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84 results on '"Hassan, Alia"'

3. Imaging active site chemistry and protonation states : NMR crystallography of the tryptophan synthase α-aminoacrylate intermediate

Author

Holmes, Jacob B., Liu, Viktoriia, Caulkins, Bethany G., Hilario, Eduardo, Ghosh, Rittik K., Drago, Victoria N., Young, Robert P., Romero, Jennifer A., Gill, Adam D., Bogie, Paul M., Paulino, Joana, Wang, Xiaoling, Riviere, Gwladys, Bosken, Yuliana K., Struppe, Jochem, Hassan, Alia, Guidoulianov, Jevgeni, Perrone, Barbara, Mentink-Vigier, Frederic, Chang, Chia-en A., Long, Joanna R., Hooley, Richard J., Mueser, Timothy C., Dunn, Michael F., and Mueller, Leonard J.

Published
2022

4. The roles of mTORC1 in parathyroid gland function in chronic kidney disease‐induced secondary hyperparathyroidism: Evidence from male genetic mouse models and clinical data.

Author

Khalaily, Nareman, Hassan, Alia, Khream, Yasmeen, Naveh‐Many, Tally, and Ben‐Dov, Iddo Z.

Abstract

Secondary hyperparathyroidism (SHP) associated with chronic kidney disease (CKD) contributes to morbidity and mortality, yet the related parathyroid signaling pathways are not fully understood. Previous studies have indicated that the parathyroid mTORC1 pathway is activated in both experimental CKD and hypocalcemia‐induced SHP. Furthermore, mice with parathyroid‐specific mTOR deficiency (PT‐mTOR−/−) exhibit disrupted parathyroid glands, but maintain normal serum PTH levels. Conversely, PT‐Tsc1−/− mice, with mTORC1 hyperactivation, have enlarged glands and high serum PTH and calcium levels. We now uncover links between mTORC1 function, parathyroid gland morphology, and the response to CKD. Despite impaired gland structure, PT‐mTOR−/− mice increased serum PTH to levels similar to controls in response to CKD, but not to acute kidney injury (AKI), highlighting the adaptability of their parathyroid glands to chronic but not acute stimulation. PT‐Tsc1−/− mice, with enlarged glands also exhibited a CKD‐induced rise in serum PTH comparable to controls, but with a reduced magnitude, suggesting compromised secretion capacity. Parathyroid glands from PT‐Tsc1−/− mice displayed sustained high PTH secretion in culture, with no further increase when exposed to calcium‐depleted media, unlike control glands. Complementing these findings, human data from 106 healthcare organizations demonstrated that drug‐induced mTORC1 inhibition is associated with reduced serum PTH and a lower incidence of SHP in kidney transplant recipients. Collectively, our findings underscore the complex interplay between mTORC1 signaling and gland structure in the pathogenesis of SHP. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Impact of COVID-19 Pandemic on Cardiovascular Testing in Asia: The IAEA INCAPS-COVID Study

