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363 results on '"Kopyt A"'

1. Increase of flight operations effectiveness using automated control over a fleet of various UAS

Author

Bibik Przemysław and Kopyt Antoni

Subjects
uas, trajectory optimization, fleet of uas, efficiency improvement, advanced system, Oceanography, GC1-1581, Geology, QE1-996.5
Abstract

Following paper presents a research aiming to increase the efficiency of an Unmanned Aerial System (UAS) fleet during mission execution. The developed system allows to reduce the mission time by considering the fleet diversity. System is based on a multilevel optimization, applying an innovative trajectory generation method. The Mixed Integer Linear Programming (MILP) algorithm was adopted, so the trajectories for individual platform were optimal (shortest). The developed solution considers not only the area but also the UASs performance and sensors capabilities. The mission operator with the dedicated GUI could control and designate the platforms for various tasks. The method was tested on various platforms with different performance. The method proved its efficiency reducing the mission time up to 15%. Finally, the system was successfully tested in real environment with the use of three various platforms.

Published
2019
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2. Population density as the attractor of business to the place

Author

Katarzyna Kopczewska, Maria Kubara, and Mateusz Kopyt

Subjects
Economies of density, Attracting mechanism, Population density, Hierarchical agglomeration, Convenience, Business venturing, Medicine, Science
Abstract

Abstract Firm location studies traditionally assume that this is business that attracts other business to a given location. They focus on knowledge transfers between the most productive and innovative firms and analyse agglomeration economies arising from matching, learning and sharing mechanisms. We argue that the population density also attracts firms to the place. Therefore, we extend this stream of research by using the concept of economies of density to discuss the effects of the attraction of firms by population. Our study explores the existence of the hierarchical causal mechanism that occurs when 2nd line firms understood as non-innovative, less productive retail and service businesses together with human settlement create an environment that attracts 1st line firms - the most innovative and productive businesses. We show that population density and business agglomeration jointly affect the location of firms in different sectors and should be considered as complementary rather than substitutable attraction factors.

Published
2024
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4. Long-Term Results from an Open-Label Extension Study of Atacicept for the Treatment of IgA Nephropathy

Author

Barratt, Jonathan, Barbour, Sean, Brenner, Robert, Cooper, Kerry, Wei, Xuelian, Eren, Necmi, Floege, Jürgen, Jha, Vivekanand, Kim, Sung Gyun, Maes, Bart, Phoon, Richard K.S., Singh, Harmeet, Tesař, Vladimír, Lafayette, Richard, Umanath, Kausik, Kopyt, Nelson, Lafayette, Richard, Singh, Harmeet, Yalavarthy, Rajesh, Campbell, Kirk, Gohh, Reginald, Shah, Ankur, Zhang, Jingjing, Kumar, Jayant, Barbour, Sean, Bouquegneau, Antoine, Maes, Bart, Speeckaert, Marijn, Vielhauer, Volker, Hugo, Christian, Nitschke, Martin, Tokgoz, Bulent, Eren, Necmi, Rydzewski, Andrzej, Doulton, Timothy, Power, Albert, Hall, Matthew, Willcocks, Lisa, Tesar, Vladimir, Rychlik, Ivan, Goumenos, Dimitrios, Papagianni, Aikaterini, Stangou, Maria, Boletis, Ioannis, Marinaki, Smaragdi, Stylianou, Konstantinos, Zermpala, Synodi, Ntounousi, Evangelia, Gang, Sishir, Alexander, Suceena, Pandey, Rajendra, Dalal, Sonal, Sunil, R, Khetan, Prakash, Jain, Alok, Park, Hyeong Cheon, Kim, Dong Ki, Kim, Sung Gyun, Kim, Beom Seok, Levidiotis, Vicki, Pedagogos, Eugenia, Francis, Ross, Ryan, Jessica, Phoon, Richard, Yahya, Rosnawati, Nor, Bin Mohd, Safhan, Fariz, Lim, Soo Kun, and Teng, Kok Seng

Published
2024
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6. Frequency of Group A Streptococcus Infection and Analysis of Antibiotic Use in Patients with Pharyngitis—A Retrospective, Multicenter Study

Author

Martyna Biała, Mateusz Babicki, Wojciech Malchrzak, Sandra Janiak, Dominik Gajowiak, Alan Żak, Karolina Kłoda, Piotr Gibas, Justyna Ledwoch, Anna Myśliwiec, Daria Kopyt, Anna Węgrzyn, Brygida Knysz, and Patrycja Leśnik

Subjects
Streptococcus pyogenes, GAS, infection, antibiotics, Medicine
Abstract

Streptococcus pyogenes is responsible for 20–30% of pharyngitis in children and 5–15% in adults. The ineffective treatment of group A Streptococcus (GAS) infections can result in postinfectious sequelae. This study aims to evaluate the frequency of GAS pharyngitis and assess the management of patients with pharyngitis and antibiotic use. We conducted a multicenter, retrospective analysis of medical records from nine primary care centers in Poland. The study enrolled 1949 medical records of patients (children 67.4%, adults 32.6%). An infection of Streptococcus pyogenes, based on a rapid strep test, was diagnosed in 830 patients (42.6%). In the comprehensive study group of 1949 patients, 1054 (54.1%) were given antibiotics. Notably, 224 patients had a negative rapid strep test result but still received antibiotic treatment, underscoring the complexity of treatment decisions. The most commonly used antibiotics were oral penicillin V in 431 cases (41%) and amoxicillin in 219 cases (20.8%). We observed no significant difference between positive rapid strep test results and patients’ sociodemographic data and comorbidities. The prevalence of GAS was 42.6% in the analyzed records of patients with pharyngitis, and 54.1% were prescribed antibiotics. Antibiotics were overprescribed for sore throats. Strategies are needed to promote rational antibiotic use.

Published
2024
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7. Diagnostic and Therapeutic Challenge Caused by Candida albicans and Aspergillus spp. Infections in a Pediatric Patient as a Complication of Acute Lymphoblastic Leukemia Treatment: A Case Report and Literature Review

Author

Natalia Zaj, Weronika Kopyt, Emilia Kamizela, Julia Zarychta, Adrian Kowalczyk, Monika Lejman, and Joanna Zawitkowska

Subjects
invasive fungal infections, Aspergillus spp. infection, Candida albicans infection, children, acute lymphoblastic leukemia, Medicine
Abstract

Fungal infections constitute a significant challenge and continue to be a predominant cause of treatment failure in pediatric leukemia cases. Despite the implementation of antifungal prophylaxis, these infections contribute to approximately 20% of cases in children undergoing treatment for acute lymphoblastic leukemia (ALL). The aim of this study is to highlight the diagnostic and therapeutic challenges associated with invasive fungal infections (IFIs). We also present a review of the epidemiology, risk factors, treatment, and a clinical presentation of IFI in patients with ALL. This case report details the clinical course of confirmed Candida albicans (C. albicans) and Aspergillus spp. infections during the consolidation phase of ALL treatment in a 5-year-old pediatric patient. This male patient did not experience any complications until Day 28 of protocol II. Then, the patient’s condition deteriorated. Blood culture detected the growth of C. albicans. Despite the implementation of targeted therapy, the boy’s condition did not show improvement. The appearance of respiratory symptoms necessitated a computed tomography (CT) of the chest, which revealed multiple nodular densities atypical for C. albicans etiology. In spite of ongoing antifungal treatment, the lesions depicted in the CT scans showed no regression. A lung biopsy ultimately identified Aspergillus species as the source of the infection. Overcoming fungal infections poses a considerable challenge; therefore, an accurate diagnosis and the prompt initiation of targeted therapy are crucial in managing these infections in patients with leukemia.

Published
2024
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9. Short-Term Forecasts of Energy Generation in a Solar Power Plant Using Various Machine Learning Models, along with Ensemble and Hybrid Methods

Author

Paweł Piotrowski and Marcin Kopyt

Subjects
ensemble forecasting methods, feature engineering, feature importance, machine learning, short-term forecasting, solar power plant, Technology
Abstract

High-quality short-term forecasts of electrical energy generation in solar power plants are crucial in the dynamically developing sector of renewable power generation. This article addresses the issue of selecting appropriate (preferred) methods for forecasting energy generation from a solar power plant within a 15 min time horizon. The effectiveness of various machine learning methods was verified. Additionally, the effectiveness of proprietary ensemble and hybrid methods was proposed and examined. The research also aimed to determine the appropriate sets of input variables for the predictive models. To enhance the performance of the predictive models, proprietary additional input variables (feature engineering) were constructed. The significance of individual input variables was examined depending on the predictive model used. This article concludes with findings and recommendations regarding the preferred predictive methods.

Published
2024
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12. Kidney and Cardiovascular Effects of Canagliflozin According to Age and Sex: A Post Hoc Analysis of the CREDENCE Randomized Clinical Trial

Author

Perkovic, Vlado, Mahaffey, Kenneth W., Agarwal, Rajiv, Bakris, George, Brenner, Barry M., Cannon, Christopher P., Charytan, David M., de Zeeuw, Dick, Greene, Tom, Jardine, Meg J., Heerspink, Hiddo J.L., Levin, Adeera, Meininger, Gary, Neal, Bruce, Pollock, Carol, Wheeler, David C., Zhang, Hong, Zinman, Bernard, Jardine, Meg, Li, Nicole, Kolesnyk, Inna, Aizenberg, Diego, Pecoits-Filho, Roberto, Cherney, David, Obrador, Gregorio, Chertow, Glenn, Chang, Tara, Hawley, Carmel, Ji, Linong, Wada, Takashi, Jha, Vivekanand, Lim, Soo Kun, Lim-Abrahan, Mary Anne, Santos, Florence, Chae, Dong-Wan, Hwang, Shang-Jyh, Vazelov, Evgueniy, Rychlík, Ivan, Hadjadj, Samy, Krane, Vera, Rosivall, László, De Nicola, Luca, Dreval, Alexander, Nowicki, Michał, Schiller, Adalbert, Distiller, Larry, Górriz, Jose L., Kolesnyk, Mykola, David, Wheeler, C., Guerrero, Rodolfo Andres Ahuad, Albisu, Juan Pablo, Alvarisqueta, Andres, Bartolacci, Ines, Berli, Mario Alberto, Bordonava, Anselmo, Calella, Pedro, Cantero, Maria Cecilia, Cartasegna, Luis Rodolfo, Cercos, Esteban, Coloma, Gabriela Cecilia, Colombo, Hugo, Commendatore, Victor, Cuadrado, Jesus, Cuneo, Carlos Alberto, Cusumano, Ana Maria, Douthat, Walter Guillermo, Dran, Ricardo Dario, Farias, Eduardo, Fernandez, Maria Florencia, Finkelstein, Hernan, Fragale, Guillermo, Fretes, Jose Osvaldo, Garcia, Nestor Horacio, Gastaldi, Anibal, Gelersztein, Elizabeth, Glenny, Jorge Archibaldo, Gonzalez, Joaquin Pablo, Colaso, Patricia del Carmen Gonzalez, Goycoa, Claudia, Greloni, Gustavo Cristian, Guinsburg, Adrian, Hermida, Sonia, Juncos, Luis Isaias, Klyver, Maria Isabel, Kraft, Florencia, Krynski, Fernando, Lanchiotti, Paulina Virginia, Leon de la Fuente, Ricardo Alfonso, Marchetta, Nora, Mele, Pablo, Nicolai, Silvia, Novoa, Pablo Antonio, Orio, Silvia Ines, Otreras, Fabian, Oviedo, Alejandra, Raffaele, Pablo, Resk, Jorge Hector, Rista, Lucas, Papini, Nelson Rodriguez, Sala, Jorgelina, Santos, Juan Carlos, Schiavi, Lilia Beatriz, Sessa, Horacio, Casabella, Tomas Smith, Ulla, Maria Rosa, Valdez, Maria, Vallejos, Augusto, Villarino, Adriana, Visco, Virginia Esther, Wassermann, Alfredo, Zaidman, Cesar Javier, Cheung, Ngai Wah, Droste, Carolyn, Fraser, Ian, Johnson, David, Mah, Peak Mann, Nicholls, Kathy, Packham, David, Proietto, Joseph, Roberts, Anthony, Roger, Simon, Tsang, Venessa, Raduan, Roberto Abrão, Costa, Fernando Augusto Alves da, Amodeo, Celso, Turatti, Luiz Alberto Andreotti, Bregman, Rachel, Sanches, Fernanda Cristina Camelo, Canani, Luis Henrique, Chacra, Antônio Roberto, Borges, João Lindolfo Cunha, Vêncio, Sérgio Alberto Cunha, Franco, Roberto Jorge da Silva, d’Avila, Domingos, Portes, Evandro de Souza, de Souza, Pedro, Deboni, Luciane Mônica, Fraige Filho, Fadlo, Neto, Bruno Geloneze, Gomes, Marcus, Kohara, Suely Keiko, Keitel, Elizete, Saraiva, Jose Francisco Kerr, Lisboa, Hugo Roberto Kurtz, Contieri, Fabiana Loss de Carvalho, Milagres, Rosângela, Junior, Renan Montenegro, de Brito, Claudia Moreira, Hissa, Miguel Nasser, Sabbag, Ângela Regina Nazario, Noronha, Irene, Panarotto, Daniel, Filho, Roberto Pecoits, Pereira, Márcio Antônio, Saporito, Wladmir, Scotton, Antonio Scafuto, Schuch, Tiago, de Almeida, Roberto Simões, Ramos, Cássio Slompo, Felício, João Soares, Thomé, Fernando, Hachmann, Jean Carlo Tibes, Yamada, Sérgio, Hayashida, Cesar Yoiti, Petry, Tarissa Beatrice Zanata, Zanella, Maria Teresa, Andreeva, Viktoria, Angelova, Angelina, Dimitrov, Stefan, Genadieva, Veselka, Genova-Hristova, Gabriela, Hristozov, Kiril, Kamenov, Zdravko, Koundurdjiev, Atanas, Lozanov, Lachezar, Margaritov, Viktor, Nonchev, Boyan, Rangelov, Rangel, Shinkov, Alexander, Temelkova, Margarita, Velichkova, Ekaterina, Yakov, Andrian, Aggarwal, Naresh, Aronson, Ronnie, Bajaj, Harpreet, Chouinard, Guy, Conway, James, Cournoyer, Serge, DaRoza, Gerald, De Serres, Sacha, Dubé, François, Goldenberg, Ronald, Gupta, Anil, Gupta, Milan, Henein, Sam, Khandwala, Hasnain, Leiter, Lawrence, Madore, François, McMahon, Alan, Muirhead, Norman, Pichette, Vincent, Rabasa-Lhoret, Remi, Steele, Andrew, Tangri, Navdeep, Torshizi, Ali, Woo, Vincent, Zalunardo, Nadia, Montenegro, María Alicia Fernández, Gonzalo Godoy Jorquera, Juan, Fariña, Marcelo Medina, Gajardo, Victor Saavedra, Vejar, Margarita, Chen, Nan, Chen, Qinkai, Gan, Shenglian, Kong, Yaozhong, Li, Detian, Li, Wenge, Li, Xuemei, Lin, Hongli, Liu, Jian, Lu, Weiping, Mao, Hong, Ren, Yan, Song, Weihong, Sun, Jiao, Sun, Lin, Tu, Ping, Wang, Guixia, Yang, Jinkui, Yin, Aiping, Yu, Xueqing, Zhao, Minghui, Zheng, Hongguang, Mendoza, Jose Luis Accini, Arcos, Edgar, Avendano, Jorge, Diaz Ruiz, Jorge Ernesto Andres, Ortiz, Luis Hernando Garcia, Gonzalez, Alexander, Triana, Eric Hernandez, Higuera, Juan Diego, Malaver, Natalia, de Salazar, Dora Inés Molina, Rosero, Ricardo, Alexandra Terront Lozano, Monica, Cometa, Luis Valderrama, Valenzuela, Alex, Vargas Alonso, Ruben Dario, Villegas, Ivan, Yupanqui, Hernan, Bartaskova, Dagmar, Barton, Petr, Belobradkova, Jana, Dohnalova, Lenka, Drasnar, Tomas, Ferkl, Richard, Halciakova, Katarina, Klokocnikova, Vera, Kovar, Richard, Lastuvka, Jiri, Lukac, Martin, Pesickova, Satu, Peterka, Karel, Pumprla, Jiri, Rychlik, Ivan, Saudek, Frantisek, Tesar, Vladimir, Valis, Martin, Weiner, Pavel, Zemek, Stanislav, Alamartine, Eric, Borot, Sophie, Cariou, Bertrand, Dussol, Bertrand, Fauvel, Jean-Pierre, Gourdy, Pierre, Klein, Alexandre, Le Meur, Yannick, Penfornis, Alfred, Roussel, Ronan, Saulnier, Pierre-Jean, Thervet, Eric, Zaoui, Philippe, Burst, Volker, Faghih, Markus, Faulmann, Grit, Haller, Hermann, Jerwan-Keim, Reinhold, Maxeiner, Stephan, Paschen, Björn, Plassmann, Georg, Rose, Ludger, Gonzalez Orellana, Ronaldo Arturo, Haase, Franklin Paul, Moreira Diaz, Juan Pablo, Ramirez Roca, Luis Alberto, Sánchez Arenales, Jose Antonio, Sanchez Polo, José Vicente, Juarez, Erick Turcios, Csecsei, Gyongyi, Csiky, Botond, Danos, Peter, Deak, Laszlo, Dudas, Mihaly, Harcsa, Eleonora, Keltai, Katalin, Keresztesi, Sandor, Kiss, Krisztian, Konyves, Laszlo, Major, Lajos, Mileder, Margit, Molnar, Marta, Mucsi, Janos, Oroszlan, Tamas, Ory, Ivan, Paragh, Gyorgy, Peterfai, Eva, Petro, Gizella, Revesz, Katalin, Takacs, Robert, Vangel, Sandor, Vasas, Szilard, Zsom, Marianna, Abraham, Oomman, Bhushan, Raju Sree, Deepak, Dewan, Edwin, Fernando M., Gopalakrishnan, Natarajan, Gracious, Noble, Hansraj, Alva, Jain, Dinesh, Keshavamurthy, C.B., Khullar, Dinesh, Manisha, Sahay, Peringat, Jayameena, Prasad, Narayan, Satyanarayana, Rao K., Sreedhar, Reddy, Sreelatha, Melemadathil, Sudhakar, Bhimavarapu, Chandra Vyasam, Ramesh, Bonadonna, Riccardo, Castellino, Pietro, Ceriello, Antonio, Chiovato, Luca, De Cosmo, Salvatore, Derosa, Giuseppe, Di Carlo, Alberto, Di Cianni, Graziano, Frascà, Giovanni, Fuiano, Giorgio, Gambaro, Giovanni, Garibotto, Giacomo, Giorda, Carlo, Malberti, Fabio, Mandreoli, Marcora, Mannucci, Edoardo, Orsi, Emanuela, Piatti, Piermarco, Santoro, Domenico, Sasso, Ferdinando Carlo, Serviddio, Gaetano, Stella, Andrea, Trevisan, Roberto, Veronelli, Anna Maria, Zanoli, Luca, Akiyama, Hitoshi, Aoki, Hiromi, Asano, Akimichi, Iitsuka, Tadashi, Kajiyama, Shizuo, Kashine, Susumu, Kawada, Toshio, Kodera, Takamoto, Kono, Hiroshi, Koyama, Kazunori, Kumeda, Yasuro, Miyauchi, Shozo, Mizuyama, Kazuyuki, Niiya, Tetsuji, Oishi, Hiroko, Ota, Satoshi, Sakakibara, Terue, Takai, Masahiko, Tomonaga, Osamu, Tsujimoto, Mitsuru, Wakasugi, Masakiyo, Wakida, Yasushi, Watanabe, Takayuki, Yamada, Masayo, Yanagida, Kazuhiro, Yanase, Toshihiko, Yumita, Wataru, Gaupsiene, Egle, Kozloviene, Dalia, Navickas, Antanas, Urbanaviciene, Egle, Abdul Ghani, Rohana, Kadir, Khalid Abdul, Ali, Norsiah, Che Yusof, Mohd Daud, Gan, Chye Lee, Ismail, Mastura, Kong, Wei Yen, Lam, Swee Win, Lee, Li Yuan, Loh, Chek Loong, Manocha, Anita Bhajan, Ng, Kee Sing, Ahmad, Nik Nur Fatnoon Nik, Ratnasingam, Vanassa, Shudim, Saiful Shahrizal Bin, Vengadasalam, Paranthaman, Abraira Munoz, Luis David, Salazar, Melchor Alpizar, Cruz, Juan Baas, Soto, Mario Burgos, Ramos, Jose Chevaile, Wong, Alfredo Chew, Correa Rotter, Jose Ricardo, Escalante, Tonatiu Diaz, Enriquez Sosa, Favio Edmundo, Lozano, Fernando Flores, Flota Cervera, Luis Fernando, Baron, Paul Frenk, Ballesteros, Cecilia Garcia, Gomez Rangel, Jose David, Herrera Jimenez, Luis Enrique, Irizar Santana, Sergio Saul, Flores, Fernando Jimenez, Molina, Hugo Laviada, Luna Ceballos, Rosa Isela, del Campo Blanco, Belia Martin, Franco, Guadalupe Morales, Moreno Loza, Oscar Tarsicio, Rocha, Cynthia Mustieles, Vera, Gregorio Obrador, Castellanos, Ricardo Orozco, Calcaneo, Juan Peralta, Reyes Rosano, Miguel Angel, Pattzi, Hiromi Rodriguez, Guzman, Juan Rosas, Rucker Joerg, Isabel Erika, Saavedra Sanchez, Sandra Berenice, Sanchez Mijangos, Jose Hector, Sanson, Pablo Serrano, Tamayo y Orozco, Juan Alfredo, Chavez, Eloisa Tellez, Cepeda, Alejandro Valdes, Carrillo, Luis Venegas, Mesa, Juan Villagordoa, Escobedo, Rolando Zamarripa, Baker, John, Noonan, Paul, Scott, Russell, Walker, Robert, Watson, Edward, Williams, Michael, Young, Simon, Abejuela, Zaynab, Agra, Jeimeen, Aquitania, Grace, Caringal, Clodoaido, Comia, Rhea Severina, Santos, Lalaine Delos, Gomez, Olivert, Jimeno, Cecilia, Tan, Gerry, Tolentino, Marsha, Yao, Christy, Yap, Yvette Ethel, Lallaine Ygpuara, Ma. Dovie, Bijata-Bronisz, Renata, Hotlos, Lucyna, Januszewicz, Andrzej, Kaczmarek, Barbara, Kaminska, Anna, Lazuka, Lech, Madej, Andrzej, Mazur, Stanislaw, Mlodawska-Choluj, Dorota, Nowicki, Michal, Orlowska-Kowalik, Grazyna, Popenda, Grazyna, Rewerska, Barbara, Sowinski, Dariusz, Angelescu, Liliana Monica, Anghel, Veronica, Avram, Rodica-Ioana, Busegeanu, Mihaela-Magdalena, Cif, Adriana, Cosma, Dana, Crisan, Carmen, Demian, Luiza Despina, Ferariu, Ioana Emilia, Halmagyi, Ildiko, Hancu, Nicolae, Munteanu, Mircea, Negru, Doru, Onaca, Adriana Gabriela, Petrica, Ligia, Popa, Amorin Remus, Ranetti, Aurelian-Emil, Serafinceanu, Cristian, Toarba, Cristina, Agafyina, Alina, Barbarash, Olga, Barysheva, Olga, Chizhov, Daniil, Dobronravov, Vladimir, Glinkina, Irina, Grineva, Elena, Khirmanov, Vladimir, Kolmakova, Elena, Koroleva, Tatiana, Kvitkova, Liudmila, Marasaev, Viacheslav, Mkrtumyan, Ashot, Morugova, Tatiana, Nagibovich, Galina, Nagibovich, Oleg, Nedogoda, Sergei, Osipova, Irina, Raskina, Tatiana, Samoylova, Yulia, Sazonova, Olga, Shamkhalova, Minara, Shutemova, Elena, Shwartz, Yuriy, Uriasyev, Oleg, Vorobyev, Sergey, Zateyshchikova, Anna, Zateyshshikov, Dmitry, Zykova, Tatyana, Antic, Slobodan, Djordjevic, Miodrag, Kendereski, Aleksandra, Lalic, Katarina, Lalic, Nebojsa, Popovic-Radinovic, Vesna, Babikova, Jana, Benusova, Olga, Buganova, Ingrid, Culak, Jan, Dzupina, Andrej, Dzuponova, Jana, Fulop, Peter, Ilavska, Adriana, Martinka, Emil, Ochodnicka, Zuzana, Pella, Daniel, Smatanova, Iveta, Ahmed, Fayzal, Badat, Aysha, Breedt, Johannes, Distiller, Lawrence, Govender, Vimladhevi, Govender, Ravendran, Joshi, Mukesh, Jurgens, Jaco, Latiff, Gulam, Lombard, Landman, Mookadam, Mohamed, Ngcakani, Nomangesi, Nortje, Hendrik, Oosthuizen, Helena, Pillay-Ramaya, Larisha, Prozesky, Hans, Reddy, Jeevren, Rheeder, Paul, Seeber, Mary, Cho, Young Min, Jeong, In-Kyung, Kim, Sin Gon, Kim, Yeong Hoon, Kwon, Hyuk-Sang, Kwon, Min Jeong, Lee, Byung-Wan, Lee, JungEun, Lee, Moon-Kyu, Nam, Moon-Suk, Oh, Kook-Hwan, Park, Cheol- Young, Park, Sun-Hee, Yoon, Kun Ho, Garcia, Pere Alvarez, Mercadal, Luis Asmarats, Barrios, Clara, Castro, Fernando Cereto, Guldris, Secundino Cigarran, Lopez, Marta Dominguez, Egido de los Rios, Jesus, Fresnedo, Gema Fernandez, Serrano, Antonio Galan, Garcia, Isabel, Gonzalez Martinez, Francisco Javier, Jodar Gimeno, Jose Esteban, Mendoza, Manuel Lopez, Marin, Tamara Malek, Portillo, Cristobal Morales, Munar Vila, Maria Antonia, Torres, Manuel Muñoz, Iglesias, Javier Nieto, Perez, Jonay Pantoja, Vera, Merce Perez, Portoles Perez, Jose M., Quesada Simón, María Angustias, Canonge, Rafael Simo, Gonzalez, Alfonso Soto, Riera, Manel Terns, Tinahones Madueno, Francisco Jose, Plaza, Mercedes Velo, Chang, Chwen-Tzuei, Chuang, Lee-Ming, Hsia, Te-Lin, Hsieh, Chang-Hsun, Lin, Chih-Ching, Lu, Yung- Chuan, Sheu, Wayne H-H, Barna, Olga, Bilyk, Svitlana D., Botsyurko, Volodymyr, Dudar, Iryna, Fushtey, Ivan, Godlevska, Olga, Golovchenko, Oleksandr, Gyrina, Olga, Kazmirchuk, Anatoliy, Komisarenko, Iuliia, Korzh, Oleksii, Kravchun, Nonna, Legun, Oleg, Mankovskyy, Borys, Martynyuk, Liliya, Mostovoy, Yuriy, Pashkovska, Nataliia, Pererva, Larysa, Pertseva, Tetyana, Samoylov, Oleksandr, Smirnov, Ivan, Svyshchenko, Yevgeniya, Tomashkevych, Halyna, Topchii, Ivan, Tryshchuk, Nadiya, Tseluyko, Vira, Vizir, Vadym, Vlasenko, Maryna, Zlova, Tetiana, Zub, Liliia, Abusnana, Salah, Railey, Mohamed, Abouglila, Kamal, Ainsworth, Paul, Ali, Zishan, Arutchelvam, Vijayaraman, Barnard, Maria, Bellary, Srikanth, Davies, Emyr, Davies, Mark, Davies, Simon, Dawson, Alison, El Kossi, Mohsen, English, Patrick, Fraser, Donald, Gnudi, Luigi, Gunstone, Anthony, Hall, Timothy, Hanif, Wasim, Jackson, Alan, Johnson, Andrew, Joseph, Franklin, Krishnan, Singhan, Kumwenda, Mick, MacDougall, Iain, Nixon, Paul, O'Hare, Joseph, Philip, Sam, Ramtoola, Shenaz, Saxena, Manish, Sennik, Davesh, Simon, Godwin, Singh, Baldev, Stephens, Jeffrey, Strzelecka, Anna, Symonds, Rehan, Turner, Wayne, Wahba, Mona, Wakeling, John, Wheeler, David, Winocour, Peter, Abdallah, Joseph, Abdullah, Raied, Abramowitz, Matthew, Acosta, Idalia, Aiello, Joseph, Akright, Laura, