lauka, Lelde, Fabbri, Anna, Hentati, Hassen, Fnaiech, Iskander, Aurélien, Venara, Bougard, Marie, Roulet, Maxime, Demetrashvili, Zaza, Pipia, Irakli, Merabishvili, Giorgi, Bouliaris, Konstantinos, Koukoulis, Georgios, Doudakmanis, Christos, Xenaki, Sofia, Chrysos, Emmanuel, Kokkinakis, Stamatios, Vassiliu, Panteleimon, Michalopoulos, Nikolaos, Margaris, Ioannis, Kechagias, Aristotelis, Avgerinos, Konstantinos, Katunin, Jevgeni, Lostoridis, Eftychios, Nagorni, Eleni-Aikaterini, Pujante, Antonio, Mulita, Francesk, Maroulis, Ioannis, Vailas, Michail, Marinis, Athanasios, Siannis, Ioannis, Bourbouteli, Eirini, Manatakis, Dimitrios K., Tasis, Nikolaos, Acheimastos, Vasileios, Maria, Sotiropoulou, Stylianos, Kapiris, Kuzeridis, Harilaos, Korkolis, Dimitrios, Fradelos, Evangelos, Kavalieratos, George, Petropoulou, Thalia, Polydorou, Andreas, Papacostantinou, Ioannis, Triantafyllou, Tania, Kimpizi, Despina, Theodorou, Dimitrios, Toutouzas, Konstantinos, Chamzin, Alexandros, Frountzas, Maximos, Schizas, Dimitrios, Karavokyros, Ioannis, Syllaios, Athanasios, Charalabopoulos, Alexandros, Boura, Maria, Baili, Efstratia, Ioannidis, Orestis, Loutzidou, Lydia, Anestiadou, Elissavet, Tsouknidas, Ioannis, Petrakis, Georgios, Polenta, Eleni, Bains, Lovenish, Gupta, Rahul, Singh, Sudhir K., Khanduri, Archana, Bala, Miklosh, Kedar, Asaf, Pisano, Marcello, Podda, Mauro, Pisanu, Adolfo, Martines, Gennaro, Trigiante, Giuseppe, Lantone, Giuliano, Agrusa, Antonino, Di Buono, Giuseppe, Buscemi, Salvatore, Veroux, Massimiliano, Gioco, Rossella, Veroux, Gastone, Oragano, Luigi, Zonta, Sandro, Lovisetto, Federico, Feo, Carlo V., Pesce, Antonio, Fabbri, Nicolò, Lantone, Giulio, Marino, Fabio, Perrone, Fabrizio, Vincenti, Leonardo, Papagni, Vincenzo, Picciariello, Arcangelo, Rossi, Stefano, Picardi, Biagio, Del Monte, Simone Rossi, Visconti, Diego, Osella, Giulia, Petruzzelli, Luca, Pignata, Giusto, Andreuccetti, Jacopo, D’Alessio, Rossella, Buonfantino, Massimo, Guaitoli, Eleonora, Spinelli, Stefano, Sampietro, Gianluca Matteo, Corbellini, Carlo, Lorusso, Leonardo, Frontali, Alice, Pezzoli, Isabella, Bonomi, Alessandro, Chierici, Andrea, Cotsoglou, Christian, Manca, Giuseppe, Delvecchio, Antonella, Musa, Nicola, Casati, Massimiliano, Letizia, Laface, Abate, Emmanuele, Ercolani, Giorgio, D’Acapito, Fabrizio, Solaini, Leonardo, Guercioni, Gianluca, Cicconi, Simone, Sasia, Diego, Borghi, Felice, Giraudo, Giorgio, Sena, Giuseppe, Castaldo, Pasquale, Cardamone, Eugenia, Portale, Giuseppe, Zuin, Matteo, Spolverato, Ylenia, Esposito, Marialusia, Isernia, Roberta Maria, Di Salvo, Maria, Manunza, Romina, Esposito, Giuseppe, Agus, Marcello, Asti, Emanuele Luigi Giuseppe, Bernardi, Daniele Tiziano, Tonucci, Tommaso Panici, Luppi, Davide, Casadei, Massimiliano, Bonilauri, Stefano, Pezzolla, Angela, Panebianco, Annunziata, Laforgia, Rita, De Luca, Maurizio, Zese, Monica, Parini, Dario, Jovine, Elio, De Sario, Giuseppina, Lombardi, Raffaele, Aprea, Giovanni, Palomba, Giuseppe, Capuano, Marianna, Argenio, Giulio, Orio, Gianluca, Armellino, Mariano Fortunato, Troian, Marina, Guerra, Martina, Nagliati, Carlo, Biloslavo, Alan, Germani, Paola, Aizza, Giada, Monsellato, Igor, Chahrour, Ali Chaouki, Anania, Gabriele, Bombardini, Cristina, Bagolini, Francesco, Sganga, Gabriele, Fransvea, Pietro, Bianchi, Valentina, Boati, Paolo, Ferrara, Francesco, Palmieri, Francesco, Cianci, Pasquale, Gattulli, Domenico, Restini, Enrico, Cillara, Nicola, Cannavera, Alessandro, Nita, Gabriela Elisa, Sarnari, Jlenia, Roscio, Francesco, Clerici, Federico, Scandroglio, Ildo, Berti, Stefano, Cadeo, Alessandro, Filippelli, Alice, Conti, Luigi, Grassi, Carmine, Cattaneo, Gaetano Maria, Pighin, Marina, Papis, Davide, Gambino, Giovanni, Bertino, Vanessa, Schifano, Domenico, Prando, Daniela, Fogato, Luisella, Cavallo, Fabio, Ansaloni, Luca, Picheo, Roberto, Pontarolo, Nicholas, Depalma, Norma, Spampinato, Marcello, D’Ugo, Stefano, Lepre, Luca, Capponi, Michela Giulii, Campa, Rossella Domenica, Sarro, Giuliano, Dinuzzi, Vincenza Paola, Olmi, Stefano, Uccelli, Matteo, Ferrari, Davide, Inama, Marco, Moretto, Gianluigi, Fontana, Michele, Favi, Francesco, Picariello, Erika, Rampini, Alessia, Barberis, Andrea, Azzinnaro, Antonio, Oliva, Alba, Totaro, Luigi, Benzoni, Ilaria, Ranieri, Valerio, Capolupo, Gabriella Teresa, Carannante, Filippo, Caricato, Marco, Ronconi, Maurizio, Casiraghi, Silvia, Casole, Giovanni, Pantalone, Desire, Alemanno, Giovanni, Scheiterle, Maximilian, Ceresoli, Marco, Cereda, Marco, Fumagalli, Chiara, Zanzi, Federico, Bolzon, Stefano, Guerra, Enrico, Lecchi, Francesca, Cellerino, Paola, Ardito, Antonella, Scaramuzzo, Rosa, Balla, Andrea, Lepiane, Pasquale, Tartaglia, Nicola, Ambrosi, Antonio, Pavone, Giovanna, Palini, Gian Marco, Veneroni, Simone, Garulli, Gianluca, Ricci, Claudio, Torre, Beatrice, Russo, Iris Shari, Rottoli, Matteo, Tanzanu, Marta, Belvedere, Angela, Milone, Marco, Manigrasso, Michele, De Palma, Giovanni Domenico, Piccoli, Micaela, Pattacini, Gianmaria Casoni, Magnone, Stefano, Bertoli, Paolo, Pisano, Michele, Massucco, Paolo, Palisi, Marco, Luzzi, Andrea-Pierre, Fleres, Francesco, Clarizia, Guglielmo, Spolini, Alessandro, Kobe, Yoshiro, Toma, Takayuki, Shimamura, Fumihiko, Parker, Robert, Ranketi, Sinkeet, Mitei, Mercy, Svagzdys, Saulius, Pauzas, Henrikas, Zilinskas, Justas, Poskus, Tomas, Kryzauskas, Marius, Jakubauskas, Matas, Zakaria, Andee Dzulkarnaen, Zakaria, Zaidi, Wong, Michael Pak-Kai, Jusoh, Asri Che, Zakaria, Muhammad Nazreen, Cruz, Daniel Rios, Elizalde, Aurea Barbara Rodriguez, Reynaud, Alejandro Bañon, Hernandez, Edgard Efren Lozada, Monroy, Jose maria Victor Palomo, Hinojosa-Ugarte, Diego, Quiodettis, Martha, Du Bois, María Esther, Latorraca, José, Major, Piotr, Pędziwiatr, Michał, Pisarska-Adamczyk, Magdalena, Walędziak, Maciej, Kwiatkowski, Andrzej, Czyżykowski, Łukasz, da Costa, Silvia Dantas, Pereira, Bela, Ferreira, Ana Rita Oliveira, Almeida, Filipe, Rocha, Ricardo, Carneiro, Carla, Perez, Diego Pita, Carvas, João, Rocha, Catarina, Ferreira, Cátia, Marques, Rita, Fernandes, Urânia, Leao, Pedro, Goulart, André, Pereira, Rita Gonçalves, Patrocínio, Sara Daniela Direito, de Mendonça, Nuno Gonçalo Gonçalves, Manso, Maria Isabel Cerqueira, Morais, Henrique Manuel Cardoso, Cardoso, Paulo Sebastião, Calu, Valentin, Miron, Adrian, Toma, Elena Adelina, Gachabayov, Mahir, Abdullaev, Abakar, Litvin, Andrey, Nechay, Taras, Tyagunov, Alexander, Yuldashev, Anvar, Bradley, Alison, Wilson, Michael, Panyko, Arpád, Látečková, Zuzana, Lacko, Vladimír, Lesko, Dusan, Soltes, Marek, Radonak, Jozef, Turrado-Rodriguez, Victor, Termes-Serra, Roser, Morales-Sevillano, Xavier, Lapolla, Pierfrancesco, Mingoli, Andrea, Brachini, Gioia, Degiuli, Maurizio, Sofia, Silvia, Reddavid, Rossella, de Manzoni Garberini, Andrea, Buffone, Angelica, del Pozo, Eduardo Perea, Aparicio-Sánchez, Daniel, Dos Barbeito, Sandra, Estaire-Gómez, Mercedes, Vitón-Herrero, Rebeca, de los Ángeles Gil Olarte-Marquez, Mª, Gil-Martínez, José, Alconchel, Felipe, Nicolás-López, Tatiana, Rahy-Martin, Aida Cristina, Pelloni, María, Bañolas-Suarez, Raquel, Mendoza-Moreno, Fernando, Nisa, Francisca García-Moreno, Díez-Alonso, Manuel, Rodas, María Elisa Valle, Agundez, María Carmona, Andrés, María Inmaculada Pérez, Moreira, Claudia Cristina Lopes, Perez, Aintzane Lizarazu, Ponce, Iñigo Augusto, González-Castillo, Ana María, Membrilla-Fernández, Estela, Salvans, Silvia, Serradilla-Martín, Mario, Pardo, Pablo Sancho, Rivera-Alonso, Daniel, Dziakova, Jana, Huguet, Jose Mugüerza, Valle, Naila Pagès, Ruiz, Enrique Colás, Valcárcel, Cristina Rey, Moreno, Cristina Ruiz, Salazar, Yeniffer Tatiana Moreno, García, Juan Jesús Rubio, Micó, Silvia Sevila, López, Joaquín Ruiz, Farré, Silvia Pérez, Gomez, Maite Santamaria, Petit, Nuria Mestres, Titos-García, Alberto, Aranda-Narváez, Jose Manuel, Romacho-López, Laura, Sánchez-Guillén, Luis, Aranaz-Ostariz, Veronica, Bosch-Ramírez, Marina, Martínez-Pérez, Aleix, Martínez-López, Elías, Sebastián-Tomás, Juan Carlos, Jimenez-Riera, Granada, Jimenez-Vega, Javier, Cuellar, Jose Aurelio Navas, Campos-Serra, Andrea, Muñoz-Campaña, Anna, Gràcia-Roman, Raquel, Alegre, Javier Martínez, Pinto, Francisca Lima, O’Sullivan, Sara Nuñez, Antona, Francisco Blanco, Jiménez, Beatriz Muñoz, López-Sánchez, Jaime, Carmona, Zahira Gómez, Fernández, Rocio Torres, Sierra, Isabel Blesa, de León, Laura Román García, Moreno, Verónica Polaino, Iglesias, Eva, Cumplido, Paola Lora, Bravo, Altea Arango, Simó, Ignacio Rey, Domínguez, Carlota López, Caamaño, Aloia Guerreiro, Lozano, Rafael Calleja, Martínez, Manuel Durán, Torres, Álvaro Naranjo, de Quiros, Javier Tomas Morales Bernaldo, Pellino, Gianluca, Cloquell, Miriam Moratal, Moller, Elsa García, Jalal-Eldin, Sami, Abdoun, Ahmed K., Hamid, Hytham K. S., Lohsiriwat, Varut, Mongkhonsupphawan, Aitsariya, Baraket, Oussama, Ayed, Karim, Abbassi, Imed, Ali, Ali Ben, Ammar, Houssem, Kchaou, Ali, Tlili, Ahmed, Zribi, Imen, Colak, Elif, Polat, Suleyman, Koylu, Zehra Alan, Guner, Ali, Usta, Mehmet Arif, Reis, Murat Emre, Mantoglu, Baris, Gonullu, Emre, Akin, Emrah, Altintoprak, Fatih, Bayhan, Zulfu, Firat, Necattin, Isik, Arda, Memis, Ufuk, Bayrak, Mehmet, Altıntaş, Yasemin, Kara, Yasin, Bozkurt, Mehmet Abdussamet, Kocataş, Ali, Das, Koray, Seker, Ahmet, Ozer, Nazmi, Atici, Semra Demirli, Tuncer, Korhan, Kaya, Tayfun, Ozkan, Zeynep, Ilhan, Onur, Agackiran, Ibrahim, Uzunoglu, Mustafa Yener, Demirbas, Eren, Altinel, Yuksel, Meric, Serhat, Hacım, Nadir Adnan, Uymaz, Derya Salim, Omarov, Nail, Balık, Emre, Tebala, Giovanni D., Khalil, Hany, Rana, Mridul, Khan, Mansoor, Florence, Charlotte, Swaminathan, Christie, Leo, Cosimo Alex, Liasis, Lampros, Watfah, Josef, Trostchansky, Ivan, Delgado, Edward, Pontillo, Marcelo, Latifi, Rifat, Coimbra, Raul, Edwards, Sara, Lopez, Ana, Velmahos, George, Dorken, Ander, Gebran, Anthony, Palmer, Amanda, Oury, Jeffrey, Bardes, James M., Seng, Sirivan Suon, Coffua, Lauren S., Ratnasekera, Asanthi, Egodage, Tanya, Echeverria-Rosario, Karla, Armento, Isabella, Napolitano, Lena M., Sangji, Naveen F., Hemmila, Mark, Quick, Jacob A., Austin, Tyler R., Hyman, Theodore S., Curtiss, William, McClure, Amanda, Cairl, Nicholas, Biffl, Walter L., Truong, Hung P., Schaffer, Kathryn, Reames, Summer, Banchini, Filippo, Capelli, Patrizio, Coccolini, Federico, Sartelli, Massimo, Bravi, Francesca, Vallicelli, Carlo, Agnoletti, Vanni, Baiocchi, Gian Luca, and Catena, Fausto

Published
2024
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47. Biogenic Amine Content and Shelf-Life of Salmon Fillets Packaged in Modified Atmospheres of Low-Level Carbon Monoxide and Different Carbon Dioxide Concentrations

Author

Esra Akkaya, Hilal Colak, Hamparsun Hampikyan, Ayse S. Engin, and Enver B. Bingol

Subjects
atlantic salmon, cold storage, packaging, quality parameters, sensory attributes, Nutrition. Foods and food supply, TX341-641
Abstract

The objective of this study was to determine the biogenic amine levels and quality parameters of Atlantic salmon fillets packaged with a low level of carbon monoxide and varied concentrations of carbon dioxide and stored at 1°C. For this purpose, ambient air packaging and modified atmosphere packaging (MAP) with gas mixtures of CO, CO 2 and N 2 (in a ratio of 0.4/30/69.6); CO 2 , N 2 and O 2 (in the ratios of 40/30/30, 50/30/20, and 60/30/10); and CO 2 and N 2 (in a ratio of 40/60) were applied. Salmon fillets were analyzed for biogenic amine contents and chemical, microbiological and sensorial properties during 27-day cold storage. The study results indicate that salmon fillets stored in cold storage undergo a deterioration process depending on storage time and packaging conditions. The thiobarbituric acid reactive substances, total volatile basic nitrogen and trimethylamine nitrogen values, and biogenic amine levels were lower in CO-MAP and 60% CO 2 -MAP compared to the air-packaged samples in extended storage period. Furthermore, 1.5–2 log bacterial inhibition was recorded in CO-MAP and 60% CO 2 -MAP, which allowed the products to be consumed up to day 21. However, the shelf-life of air-packaged salmon was limited to one week due to the signs of deterioration. In conclusion, modified atmosphere packaging with 0.4% CO and 60% CO 2 significantly extended the shelf-life of cold-stored salmon fillets by maintaining quality characteristics of the products. These alternative gas concentrations can also be effective in the preservation of other fatty fish species under cold storage

Published
2024
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49. Effective Proxy for Human Labeling: Ensemble Disagreement Scores in Large Language Models for Industrial NLP

Author

Du, Wei, Advani, Laksh, Gambhir, Yashmeet, Perry, Daniel J, Shiralkar, Prashant, Xing, Zhengzheng, and Colak, Aaron

Subjects
Computer Science - Computation and Language
Abstract

Large language models (LLMs) have demonstrated significant capability to generalize across a large number of NLP tasks. For industry applications, it is imperative to assess the performance of the LLM on unlabeled production data from time to time to validate for a real-world setting. Human labeling to assess model error requires considerable expense and time delay. Here we demonstrate that ensemble disagreement scores work well as a proxy for human labeling for language models in zero-shot, few-shot, and fine-tuned settings, per our evaluation on keyphrase extraction (KPE) task. We measure fidelity of the results by comparing to true error measured from human labeled ground truth. We contrast with the alternative of using another LLM as a source of machine labels, or silver labels. Results across various languages and domains show disagreement scores provide a better estimation of model performance with mean average error (MAE) as low as 0.4% and on average 13.8% better than using silver labels., Comment: Camera ready version for 2023 EMNLP (The Third Workshop on Natural Language Generation, Evaluation, and Metrics (GEM))

Published
2023

50. Evaluation of the End-of-Unit Evaluation Questions in 6th Grade Science Lesson Book According to the Revised Bloom's Taxonomy

Author

Colak-Seker, Zeynep and Demir, Cihat

Abstract

Aim of this study was to examine the end-of-unit evaluation questions in the 6th Grade Science book of primary education according to the knowledge and cognitive process dimensions of the Revised Bloom Taxonomy. For that purpose, 130 end-of-unit evaluation questions of 6th grade Science textbooks which were approved by the Board of Education and Discipline in Ministry of National Education of Republic of Turkey. The evaluation was performed with document analysis with considering knowledge and cognitive process dimensions of the Revised Bloom Taxonomy. Data of this study were obtained with document analysis which classified as qualitatively research method. Accessing documents, checking authenticity, understanding documents, analyzing and using data steps were performed. Analyzed questions were categorized according to previously published studies of experts, and according to the criteria of "Taxonomy for learning, teaching and Assessing" book written by Anderson et al which is published in 2001 and translated into Turkish by Ozcelik in 2010. Ratio and frequencies were used to reach results. When the unit evaluation questions of the 6th Grade Science Textbook are evaluated according to the cognitive level of the Revised Bloom Taxonomy, it is observed that 60 of the 130 questions are belong to remembering level. When these questions are evaluated according to the knowledge dimension it is observed that 60 of 130 questions are belong to factual knowledge. When the 6th grade units are evaluated as a whole, it's possible to observe that majority of the questions are belong to subcognitive knowledge level. These questions can be considered as factual knowledge level when evaluated according to Revised Bloom's Taxonomy. As a conclusion, it is suggested that the sub-cognitive and metacognitive questions according to the Revised Bloom's Taxonomy should be served equally at unit-end-up questions of the 6th grade of primary school Ministry of National Education approved book.

Published
2022

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