Author

Einstein, Andrew J., Paez, Diana, Dondi, Maurizio, Better, Nathan, Cerci, Rodrigo, Dorbala, Sharmila, Pascual, Thomas N.B., Raggi, Paolo, Shaw, Leslee J., Villines, Todd C., Vitola, Joao V., Williams, Michelle C., Pynda, Yaroslav, Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Hirschfeld, Cole B., Cohen, Yosef, Goebel, Benjamin, Malkovskiy, Eli, Randazzo, Michael, Choi, Andrew, Lopez-Mattei, Juan, Parwani, Purvi, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qais, Agolti, Mariela, Aguero, Roberto Nicolas, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Bas, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlos, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Lucas, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, López De Munaín, Maria Nieves A., Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matias, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marcos, Noguera, Eduardo, Novoa, Carlos, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matías, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Lucas, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charles, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, William, Verjans, Johan, Voutnis, Demetrius, Wayne, Victor, Wilson, Peter, Wong, David, Wong, Kirby, Younger, John, Feuchtner, Gudrun, Mirzaei, Siroos, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Gheysens, Olivier, Homans, Filip, Moreno-Reyes, Rodrigo, Pasquet, Agnès, Roelants, Veronique, Van De Heyning, Caroline M., Ríos, Raúl Araujo, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Albernaz Siqueira, Maria Helena, Almeida, Augusto, Alves Togni, Paulo Henrique, Andrade, Jose Henrique, Andrade, Luciana, Anselmi, Carlos, Araújo, Roberta, Azevedo, Guilherme, Bezerra, Sabbrina, Biancardi, Rodrigo, Grossman, Gabriel Blacher, Brandão, Simone, Pianta, Diego Bromfman, Carreira, Lara, Castro, Bruno, Chang, Tien, Cunali, Fernando, Jr., Cury, Roberto, Dantas, Roberto, de Amorim Fernandes, Fernando, De Lorenzo, Andrea, De Macedo Filho, Robson, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, De Souza, Thiago Ferreira, Alves, Wilson Furlan, Ghini, Bruno, Goncalves, Luiz, Gottlieb, Ilan, Hadlich, Marcelo, Kameoka, Vinícius, Lima, Ronaldo, Lima, Adna, Lopes, Rafael Willain, Machado e Silva, Ricardo, Magalhães, Tiago, Silva, Fábio Martins, Mastrocola, Luiz Eduardo, Medeiros, Fábio, Meneghetti, José Claudio, Naue, Vania, Naves, Danilo, Nolasco, Roberto, Nomura, Cesar, Oliveira, Joao Bruno, Paixao, Eduardo, De Carvalho, Filipe Penna, Pinto, Ibraim, Possetti, Priscila, Quinta, Mayra, Nogueira Ramos, Rodrigo Rizzo, Rocha, Ricardo, Rodrigues, Alfredo, Rodrigues, Carlos, Romantini, Leila, Sanches, Adelina, Santana, Sara, Sara da Silva, Leonardo, Schvartzman, Paulo, Matushita, Cristina Sebastião, Senra, Tiago, Shiozaki, Afonso, Menezes de Siqueira, Maria Eduarda, Siqueira, Cristiano, Smanio, Paola, Soares, Carlos Eduardo, Junior, José Soares, Bittencourt, Marcio Sommer, Spiro, Bernardo, Mesquita, Cláudio Tinoco, Torreao, Jorge, Torres, Rafael, Uellendahl, Marly, Monte, Guilherme Urpia, Veríssimo, Otávia, Cabeda, Estevan Vieira, Pedras, Felipe Villela, Waltrick, Roberto, Zapparoli, Marcello, Naseer, Hamid, Garcheva-Tsacheva, Marina, Kostadinova, Irena, Theng, Youdaline, Abikhzer, Gad, Barette, Rene, Chow, Benjamin, Dabreo, Dominique, Friedrich, Matthias, Garg, Ria, Hafez, Mohammed Nassoh, Johnson, Chris, Kiess, Marla, Leipsic, Jonathon, Leung, Eugene, Miller, Robert, Oikonomou, Anastasia, Probst, Stephan, Roifman, Idan, Small, Gary, Tandon, Vikas, Trivedi, Adwait, White, James, Zukotynski, Katherine, Canessa, Jose, Muñoz, Gabriel Castro, Concha, Carmen, Hidalgo, Pablo, Lovera, Cesar, Massardo, Teresa, Vargas, Luis Salazar, Abad, Pedro, Arturo, Harold, Ayala, Sandra, Benitez, Luis, Cadena, Alberto, Caicedo, Carlos, Moncayo, Antonio Calderón, Gomez, Sharon, Gutierrez Villamil, Claudia T., Jaimes, Claudia, Londoño, Juan, Londoño Blair, Juan Luis, Pabon, Luz, Pineda, Mauricio, Rojas, Juan Carlos, Ruiz, Diego, Escobar, Manuel Valencia, Vasquez, Andres, Vergel, Damiana, Zuluaga, Alejandro, Gamboa, Isabel Berrocal, Castro, Gabriel, González, Ulises, Baric, Ana, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Jukic, Mladen, Medakovic, Petar, Persic, Viktor, Prpic, Marina, Punda, Ante, Batista, Juan Felipe, Gómez Lauchy, Juan Manuel, Gutierrez, Yamile Marcos, Menéndez, Rayner, Peix, Amalia, Rochela, Luis, Panagidis, Christoforos, Petrou, Ioannis, Engelmann, Vaclav, Kaminek, Milan, Kincl, Vladimír, Lang, Otto, Simanek, Milan, Abdulla, Jawdat, Bøttcher, Morten, Christensen, Mette, Gormsen, Lars Christian, Hasbak, Philip, Hess, Søren, Holdgaard, Paw, Johansen, Allan, Kyhl, Kasper, Norgaard, Bjarne Linde, Øvrehus, Kristian Altern, Rønnow Sand, Niels Peter, Steffensen, Rolf, Thomassen, Anders, Zerahn, Bo, Perez, Alfredo, Escorza Velez, Giovanni Alejandro, Velez, Mayra Sanchez, Abdel Aziz, Islam Shawky, Abougabal, Mahasen, Ahmed, Taghreed, Allam, Adel, Asfour, Ahmed, Hassan, Mona, Hassan, Alia, Ibrahim, Ahmed, Kaffas, Sameh, Kandeel, Ahmed, Ali, Mohamed Mandour, Mansy, Ahmad, Maurice, Hany, Nabil, Sherif, Shaaban, Mahmoud, Flores, Ana Camila, Poksi, Anne, Knuuti, Juhani, Kokkonen, Velipekka, Larikka, Martti, Uusitalo, Valtteri, Bailly, Matthieu, Burg, Samuel, Deux, Jean-François, Habouzit, Vincent, Hyafil, Fabien, Lairez, Olivier, Proffit, Franck, Regaieg, Hamza, Sarda-Mantel, Laure, Tacher, Vania, Schneider, Roman P., Ayetey, Harold, Angelidis, George, Archontaki, Aikaterini, Chatziioannou, Sofia, Datseris, Ioannis, Fragkaki, Christina, Georgoulias, Panagiotis, Koukouraki, Sophia, Koutelou, Maria, Kyrozi, Eleni, Repasos, Evangelos, Stavrou, Petros, Valsamaki, Pipitsa, Gonzalez, Carla, Gutierrez, Goleat, Maldonado, Alejandro, Buga, Klara, Garai, Ildiko, Maurovich-Horvat, Pál, Schmidt, Erzsébet, Szilveszter, Balint, Várady, Edit, Banthia, Nilesh, Bhagat, Jinendra Kumar, Bhargava, Rishi, Bhat, Vivek, Bhatia, Mona, Choudhury, Partha, Chowdekar, Vijay Sai, Irodi, Aparna, Jain, Shashank, Joseph, Elizabeth, Kumar, Sukriti, Girijanandan Mahapatra, Prof Dr, Mitra, Deepanjan, Mittal, Bhagwant Rai, Ozair, Ahmad, Patel, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Saxena, Sudhir, Sengupta, Shantanu, Singh, Santosh, Singh, Bhanupriya, Sood, Ashwani, Verma, Atul, Affandi, Erwin, Alam, Padma Savenadia, Edison, Edison, Gunawan, Gani, Hapkido, Habusari, Hidayat, Basuki, Huda, Aulia, Mukti, Anggoro Praja, Prawiro, Djoko, Soeriadi, Erwin Affandi, Syawaluddin, Hilman, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Houshmand, Golnaz, Maleki, Majid, Rostami, Maryam Tajik, Zakavi, Seyed Rasoul, Zaid, Eed Abu, Agranovich, Svetlana, Arnson, Yoav, Bar-Shalom, Rachel, Frenkel, Alex, Knafo, Galit, Lugassi, Rachel, Maor Moalem, Israel Shlomo, Mor, Maya, Muskal, Noam, Ranser, Sara, Shalev, Aryeh, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Bagatin, Elisa, Baldari, Sergio, Bauckneht, Matteo, Bertelli, Paolo, Bianco, Francesco, Bonfiglioli, Rachele, Boni, Roberto, Bruno, Andrea, Bruno, Isabella, Busnardo, Elena, Califaretti, Elena, Camoni, Luca, Carnevale, Aldo, Casoni, Roberta, Cavallo, Armando Ugo, Cavenaghi, Giorgio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Colletta, Mauro, Conti, Umberto, Cossu, Alberto, Cuocolo, Alberto, Cuzzocrea, Marco, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Del Giudice, Eleonora, Del Torto, Alberico, Della Tommasina, Veronica, Durmo, Rexhep, Erba, Paola Anna, Evangelista, Laura, Faletti, Riccardo, Faragasso, Evelina, Farsad, Mohsen, Ferro, Paola, Florimonte, Luigia, Frantellizzi, Viviana, Fringuelli, Fabio Massimo, Gatti, Marco, Gaudiano, Angela, Gimelli, Alessia, Giubbini, Raffaele, Giuffrida, Francesca, Ialuna, Salvatore, Laudicella, Riccardo, Leccisotti, Lucia, Leva, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Mancini, Maria Elisabetta, Marcassa, Claudio, Milan, Elisa, Nardi, Barbara, Pacella, Sara, Pepe, Giovanna, Pontone, Gianluca, Pulizzi, Sabina, Quartuccio, Natale, Rampin, Lucia, Ricci, Fabrizio, Rossini, Pierluigi, Rubini, Giuseppe, Russo, Vincenzo, Sacchetti, Gian Mauro, Sambuceti, Gianmario, Scarano, Massimo, Sciagrà, Roberto, Sperandio, Massimiliano, Stefanelli, Antonella, Ventroni, Guido, Zoboli, Stefania, Baugh, Dainia, Chambers, Duane, Madu, Ernest, Nunura, Felix, Asano, Hiroshi, Chimura, Chimura Misato, Fujimoto, Shinichiro, Fujisue, Koichiro, Fukunaga, Tomohisa, Fukushima, Yoshimitsu, Fukuyama, Kae, Hashimoto, Jun, Ichikawa, Yasutaka, Iguchi, Nobuo, Imai, Masamichi, Inaki, Anri, Ishimura, Hayato, Isobe, Satoshi, Kadokami, Toshiaki, Kato, Takao, Kudo, Takashi, Kumita, Shinichiro, Maruno, Hirotaka, Mataki, Hiroyuki, Miyagawa, Masao, Morimoto, Ryota, Moroi, Masao, Nagamachi, Shigeki, Nakajima, Kenichi, Nakata, Tomoaki, Nakazato, Ryo, Nanasato, Mamoru, Naya, Masanao, Norikane, Takashi, Ohta, Yasutoshi, Okayama, Satoshi, Okizaki, Atsutaka, Otomi, Yoichi, Otsuka, Hideki, Saito, Masaki, Sakata, Sakata Yasushi, Sarai, Masayoshi, Sato, Daisuke, Shiraishi, Shinya, Suwa, Yoshinobu, Takanami, Kentaro, Takehana, Kazuya, Taki, Junichi, Tamaki, Nagara, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Tsujita, Kenichi, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Batyrkhanov, Daultai, Dautov, Tairkhan, Makhdomi, Khalid, Ombati, Kevin, Alkandari, Faridah, Garashi, Masoud, Coie, Tchoyoson Lim, Rajvong, Sonexay, Kalinin, Artem, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Mataciunas, Mindaugas, Vajauskas, Donatas, Picard, Christian, Karim, Noor Khairiah A., Reichmuth, Luise, Samuel, Anthony, Allarakha, Mohammad Aaftaab, Naojee, Ambedhkar Shantaram, Alexanderson-Rosas, Erick, Barragan, Erika, González-Montecinos, Alejandro Becerril, Cabada, Manuel, Rodriguez, Daniel Calderon, Carvajal-Juarez, Isabel, Cortés, Violeta, Cortés, Filiberto, De La Peña, Erasmo, Gama-Moreno, Manlio, González, Luis, Ramírez, Nelsy Gonzalez, Jiménez-Santos, Moisés, Matos, Luis, Monroy, Edgar, Morelos, Martha, Ornelas, Mario, Ortga Ramirez, Jose Alberto, Preciado-Anaya, Andrés, Preciado-Gutiérrez, Óscar Ulises, Barragan, Adriana Puente, Rosales Uvera, Sandra Graciela, Sandoval, Sigelinda, Tomas, Miguel Santaularia, Sierra-Galan, Lilia M., Siu, Silvia, Vallejo, Enrique, Valles, Mario, Faraggi, Marc, Sereegotov, Erdenechimeg, Ilic, Srdja, Ben-Rais, Nozha, Alaoui, Nadia Ismaili, Taleb, Sara, Pa Myo, Khin Pa, Thu, Phyo Si, Ghimire, Ram Kumar, Rajbanshi, Bijoy, Barneveld, Peter, Glaudemans, Andor, Habets, Jesse, Koopmans, Klaas Pieter, Manders, Jeroen, Pool, Stefan, Scholte, Arthur, Scholtens, Asbjørn, Slart, Riemer, Thimister, Paul, Van Asperen, Erik-Jan, Veltman, Niels, Verschure, Derk, Wagenaar, Nils, Edmond, John, Ellis, Chris, Johnson, Kerryanne, Keenan, Ross, Kueh, Shaw Hua (Anthony), Occleshaw, Christopher, Sasse, Alexander, To, Andrew, Van Pelt, Niels, Young, Calum, Cuadra, Teresa, Roque Vanegas, Hector Bladimir, Soli, Idrissa Adamou, Issoufou, Djibrillou Moussa, Ayodele, Tolulope, Madu, Chibuzo, Onimode, Yetunde, Efros-Monsen, Elen, Forsdahl, Signe Helene, Hildre Dimmen, Jenni-Mari, Jørgensen, Arve, Krohn, Isabel, Løvhaugen, Pål, Bråten, Anders Tjellaug, Al Dhuhli, Humoud, Al Kindi, Faiza, Al-Bulushi, Naeema, Jawa, Zabah, Tag, Naima, Afzal, Muhammad Shehzad, Fatima, Shazia, Younis, Muhammad Numair, Riaz, Musab, Saadullah, Mohammad, Herrera, Yariela, Lenturut-Katal, Dora, Vázquez, Manuel Castillo, Ortellado, José, Akhter, Afroza, Cao, Dianbo, Cheung, Stephen, Dai, Xu, Gong, Lianggeng, Han, Dan, Hou, Yang, Li, Caiying, Li, Tao, Li, Dong, Li, Sijin, Liu, Jinkang, Liu, Hui, Lu, Bin, Ng, Ming Yen, Sun, Kai, Tang, Gongshun, Wang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wu, Jiang, Wu, Zhifang, Xia, Liming, Xiao, Jiangxi, Xu, Lei, Yang, Youyou, Yin, Wu, Yu, Jianqun, Yuan, Li, Zhang, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhu, Li, Alfaro, Ana, Abrihan, Paz, Barroso, Asela, Cruz, Eric, Gomez, Marie Rhiamar, Magboo, Vincent Peter, Medina, John Michael, Obaldo, Jerry, Pastrana, Davidson, Pawhay, Christian Michael, Quinon, Alvin, Tang, Jeanelle Margareth, Tecson, Bettina, Uson, Kristine Joy, Uy, Mila, Kostkiewicz, Magdalena, Kunikowska, Jolanta, Bettencourt, Nuno, Cantinho, Guilhermina, Ferreira, Antonio, Syed, Ghulam, Arnous, Samer, Atyani, Said, Byrne, Angela, Gleeson, Tadhg, Kerins, David, Meehan, Conor, Murphy, David, Murphy, Mark, Murray, John, O'Brien, Julie, Bang, Ji-In, Bom, Henry, Cho, Sang-Geon, Hong, Chae Moon, Jang, Su Jin, Jeong, Yong Hyu, Kang, Won Jun, Kim, Ji-Young, Lee, Jaetae, Namgung, Chang Kyeong, So, Young, Won, Kyoung Sook, Majstorov, Venjamin, Vavlukis, Marija, Salobir, Barbara Gužic, Štalc, Monika, Benedek, Theodora, Benedek, Imre, Mititelu, Raluca, Stan, Claudiu Adrian, Ansheles, Alexey, Dariy, Olga, Drozdova, Olga, Gagarina, Nina, Gulyaev, Vsevolod Milyevich, Itskovich, Irina, Karalkin, Anatoly, Kokov, Alexander, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Saifullina, Guzaliya, Sazonova, Svetlana, Sergienko, Vladimir, Shurupova, Irina, Trifonova, Tatjana, Ussov, Wladimir Yurievich, Vakhromeeva, Margarita, Valiullina, Nailya, Zavadovsky, Konstantin, Zhuravlev, Kirill, Alasnag, Mirvat, Okarvi, Subhani, Saranovic, Dragana Sobic, Keng, Felix, Jason See, Jia Hao, Sekar, Ramkumar, Yew, Min Sen, Vondrak, Andrej, Bejai, Shereen, Bennie, George, Bester, Ria, Engelbrecht, Gerrit, Evbuomwan, Osayande, Gongxeka, Harlem, Vuuren, Magritha Jv, Kaplan, Mitchell, Khushica, Purbhoo, Lakhi, Hoosen, Louw, Lizette, Malan, Nico, Milos, Katarina, Modiselle, Moshe, More, Stuart, Naidoo, Mathava, Scholtz, Leonie, Vangu, Mboyo, Aguadé-Bruix, Santiago, Blanco, Isabel, Cabrera, Antonio, Camarero, Alicia, Casáns-Tormo, Irene, Cuellar-Calabria, Hug, Flotats, Albert, Fuentes Cañamero, Maria Eugenia, García, María Elia, Jimenez-Heffernan, Amelia, Leta, Rubén, Diaz, Javier Lopez, Lumbreras, Luis, Marquez-Cabeza, Juan Javier, Martin, Francisco, Martinez de Alegria, Anxo, Medina, Francisco, Canal, Maria Pedrera, Peiro, Virginia, Pubul-Nuñez, Virginia, Rayo Madrid, Juan Ignacio, Rey, Cristina Rodríguez, Perez, Ricardo Ruano, Ruiz, Joaquín, Hernández, Gertrudis Sabatel, Sevilla, Ana, Zeidán, Nahla, Nanayakkara, Damayanthi, Udugama, Chandraguptha, Simonsson, Magnus, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Ceriani, Luca, De Boeck, Bart, Gräni, Christoph, Juillet de Saint Lager Lucas, Alix, Kamani, Christel H., Kawel-Boehm, Nadine, Manka, Robert, Prior, John O., Rominger, Axel, Vallée, Jean-Paul, Khiewvan, Benjapa, Premprabha, Teerapon, Thientunyakit, Tanyaluck, Sellem, Ali, Kir, Kemal Metin, Sayman, Haluk, Sebikali, Mugisha Julius, Muyinda, Zerida, Kmetyuk, Yaroslav, Korol, Pavlo, Mykhalchenko, Olena, Pliatsek, Volodymyr, Satyr, Maryna, Albalooshi, Batool, Ahmed Hassan, Mohamed Ismail, Anderson, Jill, Bedi, Punit, Biggans, Thomas, Bularga, Anda, Bull, Russell, Burgul, Rajesh, Carpenter, John-Paul, Coles, Duncan, Cusack, David, Deshpande, Aparna, Dougan, John, Fairbairn, Timothy, Farrugia, Alexia, Gopalan, Deepa, Gummow, Alistair, Ramkumar, Prasad Guntur, Hamilton, Mark, Harbinson, Mark, Hartley, Thomas, Hudson, Benjamin, Joshi, Nikhil, Kay, Michael, Kelion, Andrew, Khokhar, Azhar, Kitt, Jamie, Lee, Ken, Low, Chen, Mak, Sze Mun, Marousa, Ntouskou, Martin, Jon, Mcalindon, Elisa, Menezes, Leon, Morgan-Hughes, Gareth, Moss, Alastair, Murray, Anthony, Nicol, Edward, Patel, Dilip, Peebles, Charles, Pugliese, Francesca, Luis Rodrigues, Jonathan Carl, Rofe, Christopher, Sabharwal, Nikant, Schofield, Rebecca, Semple, Thomas, Sharma, Naveen, Strouhal, Peter, Subedi, Deepak, Topping, William, Tweed, Katharine, Weir-Mccall, Jonathan, Abbara, Suhny, Abbasi, Taimur, Abbott, Brian, Abohashem, Shady, Abramson, Sandra, Al-Abboud, Tarek, Al-Mallah, Mouaz, Almousalli, Omar, Ananthasubramaniam, Karthikeyan, Kumar, Mohan Ashok, Askew, Jeffrey, Attanasio, Lea, Balmer-Swain, Mallory, Bayer, Richard R., Bernheim, Adam, Bhatti, Sabha, Bieging, Erik, Blankstein, Ron, Bloom, Stephen, Blue, Sean, Bluemke, David, Borges, Andressa, Branch, Kelley, Bravo, Paco, Brothers, Jessica, Budoff, Matthew, Bullock-Palmer, Renée, Burandt, Angela, Burke, Floyd W., Bush, Kelvin, Candela, Candace, Capasso, Elizabeth, Cavalcante, Joao, Chang, Donald, Chatterjee, Saurav, Chatzizisis, Yiannis, Cheezum, Michael, Chen, Tiffany, Chen, Jennifer, Chen, Marcus, Clarcq, James, Cordero, Ayreen, Crim, Matthew, Danciu, Sorin, Decter, Bruce, Dhruva, Nimish, Doherty, Neil, Doukky, Rami, Dunbar, Anjori, Duvall, William, Edwards, Rachael, Esquitin, Kerry, Farah, Husam, Fentanes, Emilio, Ferencik, Maros, Fisher, Daniel, Fitzpatrick, Daniel, Foster, Cameron, Fuisz, Tony, Gannon, Michael, Gastner, Lori, Gerson, Myron, Ghoshhajra, Brian, Goldberg, Alan, Goldner, Brian, Gonzalez, Jorge, Gore, Rosco, Gracia-López, Sandra, Hage, Fadi, Haider, Agha, Haider, Sofia, 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Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, James, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vikas, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Winchester, David, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, Nguyen, Xuan Canh, Lahey, Ryan, Henry Bom, Hee-Seung, Fazel, Reza, Karthikeyan, Ganesan, Keng, Felix Y.J., Rubinshtein, Ronen, Cerci, Rodrigo Julio, Vitola, João V., Choi, Andrew D., and Cohen, Yosef A.

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2021
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6. Impact of COVID-19 on Cardiovascular Testing in the United States Versus the Rest of the World

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Einstein, Andrew J., Paez, Diana, Dondi, Maurizio, Better, Nathan, Cerci, Rodrigo, Dorbala, Sharmila, Pascual, Thomas N.B., Raggi, Paolo, Shaw, Leslee J., Villines, Todd C., Vitola, Joao V., Williams, Michelle C., Pynda, Yaroslav, Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Hirschfeld, Cole B., Cohen, Yosef, Goebel, Benjamin, Malkovskiy, Eli, Randazzo, Michael, Choi, Andrew, Lopez-Mattei, Juan, Parwani, Purvi, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qais, Agolti, Mariela, Aguero, Roberto Nicolas, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Bas, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlos, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Lucas, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, Nieves A López De Munaín, Maria, Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matias, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marcos, Noguera, Eduardo, Novoa, Carlos, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matías, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Lucas, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charles, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, William, Verjans, Johan, Voutnis, Demetrius, Wayne, Victor, Wilson, Peter, Wong, David, Wong, Kirby, Younger, John, Feuchtner, Gudrun, Mirzaei, Siroos, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Gheysens, Olivier, Homans, Filip, Moreno-Reyes, Rodrigo, Pasquet, Agnès, Roelants, Veronique, Van De Heyning, Caroline M., Ríos, Raúl Araujo, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Albernaz Siqueira, Maria Helena, Almeida, Augusto, Alves Togni, Paulo Henrique, Andrade, Jose Henrique, Andrade, Luciana, Anselmi, Carlos, Araújo, Roberta, Azevedo, Guilherme, Bezerra, Sabbrina, Biancardi, Rodrigo, Grossman, Gabriel Blacher, Brandão, Simone, Pianta, Diego Bromfman, Carreira, Lara, Castro, Bruno, Chang, Tien, Cunali, Fernando, Jr., Cury, Roberto, Dantas, Roberto, de Amorim Fernandes, Fernando, De Lorenzo, Andrea, De Macedo Filho, Robson, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, De Souza, Thiago Ferreira, Alves, Wilson Furlan, Ghini, Bruno, Goncalves, Luiz, Gottlieb, Ilan, Hadlich, Marcelo, Kameoka, Vinícius, Lima, Ronaldo, Lima, Adna, Lopes, Rafael Willain, Machado e Silva, Ricardo, Magalhães, Tiago, Silva, Fábio Martins, Mastrocola, Luiz Eduardo, Medeiros, Fábio, Meneghetti, José Claudio, Naue, Vania, Naves, Danilo, Nolasco, Roberto, Nomura, Cesar, Oliveira, Joao Bruno, Paixao, Eduardo, De Carvalho, Filipe Penna, Pinto, Ibraim, Possetti, Priscila, Quinta, Mayra, Nogueira Ramos, Rodrigo Rizzo, Rocha, Ricardo, Rodrigues, Alfredo, Rodrigues, Carlos, Romantini, Leila, Sanches, Adelina, Santana, Sara, Sara da Silva, Leonardo, Schvartzman, Paulo, Matushita, Cristina Sebastião, Senra, Tiago, Shiozaki, Afonso, Menezes de Siqueira, Maria Eduarda, Siqueira, Cristiano, Smanio, Paola, Soares, Carlos Eduardo, Junior, José Soares, Bittencourt, Marcio Sommer, Spiro, Bernardo, 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Mauricio, Rojas, Juan Carlos, Ruiz, Diego, Escobar, Manuel Valencia, Vasquez, Andres, Vergel, Damiana, Zuluaga, Alejandro, Gamboa, Isabel Berrocal, Castro, Gabriel, González, Ulises, Baric, Ana, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Jukic, Mladen, Medakovic, Petar, Persic, Viktor, Prpic, Marina, Punda, Ante, Batista, Juan Felipe, Gómez Lauchy, Juan Manuel, Gutierrez, Yamile Marcos, Menéndez, Rayner, Peix, Amalia, Rochela, Luis, Panagidis, Christoforos, Petrou, Ioannis, Engelmann, Vaclav, Kaminek, Milan, Kincl, Vladimír, Lang, Otto, Simanek, Milan, Abdulla, Jawdat, Bøttcher, Morten, Christensen, Mette, Gormsen, Lars Christian, Hasbak, Philip, Hess, Søren, Holdgaard, Paw, Johansen, Allan, Kyhl, Kasper, Norgaard, Bjarne Linde, Øvrehus, Kristian Altern, Rønnow Sand, Niels Peter, Steffensen, Rolf, Thomassen, Anders, Zerahn, Bo, Perez, Alfredo, Escorza Velez, Giovanni Alejandro, Velez, Mayra Sanchez, Abdel Aziz, Islam Shawky, Abougabal, Mahasen, Ahmed, Taghreed, Allam, Adel, Asfour, Ahmed, Hassan, Mona, Hassan, Alia, Ibrahim, Ahmed, Kaffas, Sameh, Kandeel, Ahmed, Ali, Mohamed Mandour, Mansy, Ahmad, Maurice, Hany, Nabil, Sherif, Shaaban, Mahmoud, Flores, Ana Camila, Poksi, Anne, Knuuti, Juhani, Kokkonen, Velipekka, Larikka, Martti, Uusitalo, Valtteri, Bailly, Matthieu, Burg, Samuel, Deux, Jean-François, Habouzit, Vincent, Hyafil, Fabien, Lairez, Olivier, Proffit, Franck, Regaieg, Hamza, Sarda-Mantel, Laure, Tacher, Vania, Schneider, Roman P., Ayetey, Harold, Angelidis, George, Archontaki, Aikaterini, Chatziioannou, Sofia, Datseris, Ioannis, Fragkaki, Christina, Georgoulias, Panagiotis, Koukouraki, Sophia, Koutelou, Maria, Kyrozi, Eleni, Repasos, Evangelos, Stavrou, Petros, Valsamaki, Pipitsa, Gonzalez, Carla, Gutierrez, Goleat, Maldonado, Alejandro, Buga, Klara, Garai, Ildiko, Maurovich-Horvat, Pál, Schmidt, Erzsébet, Szilveszter, Balint, Várady, Edit, Banthia, Nilesh, Bhagat, Jinendra Kumar, Bhargava, Rishi, Bhat, Vivek, Bhatia, Mona, Choudhury, Partha, Chowdekar, Vijay Sai, Irodi, Aparna, Jain, Shashank, Joseph, Elizabeth, Kumar, Sukriti, Girijanandan Mahapatra, Prof Dr, Mitra, Deepanjan, Mittal, Bhagwant Rai, Ozair, Ahmad, Patel, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Saxena, Sudhir, Sengupta, Shantanu, Singh, Santosh, Singh, Bhanupriya, Sood, Ashwani, Verma, Atul, Affandi, Erwin, Alam, Edison, Padma Savenadia, Gunawan, Gani, Hapkido, Habusari, Hidayat, Basuki, Huda, Aulia, Mukti, Anggoro Praja, Prawiro, Djoko, Soeriadi, Erwin Affandi, Syawaluddin, Hilman, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Houshmand, Golnaz, Maleki, Majid, Rostami, Maryam Tajik, Zakavi, Seyed Rasoul, Zaid, Eed Abu, Agranovich, Svetlana, Arnson, Yoav, Bar-Shalom, Rachel, Frenkel, Alex, Knafo, Galit, Lugassi, Rachel, Maor Moalem, Israel Shlomo, Mor, Maya, Muskal, Noam, Ranser, Sara, Shalev, Aryeh, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Bagatin, Elisa, Baldari, Sergio, Bauckneht, Matteo, Bertelli, Paolo, Bianco, Francesco, Bonfiglioli, Rachele, Boni, Roberto, Bruno, Andrea, Bruno, Isabella, Busnardo, Elena, Califaretti, Elena, Camoni, Luca, Carnevale, Aldo, Casoni, Roberta, Cavallo, Armando Ugo, Cavenaghi, Giorgio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Colletta, Mauro, Conti, Umberto, Cossu, Alberto, Cuocolo, Alberto, Cuzzocrea, Marco, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Del Giudice, Eleonora, Del Torto, Alberico, Della Tommasina, Veronica, Durmo, Rexhep, Erba, Paola Anna, Evangelista, Laura, Faletti, Riccardo, Faragasso, Evelina, Farsad, Mohsen, Ferro, Paola, Florimonte, Luigia, Frantellizzi, Viviana, Fringuelli, Fabio Massimo, Gatti, Marco, Gaudiano, Angela, Gimelli, Alessia, Giubbini, Raffaele, Giuffrida, Francesca, Ialuna, Salvatore, Laudicella, Riccardo, Leccisotti, Lucia, Leva, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Mancini, Maria Elisabetta, Marcassa, Claudio, Milan, Elisa, Nardi, Barbara, Pacella, Sara, Pepe, Giovanna, 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Sakata, Sakata Yasushi, Sarai, Masayoshi, Sato, Daisuke, Shiraishi, Shinya, Suwa, Yoshinobu, Takanami, Kentaro, Takehana, Kazuya, Taki, Junichi, Tamaki, Nagara, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Tsujita, Kenichi, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Batyrkhanov, Daultai, Dautov, Tairkhan, Makhdomi, Khalid, Ombati, Kevin, Alkandari, Faridah, Garashi, Masoud, Coie, Tchoyoson Lim, Rajvong, Sonexay, Kalinin, Artem, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Mataciunas, Mindaugas, Vajauskas, Donatas, Picard, Christian, Karim, Noor Khairiah A., Reichmuth, Luise, Samuel, Anthony, Allarakha, Mohammad Aaftaab, Naojee, Ambedhkar Shantaram, Alexanderson-Rosas, Erick, Barragan, Erika, González-Montecinos, Alejandro Becerril, Cabada, Manuel, Rodriguez, Daniel Calderon, Carvajal-Juarez, Isabel, Cortés, Violeta, Cortés, Filiberto, De La Peña, Erasmo, Gama-Moreno, Manlio, 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Alexander, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Saifullina, Guzaliya, Sazonova, Svetlana, Sergienko, Vladimir, Shurupova, Irina, Trifonova, Tatjana, Ussov, Wladimir Yurievich, Vakhromeeva, Margarita, Valiullina, Nailya, Zavadovsky, Konstantin, Zhuravlev, Kirill, Alasnag, Mirvat, Okarvi, Subhani, Saranovic, Dragana Sobic, Keng, Felix, Jason See, Jia Hao, Sekar, Ramkumar, Yew, Min Sen, Vondrak, Andrej, Bejai, Shereen, Bennie, George, Bester, Ria, Engelbrecht, Gerrit, Evbuomwan, Osayande, Gongxeka, Harlem, Vuuren, Magritha Jv, Kaplan, Mitchell, Khushica, Purbhoo, Lakhi, Hoosen, Louw, Lizette, Malan, Nico, Milos, Katarina, Modiselle, Moshe, More, Stuart, Naidoo, Mathava, Scholtz, Leonie, Vangu, Mboyo, Aguadé-Bruix, Santiago, Blanco, Isabel, Cabrera, Antonio, Camarero, Alicia, Casáns-Tormo, Irene, Cuellar-Calabria, Hug, Flotats, Albert, Fuentes Cañamero, Maria Eugenia, García, María Elia, Jimenez-Heffernan, Amelia, Leta, Rubén, Diaz, Javier Lopez, Lumbreras, Luis, Marquez-Cabeza, Juan Javier, Martin, Francisco, Martinez de Alegria, Anxo, Medina, Francisco, Canal, Maria Pedrera, Peiro, Virginia, Pubul-Nuñez, Virginia, Rayo Madrid, Juan Ignacio, Rey, Cristina Rodríguez, Perez, Ricardo Ruano, Ruiz, Joaquín, Hernández, Gertrudis Sabatel, Sevilla, Ana, Zeidán, Nahla, Nanayakkara, Damayanthi, Udugama, Chandraguptha, Simonsson, Magnus, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Ceriani, Luca, De Boeck, Bart, Gräni, Christoph, Juillet de Saint Lager Lucas, Alix, Kamani, Christel H., Kawel-Boehm, Nadine, Manka, Robert, Prior, John O., Rominger, Axel, Vallée, Jean-Paul, Khiewvan, Benjapa, Premprabha, Teerapon, Thientunyakit, Tanyaluck, Sellem, Ali, Kir, Kemal Metin, Sayman, Haluk, Sebikali, Mugisha Julius, Muyinda, Zerida, Kmetyuk, Yaroslav, Korol, Pavlo, Mykhalchenko, Olena, Pliatsek, Volodymyr, Satyr, Maryna, Albalooshi, Batool, Ahmed Hassan, Mohamed Ismail, Anderson, Jill, Bedi, Punit, Biggans, Thomas, Bularga, Anda, Bull, Russell, Burgul, Rajesh, Carpenter, John-Paul, Coles, Duncan, Cusack, David, Deshpande, Aparna, Dougan, John, Fairbairn, Timothy, Farrugia, Alexia, Gopalan, Deepa, Gummow, Alistair, Ramkumar, Prasad Guntur, Hamilton, Mark, Harbinson, Mark, Hartley, Thomas, Hudson, Benjamin, Joshi, Nikhil, Kay, Michael, Kelion, Andrew, Khokhar, Azhar, Kitt, Jamie, Lee, Ken, Low, Chen, Mak, Sze Mun, Marousa, Ntouskou, Martin, Jon, Mcalindon, Elisa, Menezes, Leon, Morgan-Hughes, Gareth, Moss, Alastair, Murray, Anthony, Nicol, Edward, Patel, Dilip, Peebles, Charles, Pugliese, Francesca, Luis Rodrigues, Jonathan Carl, Rofe, Christopher, Sabharwal, Nikant, Schofield, Rebecca, Semple, Thomas, Sharma, Naveen, Strouhal, Peter, Subedi, Deepak, Topping, William, Tweed, Katharine, Weir-Mccall, Jonathan, Abbara, Suhny, Abbasi, Taimur, Abbott, Brian, Abohashem, Shady, Abramson, Sandra, Al-Abboud, Tarek, Al-Mallah, Mouaz, Almousalli, Omar, Ananthasubramaniam, Karthikeyan, Kumar, Mohan Ashok, Askew, Jeffrey, Attanasio, Lea, Balmer-Swain, Mallory, Bayer, Richard R., Bernheim, Adam, Bhatti, Sabha, Bieging, Erik, Blankstein, Ron, Bloom, Stephen, Blue, Sean, Bluemke, David, Borges, Andressa, Branch, Kelley, Bravo, Paco, Brothers, Jessica, Budoff, Matthew, Bullock-Palmer, Renée, Burandt, Angela, Burke, Floyd W., Bush, Kelvin, Candela, Candace, Capasso, Elizabeth, Cavalcante, Joao, Chang, Donald, Chatterjee, Saurav, Chatzizisis, Yiannis, Cheezum, Michael, Chen, Tiffany, Chen, Jennifer, Chen, Marcus, Clarcq, James, Cordero, Ayreen, Crim, Matthew, Danciu, Sorin, Decter, Bruce, Dhruva, Nimish, Doherty, Neil, Doukky, Rami, Dunbar, Anjori, Duvall, William, Edwards, Rachael, Esquitin, Kerry, Farah, Husam, Fentanes, Emilio, Ferencik, Maros, Fisher, Daniel, Fitzpatrick, Daniel, Foster, Cameron, Fuisz, Tony, Gannon, Michael, Gastner, Lori, Gerson, Myron, Ghoshhajra, Brian, Goldberg, Alan, Goldner, Brian, Gonzalez, Jorge, Gore, Rosco, Gracia-López, Sandra, Hage, Fadi, Haider, Agha, Haider, Sofia, Hamirani, Yasmin, Hassen, Karen, Hatfield, Mallory, Hawkins, Carolyn, Hawthorne, Katie, Heath, Nicholas, Hendel, Robert, Hernandez, Phillip, Hill, Gregory, Horgan, Stephen, Huffman, Jeff, Hurwitz, Lynne, Iskandrian, Ami, Janardhanan, Rajesh, Jellis, Christine, Jerome, Scott, Kalra, Dinesh, Kaviratne, Summanther, Kay, Fernando, Kelly, Faith, Khalique, Omar, Kinkhabwala, Mona, Iii, George Kinzfogl, Kircher, Jacqueline, Kirkbride, Rachael, Kontos, Michael, Kottam, Anupama, Krepp, Joseph, Layer, Jay, Lee, Steven H., Leppo, Jeffrey, Lesser, John, Leung, Steve, Lewin, Howard, Litmanovich, Diana, Liu, Yiyan, Magurany, Kathleen, Markowitz, Jeremy, Marn, Amanda, Matis, Stephen E., Mckenna, Michael, Mcrae, Tony, Mendoza, Fernando, Merhige, Michael, Min, David, Moffitt, Chanan, Moncher, Karen, Moore, Warren, Morayati, Shamil, Morris, Michael, Mossa-Basha, Mahmud, Mrsic, Zorana, Murthy, Venkatesh, Nagpal, Prashant, Napier, Kyle, Narula, Jagat, Nelson, Katarina, Nijjar, Prabhjot, Osman, Medhat, Passen, Edward, Patel, Amit, Patil, Pravin, Paul, Ryan, Phillips, Lawrence, Polsani, Venkateshwar, Poludasu, Rajaram, Pomerantz, Brian, Porter, Thomas, Prentice, Ryan, Pursnani, Amit, Rabbat, Mark, Ramamurti, Suresh, Rich, Florence, Luna, Hiram Rivera, Robinson, Austin, Robles, Kim, Rodríguez, Cesar, Rorie, Mark, Rumberger, John, Russell, Raymond, Sabra, Philip, Sadler, Diego, Schemmer, Mary, Schoepf, U. Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, James, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vikas, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Winchester, David, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, Nguyen, Xuan Canh, Lahey, Ryan, Choi, Andrew D., Shah, Nishant R., Bluemke, David A., Berman, Daniel S., Randazzo, Michael J., Cerci, Rodrigo J., Sinitsyn, Valentin, Nørgaard, Bjarne Linde, and Cohen, Yosef A.

Published
2021
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13. Control over the fibrillization yield by varying the oligomeric nucleation propensities of self-assembling peptides

Author

Lau, Chun Yin Jerry, Fontana, Federico, Mandemaker, Laurens D. B., Wezendonk, Dennie, Vermeer, Benjamin, Bonvin, Alexandre M. J. J., de Vries, Renko, Zhang, Heyang, Remaut, Katrien, van den Dikkenberg, Joep, Medeiros-Silva, João, Hassan, Alia, Perrone, Barbara, Kuemmerle, Rainer, Gelain, Fabrizio, Hennink, Wim E., Weingarth, Markus, and Mastrobattista, Enrico

Published
2020
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14. Existence and Uniqueness Common Fixed Point in Fuzzy b-Matric Space.

Author

Ali, Ban Nazar and Hassan, Alia Shani

Subjects
SEQUENCE spaces, MATHEMATICAL mappings, METRIC spaces
Abstract

Multiple fixed points common to fuzzy spaces b-metric are presented in this work. We provide an appropriate requirement for a sequence on the fuzzy space b-metric to be Cauchy, which is a significant outcome. As a result, we streamline the numerous theorem of point fixed proofs on a fuzzy space for b-metrics with established contraction conditions. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Review of Automatic Speaker Profiling: Features, Methods, and Challenges.

Author

Jaid, Umniah Hameed and Abdul Hassan, Alia Karim

Subjects
*SHOPPING mobile apps, *FEATURE extraction, *EXTRACTION techniques
Abstract

Automatic Speaker Profiling (ASP), is concerned with estimating the physical traits of a person from their voice. These traits include gender, age, ethnicity, and physical parameters. Reliable ASP has a wide range of applications such as mobile shopping, customer service, robotics, forensics, security, and surveillance systems. Research in ASP has gained interest in the last decade, however, it was focused on different tasks individually, such as age, height, or gender. In this work, a review of existing studies on different tasks of speaker profiling is performed. These tasks include age estimation and classification, gender detection, height, and weight estimation This study aims to provide insight into the work of ASP, available datasets, feature extraction techniques, and learning models. Further, the performance of current speaker profiling systems is investigated. Finally, the challenges of speaker profiling are presented at the end of this review. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques.

Author

Radha, Huda M., Hassan, Alia K. Abdul, and Al-Timemy, Ali H.

Subjects
ELECTROENCEPHALOGRAPHY, ELECTROMYOGRAPHY, MACHINE learning, PATTERN recognition systems, FEATURE extraction
Abstract

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically electroencephalography (EEG) and electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducted in this study utilized the binary grey wolf optimization algorithm to select optimal features for the proposed classification model. The results demonstrate promising outcomes, with an average classification accuracy of 93.6% for three amputees and five individuals with intact limbs. The accuracy achieved in classifying the seven types of hand and wrist movements further validates the effectiveness of the proposed approach. By offering a non-invasive and reliable means of recognizing upper limb movements, this research represents a significant step forward in biotechnical engineering for upper limb amputees. The findings hold considerable potential for enhancing the control and usability of prosthetic devices, ultimately contributing to the overall quality of life for individuals with upper limb amputations. [ABSTRACT FROM AUTHOR]

Published
2023
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18. Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory.

Author

Radha, Huda M., Abdul Hassan, Alia K., and Al-Timemy, Ali H.

Subjects
SHOULDER girdle, POWER spectra, REHABILITATION technology, FISHER discriminant analysis, ORTHOPEDIC apparatus, PROSTHETICS
Abstract

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) classifier and a Deep Learning (DL) approach employing the Long Short-Term Memory (LSTM) classifier to evaluate the classification accuracy of the different motions. Experimental results demonstrate that the LSTM classifier outperforms the LDA-based approach in gesture recognition, thereby offering a more effective solution for prosthesis control. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Overcoming challenges in 67Zn NMR: a new strategy of signal enhancement for MOF characterization.

Author

Zhang, Wanli, Hassan, Alia, Struppe, Jochem, Monette, Martine, Hung, Ivan, Gan, Zhehong, Martins, Vinicius, Terskikh, Victor, and Huang, Yining

Subjects
*MAGNETIC fields, *SIGNALS & signaling, *CRYOGENICS
Abstract

67Zn solid-state NMR suffers from low sensitivity, limiting its ability to probe the Zn2+ surroundings in MOFs. We report a breakthrough in overcoming challenges in 67Zn NMR. Combining new cryogenic MAS probe technology and performing NMR experiments at a high magnetic field results in remarkable signal enhancement, yielding enhanced information for MOF characterization. [ABSTRACT FROM AUTHOR]

Published
2023
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20. Multimodal Age and Gender Estimation for Adaptive Human-Robot Interaction: A Systematic Literature Review.

Author

Younis, Hussain A., Ruhaiyem, Nur Intan Raihana, Badr, Ameer A., Abdul-Hassan, Alia K., Alfadli, Ibrahim M., Binjumah, Weam M., Altuwaijri, Eman A., and Nasser, Maged

Subjects
HUMAN-robot interaction, GENDER, SPEECH perception, AUTOMATIC speech recognition, HEALTH literacy, COMPUTER vision
Abstract

Identifying the gender of a person and his age by way of speaking is considered a crucial task in computer vision. It is a very important and active research topic with many areas of application, such as identifying a person, trustworthiness, demographic analysis, safety and health knowledge, visual monitoring, and aging progress. Data matching is to identify the gender of the person and his age. Thus, the study touches on a review of many research papers from 2016 to 2022. At the heart of the topic, many systematic reviews of multimodal pedagogies in Age and Gender Estimation for Adaptive were undertaken. However, no current study of the theme concerns connected to multimodal pedagogies in Age and Gender Estimation for Adaptive Learning has been published. The multimodal pedagogies in four different databases within the keywords indicate the heart of the topic. A qualitative thematic analysis based on 48 articles found during the search revealed four common themes, such as multimodal engagement and speech with the Human-Robot Interaction life world. The study touches on the presentation of many major concepts, namely Age Estimation, Gender Estimation, Speaker Recognition, Speech recognition, Speaker Localization, and Speaker Gender Identification. According to specific criteria, they were presented to all studies. The essay compares these themes to the thematic findings of other review studies on the same topic such as multimodal age, gender estimation, and dataset used. The main objective of this paper is to provide a comprehensive analysis based on the surveyed region. The study provides a platform for professors, researchers, and students alike, and proposes directions for future research. [ABSTRACT FROM AUTHOR]

Published
2023
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21. Efficient analysis of pharmaceutical drug substances and products using a solid-state NMR CryoProbe.

Author

Du, Yong, Struppe, Jochem, Perrone, Barbara, Hassan, Alia, Codina, Anna, and Su, Yongchao

Subjects
DRUGS, DRUG analysis, ITRACONAZOLE, NUCLEAR magnetic resonance, SUBSTANCE abuse, DRUG interactions
Abstract

Solid-state nuclear magnetic resonance (ssNMR) is a high-resolution and versatile spectroscopic tool for characterizing pharmaceutical solids. However, the inherent low sensitivity of NMR remains a significant challenge in the analysis of natural abundance drug substances and products. Here, we report, for the first time, the application of a CPMAS CryoProbe™ to improve the sensitivity of 13C and 15N detection by approximately 5 to 6 times for solid-state analysis of a commercial pharmaceutical drug posaconazole (POSA). The sensitivity enhancement enables two-dimensional (2D) 13C–13C and 1H–15N correlation experiments, which are otherwise time-prohibitive using regular MAS probes, for resonance assignment and structural elucidation. These polarization transfer and correlation experiments reveal drug–drug and drug–polymer interactions in amorphous POSA and its amorphous solid dispersion formulation. Our results demonstrated that the CPMAS CryoProbe™ can be widely applied for routine pharmaceutical analysis and advanced structural investigations with significantly enhanced efficiency and throughput. [ABSTRACT FROM AUTHOR]

Published
2023
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22. Driving sleepiness detection using electrooculogram analysis and grey wolf optimizer.

Author

Jasim, Sarah Saadoon and Hassan, Alia Karim Abdul

Subjects
DROWSINESS, ARTIFICIAL neural networks, SUPPORT vector machines, K-nearest neighbor classification, FATIGUE (Physiology), MODERN society
Abstract

In modern society, providing safe and collision-free travel is essential. Therefore, detecting the drowsiness state of the driver before its ability to drive is compromised. For this purpose, an automated hybrid sleepiness classification system that combines the artificial neural network and gray wolf optimizer is proposed to distinguish human Sleepiness and fatigue. The proposed system is tested on data collected from 15 drivers (male and female) in alert and sleep-deprived conditions where physiological signals are used as sleep markers. To evaluate the performance of the proposed algorithm, k-nearest neighbors (k-NN), support vector machines (SVM), and artificial neural networks (ANN) classifiers have been used. The results show that the proposed hybrid method provides 99.6% accuracy, while the SVM classifier provides 93.0% accuracy when the kernel is (RBF) and outlier (0.1). Furthermore, the k-NN classifier provides 96.7% accuracy, whereas the standalone ANN algorithm provides 97.7% accuracy. [ABSTRACT FROM AUTHOR]

Published
2022
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23. A survey on bio-signal analysis for human-robot interaction.

Author

Radha, Huda Mustafa and Hassan, Alia Karim Abdul

Subjects
HUMAN-robot interaction, REHABILITATION technology, FEATURE extraction, PEOPLE with disabilities
Abstract

The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems. [ABSTRACT FROM AUTHOR]

Published
2022
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25. Gender detection in children's speech utterances for human-robot interaction.

Author

Badr, Ameer Abdul-Baqi and Abdul-Hassan, Alia Karim

Subjects
HUMAN-robot interaction, FEATURE extraction, SPEECH, LOGISTIC regression analysis
Abstract

The human voice speech essentially includes paralinguistic information used in many real-time applications. Detecting the children's gender is considered a challenging task compared to the adult's gender. In this study, a system for human-robot interaction (HRI) is proposed to detect the gender in children's speech utterances without depending on the text. The robot's perception includes three phases: Feature's extraction phase where four formants are measured at each glottal pulse and then a median is calculated across these measurements. After that, three types of features are measured which are formant average (AF), formant dispersion (DF), and formant position (PF). Feature's standardization phase where the measured feature dimensions are standardized using the z-score method. The semantic understanding phase is where the children's gender is detected accurately using the logistic regression classifier. At the same time, the action of the robot is specified via a speech response using the text to speech (TTS) technique. Experiments are conducted on the Carnegie Mellon University (CMU) Kids dataset to measure the suggested system's performance. In the suggested system, the overall accuracy is 98%. The results show a relatively clear improvement in terms of accuracy of up to 13% compared to related works that utilized the CMU Kids dataset. [ABSTRACT FROM AUTHOR]

Published
2022
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26. Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Voice Recognition.

Author

Jasim, Sarah S., Hassan, Alia K. Abdul, and Turner, Scott

Subjects
DROWSINESS, ARTIFICIAL neural networks, FEATURE extraction, AUTOMATIC speech recognition, ACCURACY
Abstract

Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively. [ABSTRACT FROM AUTHOR]

Published
2022
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27. Classification of Different Shoulder Girdle Motions for Prosthesis Control Using a Time-Domain Feature Extraction Technique.

Author

Radha, Huda M., Hassan, Alia K. Abdul, and Al-Timemy, Ali H.

Subjects
SHOULDER girdle, FEATURE extraction, QUALITY of life, ELECTROMYOGRAPHY, WAVELENGTHS
Abstract

The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients' quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, which are root mean square, four-order autoregressive, wavelength, slope sign change, zero crossing (ZC), mean absolute value, and cardinality. In this article, the time-domain features were first extracted from the EMG and acceleration signals. Then, the spectral regression (SR) and principal component analysis dimensionality reduction methods are employed to identify the most salient features, which are then passed to the linear discriminant analysis (LDA) classifier. EMG and axial acceleration signal datasets from six intact-limbed and four amputee participants exhibited an average classification error of 15.68 % based on SR dimensionality reduction using the LDA classifier. [ABSTRACT FROM AUTHOR]

Published
2022
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28. Some Common Fixed Point Theorems of Rational Contractions Condition in Generalized Banach Space.

Author

Khuen, Wesam N. and Hassan, Alia S.

Subjects
BANACH spaces, GENERALIZED spaces, CAUCHY sequences, RATIONAL points (Geometry)
Abstract

Copyright of Al-Mustansiriyah Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2022
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29. Modern drowsiness detection techniques a review.

Author

Jasim, Sarah Saadoon and Hassan, Alia Karim Abdul

Subjects
DROWSINESS, SUPERVISED learning, IMAGE processing, HYBRID electric cars, TRAFFIC accidents
Abstract

According to recent statistics, drowsiness, rather than alcohol, is now responsible for one-quarter of all automobile accidents. As a result, many monitoring systems have been created to reduce and prevent such accidents. However, despite the huge amount of state-of-the-art drowsiness detection systems, it is not clear which one is the most appropriate. The following points will be discussed in this paper: Initial consideration should be given to the many sorts of existing supervised detecting techniques that are now in use and grouped into four types of categories (behavioral, physiological, automobile and hybrid), Second, the supervised machine learning classifiers that are used for drowsiness detection will be described, followed by a discussion of the advantages and disadvantages of each technique that has been evaluated, and lastly the recommendation of a new strategy for detecting drowsiness. [ABSTRACT FROM AUTHOR]

Published
2022
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30. Fixed point theorems with various enriched contraction conditions in generalized Banach spaces.

Author

khuen, Wesam Nafia and Hassan, Alia Shani

Subjects
BANACH spaces, GENERALIZED spaces, FIXED point theory
Abstract

In this paper we introduce some fixed point theorems type contractions on generalized Banach space and we introduce a class of enriched Chatterjea mapping, enriched Kannan contraction mappings, This section is repeated enriched Chatterjea contraction mapping and enriched Kannan and enriched Chatterjea contraction mapping. And we show that these mappings must have unique fixed points in generalized Banach space. [ABSTRACT FROM AUTHOR]

Published
2022
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32. Dissolution dynamic nuclear polarization of deuterated molecules enhanced by cross-polarization.

Author

Kurzbach, Dennis, Weber, Emmanuelle M. M., Jhajharia, Aditya, Cousin, Samuel F., Sadet, Aude, Marhabaie, Sina, Canet, Estel, Birlirakis, Nicolas, Milani, Jonas, Jannin, Sami, Eshchenko, Dmitry, Hassan, Alia, Melzi, Roberto, Luetolf, Stephan, Sacher, Marco, Rossire, Marc, Kempf, James, Lohman, Joost A. B., Weller, Matthias, and Bodenhausen, Geoffrey

Subjects
POLARIZATION (Nuclear physics), DISSOLUTION (Chemistry), DEUTERIUM, MAGNETIZATION, NUCLEAR magnetic resonance, MAGNETIC fields
Abstract

We present novel means to hyperpolarize deuterium nuclei in 13CD2 groups at cryogenic temperatures. The method is based on cross-polarization from 1H to 13C and does not require any radio-frequency fields applied to the deuterium nuclei. After rapid dissolution, a new class of longlived spin states can be detected indirectly by 13C NMR in solution. These long-lived states result from a sextet-triplet imbalance (STI) that involves the two equivalent deuterons with spin I = 1. An STI has similar properties as a triplet-singlet imbalance that can occur in systems with two equivalent I = 1=2 spins. Although the lifetimes TSTI are shorter than T1(Cz), they can exceed the life-time T1(Dz) of deuterium Zeeman magnetization by a factor of more than 20. [ABSTRACT FROM AUTHOR]

Published
2016
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33. Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Face and Eye Tracking.

Author

Jasim, Sarah S., Hassan, Alia K. Abdu, and Turner, Scott

Subjects
ARTIFICIAL neural networks, DROWSINESS, FEATURE extraction, EYELIDS, IMAGE processing
Abstract

It is critical today to provide safe and collision-free transport. As a result, identifying the driver's drowsiness before their capacity to drive is jeopardized. An automated hybrid drowsiness classification method that incorporates the artificial neural network (ANN) and the gray wolf optimizer (GWO) is presented to discriminate human drowsiness and fatigue for this aim. The proposed method is evaluated in alert and sleep-deprived settings on the driver drowsiness detection of video dataset from the National Tsing Hua University Computer Vision Lab. The video was subjected to various video and image processing techniques to detect the drivers' eye condition. Four features of the eye were extracted to determine the condition of drowsiness, the percentage of eyelid closure (PERCLOS), blink frequency, maximum closure duration of the eyes, and eye aspect ratio (ARE). These parameters were then integrated into an ANN and combined with the proposed method (gray wolf optimizer with ANN [GWOANN]) for drowsiness classification. The accuracy of these models was calculated, and the results demonstrate that the proposed method is the best. An Adadelta optimizer with 3 and 4 hidden layer networks of (13, 9, 7, and 5) and (200, 150, 100, 50, and 25) neurons was utilized. The GWOANN technique had 91.18% and 97.06% accuracy, whereas the ANN model had 82.35% and 86.76%. [ABSTRACT FROM AUTHOR]

Published
2022
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35. Analysis of the structure of Public Expenditures and the role of oil price fluctuations in Iraq after 2004.

Author

Hassan, Alia Hanitel and Shaaibith, Sundus Jasim

Subjects
PUBLIC spending, PRICE fluctuations, PETROLEUM sales & prices, PUBLIC finance, PETROLEUM
Abstract

Oil is one of the important economic resources, especially in rentier economies, and since Iraq is a one-sided economy, the revenues from crude oil have a high percentage of contribution to the financing of public expenditures. In directing Public Expenditures by influencing the volume of revenues from crude oil in Iraq and the extent to which they are related to fluctuations and changes in oil prices, and therefore aimed at analyzing the fluctuations in crude oil prices, as well as analyzing the relationship between changes in crude oil prices and Public Expenditures in Iraq for the period (2004-2019) The most important results that were reached were that oil prices are characterized by severe fluctuations and instability, whose effects were reflected in changing the volume of Public Expenditures in a volatile manner, and current expenditures were controlled by them. The second focuses on the evolution of crude oil prices and the structure of public expenditures, while the third includes an analysis of the relationship between oil prices and public expenditures. [ABSTRACT FROM AUTHOR]

Published
2021

36. CatBoost Machine Learning Based Feature Selection for Age and Gender Recognition in Short Speech Utterances.

Author

Badr, Ameer A. and Abdul-Hassan, Alia K.

Subjects
FEATURE selection, AUTOMATIC speech recognition, SPEECH perception, MACHINE learning, SUPPORT vector machines
Abstract

Lately, with the rapid growth of various technologies, identifying the information of gender and age give short speech utterances has become a necessity for many applications in daily life like human-robot interaction, targeted marketing, identifying suspects in criminal cases, etc. Despite the comprehensive studies carried out to extract descriptive features, the recognition accuracy is still not satisfactory. In this study, an automatic system is proposed to classify age and gender in short speech utterances without depending on the text. Firstly, two groups of features are extracted from each utterance frame, followed by measuring 10 statistical functionals for each extracted feature dimension. After that, the extracted features dimensions are normalized using the Quantile technique. Then, the CatBoost machine is utilized as an important features detection to select the most discriminatory features for speaker age and gender recognition tasks. For classification purposes, the selected feature dimensions are fed into the Support Vector Machine (SVM). Experiments are conducted on the aGender data-set for measuring the suggested system's performance. The unweighted accuracies (UA) of the proposed system for gender, age, in addition to gender & age is 89.62%, 72.29%, and 71.96%, respectively. The achieved results outperform recent results on the same data-set. [ABSTRACT FROM AUTHOR]

Published
2021
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37. Probing short and long‐range interactions in native collagen inside the bone matrix by BioSolids CryoProbe.

Author

Tiwari, Nidhi, Wegner, Sebastian, Hassan, Alia, Dwivedi, Navneet, Rai, RamaNand, and Sinha, Neeraj

Subjects
MAGIC angle spinning, SEWAGE sludge, NUCLEAR magnetic resonance, BONES
Abstract

Solid‐state nuclear magnetic resonance is a promising technique to probe bone mineralization and interaction of collagen protein in the native state. However, many of the developments are hampered due to the low sensitivity of the technique. In this article, we report solid‐state nuclear magnetic resonance (NMR) experiments using the newly developed BioSolids CryoProbe™ to access its applicability for elucidating the atomic‐level structural details of collagen protein in native state inside the bone. We report here approximately a fourfold sensitivity enhancement in the natural abundance 13C spectrum compared with the room temperature conventional solid‐state NMR probe. With the advantage of sensitivity enhancement, we have been able to perform natural abundance 15N cross‐polarization magic angle spinning (CPMAS) and two‐dimensional (2D) 1H–13C heteronuclear correlation (HETCOR) experiments of native collagen within a reasonable timeframe. Due to high sensitivity, 2D 1H/13C HETCOR experiments have helped in detecting several short and long‐range interactions of native collagen assembly, thus significantly expanding the scope of the method to such challenging biomaterials. [ABSTRACT FROM AUTHOR]

Published
2021
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38. Towards Intelligent E-Learning Systems: A Hybrid Model for Predicatingthe Learning Continuity in Iraqi Higher Education.

Author

Kadhim, Mohammed K. and Hassan, Alia K.

Subjects
*ARTIFICIAL neural networks, *HYBRID systems, *RECURRENT neural networks, *INTELLIGENT tutoring systems, *INTERNET in education, *MACHINE learning, *ARTIFICIAL intelligence
Abstract

E-Learning system gains a great attention in the past years; with advance of the internet and the information exchange techniques the importance to merge the traditional learning means with the internet-based learning methods became a must especially in Iraq, the Iraqi higher education is now coping with the new information and communication technologies and adopting a modern methods for upgrading their education and learning ways. There are great efforts to blend E-Learning systems with the educational process, in order to fulfill this purposes the proposed research is advancing E-Learning systems by suggesting a hybrid method that combines two Artificial Intelligence Techniques (AI) inside the design and the development of an intelligent E-Learning system for computer science department at university of technology. The utilization of Artificial Neural Networks algorithm (ANNs) especially Recurrent Neural Networks (RNN) is a way of implementing deep learning technique to predict the students' final out comes in virtual class room based on their grades and their learning behaviors. RNN is optimized by utilizing ADAM optimizer to lift the accuracy of the proposed algorithm, the dataset are gathered and processed to suite the education purposes and was divided into80% for training the model and 20% for testing the model, the results of the hybrid model are compared with other machine learning methods like Multi-Layer Perceptron (MLP), decision tree, naïve Bayesian, and random forest using WEKA environment, the results of the proposed model showed a promising accuracy when compared with the mentioned machine learning algorithms. [ABSTRACT FROM AUTHOR]

Published
2020
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39. Speech Emotion Recognition Using MELBP Variants of Spectrogram Image.

Author

Mohammed, Suhaila N. and Abdul Hassan, Alia K.

Subjects
EMOTION recognition, SPEECH perception, SPECTROGRAMS, AUTOMATIC speech recognition, SPEECH synthesis, IMAGE representation, FEATURE extraction
Abstract

Speech emotion recognition finds many applications in the daily life like conversational agents, human robot interaction, call centres etc. However; the task of emotion recognition from speech signal is not trivial due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the signal in an accurate manner. Image processing techniques are exploited in this paper to solve speech emotion recognition problem. After converting the signal into 2D spectrogram image representation, four forms of Extended Local Binary Pattern (ELBP) are generated to serve as a source for feature extraction stage. The histograms of multiple blocks from ELBP variants are computed and fed to Deep Belief Network (DBN) for classification purpose. Different tests were performed using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the achieved results showed that when using combined vectors of MELBP, the system gives the best accuracy which is 72.14%. The achieved result outperforms state-of-the-art results on the same database. [ABSTRACT FROM AUTHOR]

Published
2020
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40. Post‐transcriptional mechanisms regulating parathyroid hormone gene expression in secondary hyperparathyroidism.

Author

Kilav‐Levin, Rachel, Hassan, Alia, Nechama, Morris, Shilo, Vitali, Silver, Justin, Ben‐Dov, Iddo Z., and Naveh‐Many, Tally

Subjects
*GENE expression, *PARATHYROID hormone, *ISOMERASES, *PARATHYROID glands, *CHRONIC kidney failure, *KNOCKOUT mice
Abstract

Parathyroid hormone (PTH) regulates serum calcium levels and bone strength. Secondary hyperparathyroidism (SHP) is a common complication of chronic kidney disease (CKD) that correlates with morbidity and mortality. In experimental SHP, the increased PTH gene expression is due to increased PTH mRNA stability and is mediated by protein–PTH mRNA interactions. Adenosine–uridine‐rich binding factor 1 (AUF1) stabilizes and K‐homology splicing regulatory protein (KSRP) destabilizes PTH mRNA. The peptidyl‐prolyl cis/trans isomerase Pin1 acts on target proteins, including mRNA‐binding proteins. Pin1 leads to KSRP dephosphorylation, but in SHP, parathyroid Pin1 activity is decreased and phosphorylated KSRP fails to bind PTH mRNA, leading to increased PTH mRNA stability and levels. A further level of post‐transcriptional regulation occurs through microRNA (miRNA). Dicer mediates the final step of miRNA maturation. Parathyroid‐specific Dicer knockout mice that lack miRNAs in the parathyroid develop normally. Surprisingly, these mice fail to increase serum PTH in response to both hypocalcemia and CKD, indicating that parathyroid Dicer and miRNAs are essential for stimulation of the parathyroid. Human and rodent parathyroids share similar miRNA profiles that are altered in hyperparathyroidism. The evolutionary conservation of abundant miRNAs and their regulation in hyperparathyroidism indicate their significance in parathyroid physiology and pathophysiology. let‐7 and miR‐148 antagonism modifies PTH secretion in vivo and in vitro, suggesting roles for specific miRNAs in parathyroid function. This review summarizes the current knowledge on the post‐transcriptional mechanisms of PTH gene expression in SHP and the central contribution of miRNAs to the high serum PTH levels of both primary hyperparathyroidism and SHP. [ABSTRACT FROM AUTHOR]

Published
2020
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43. Location Aspect Based Sentiment Analyzer for Hotel Recommender System.

Author

Abdul Hassan, Alia Karim and Aldeen Abdulwahhab, Ahmed Bahaa

Subjects
*RECOMMENDER systems, *USER charges, *DECISION making, *CUSTOMER services, *LEXICON
Abstract

Recently personal recommender system has spread fast, because of its role in helping users to make their decision. Location-based recommender systems are one of these systems. These systems are working by sensing the location of the person and suggest the best services to him in his area. Unfortunately, these systems that depend on explicit user rating suffering from cold start and sparsity problems. The proposed system depends on the current user position to recommend a hotel to him, and on reviews analysis. The hybrid sentiment analyzer consists of supervised sentiment analyzer and the second stage is lexicon sentiment analyzer. This system has a contribute over the sentiment analyzer by extracting the aspects that users have been mentioned in their reviews like (cleanness, service, etc.) by using accurate parsing system built on latent semantic analysis results. The accuracy measurements of the proposed sentiment analyzer were perfect. [ABSTRACT FROM AUTHOR]

Published
2019
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44. INTELLIGENT AUTHENTICATION FOR IDENTITY AND ACCESS MANAGEMENT: A REVIEW PAPER.

Author

Abdul-Hassan, Alia Karim and Hadi, Iman Hasson

Subjects
ADVANCED Encryption Standard, INFORMATION technology security, NEAR field communication, SECURITY systems, INTELLIGENT transportation systems, INFORMATION storage & retrieval systems
Abstract

Identity and access management (IAM) system usually consist of predefined tasks as an information security system. The main task is the authentication, since it is responsible for user identity proving for service providers that corporate with (IAM). This paper provides a review on intelligent authentication research applicable to IAM systems. These researches are evaluated according to the proposal of intelligent authentication key factors. Depending on this evaluation it could not be found research implement an authentication that satisfies all these key factors. [ABSTRACT FROM AUTHOR]

Published
2019
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45. Arabic (Indian) Handwritten Digits Recognition Using Multi feature and KNN Classifier.

Author

Abdul Hassan, Alia Karim

Subjects
DISCRETE cosine transforms, STANDARD deviations, K-nearest neighbor classification, GRAPHOLOGY, NUMERALS
Abstract

Copyright of Journal of Babylon University is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2018
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46. Proposed Method of Air Traffic Routing in Dynamic Environment Usiing Modifed rrt With Collision Avoid Nace.

Author

Abdul Hassan, Alia Karim and Adwaan, Sheelan Waad

Subjects
*AIR traffic control, *AIR traffic rules, *AIRWAYS (Aeronautics), *AIRLINE routes, *AIRLINE industry
Abstract

In the current Airlines Air Traffic Management (ATM), the Air Traffic Control Operators (ATCO), with the Air Traffic Control systems (ATC), operate air traffic paths with a small number of fixed routes. Problems of fixed routes appear such that even when they reduce the chance for conflict, they also produce flight paths plans that do not reduce flight time or fuel usage. In nowadays Airlines are heavily overloaded and anxious to minimize the aircrafts fuel usage costs, increase airplanes, and optimize the paths or the flight routes in order to find the most optimal suitable flight paths. This paper presents a new path planning method that deal with such problem effectively, the idea was to produce flights routes by allowing the ATCO, or the pilot to select better fuel-efficient routes with reducing flight time. This work has been done by using modified ‘Rapidly Exploring Random Tree’ (RRT) path planning algorithm in dynamic cluttered environment with collision avoidance. The experiment of the developed algorithm simulation experiment shows promising result for future research. [ABSTRACT FROM AUTHOR]

Published
2018
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47. Distributed Information Retrieval Based On Metaheuristic Search and Query Expansion.

Author

Abdul Hassan, Alia Karim and Hadi, Mustafa Jasim

Subjects
INFORMATION retrieval, METAHEURISTIC algorithms, QUERY (Information retrieval system), GRAPH theory, HEURISTIC algorithms
Abstract

Copyright of Journal of Kufa for Mathematics & Computer is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2017
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48. Reviews Sentiment analysis for collaborative recommender system.

Author

Abdul Hassan, Alia Karim and aldeen abdulwahhab, Ahmed Bahaa

Subjects
DATA analysis, COMPUTER users, MATHEMATICAL models, NUMERICAL analysis, MATHEMATICAL analysis
Abstract

recommender system nowadays is used to deliver services and information to users. A recommender system is suffering from problems of data sparsity and cold start because of insufficient user rating or absence of data about users or items. This research proposed a sentiment analysis system work on user reviews as an additional source of information to tackle data sparsity problems. Sentiment analysis system implemented using NLP techniques with machine learning to predict user rating form his review; this model is evaluated using Yelp restaurant data set, IMDB reviews data set and Arabic qaym.com restaurant reviews data set under various classification model, the system was efficient in predicting rating from reviews. [ABSTRACT FROM AUTHOR]

Published
2017
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49. Information Retrieval using Modified Genetic Algorithm.

Author

Abdul Hassan, Alia Karim, mhawi, Duaa Enteesha, and Abdulwahid, Sarah Najm

Subjects
*GENETIC algorithms, *QUERY languages (Computer science), *INFORMATION retrieval, *DOCUMENTATION, *DATABASE searching
Abstract

Several techniques proposed to retrieve the most relevant HTML documents to user query. Genetic algorithm (GA) one of these technique, which creates several generations iteratively using the operations of: selection, crossover and mutation before producing the results. In this paper, focuses on enhance the operations of GA and proposed new fitness function to enhance the quality of the retrieved results. This technique applied to HTML documents and using recall, precision measures to evaluate. The results show high improvement in the retrieved documents quality in terms of these measures. [ABSTRACT FROM AUTHOR]

Published
2017

50. Sense-Based Arabic Information Retrieval Using Harmony Search Algorithm.

Author

Hassan, Alia Karim Abdul and Hadi, Mustafa Jasim

Subjects
INFORMATION retrieval, ARABIC language, DATA quality, SEARCH algorithms, QUERYING (Computer science)
Abstract

Information Retrieval (IR) is a field of computer science that deals with storing, searching, and retrieving documents that satisfy the user need. The modern standard Arabic language is rich in multiple meanings (senses) for many words and this is substantially due to lack of diacritical marks. The task for finding appropriate meanings is a key demand in most of the Arabic IR applications. Actually, the successful system should not be interested only in the retrieval quality and oblivious to the system efficiency. Thus, this paper contributes to improve the system effectiveness by finding appropriate stemming methodology, word sense disambiguation, and query expansion for addressing the retrieval quality of AIR. Also, it contributes to improve the system efficiency through using a powerful metaheuristic search called Harmony Search (HS) algorithm inspired from the musical improvisation processes. The performance of the proposed system outperforms the one in the traditional system in a rate of 19.5% while reduces the latency in an approximate rate of 0.077 second for each query. [ABSTRACT FROM AUTHOR]

Published
2017
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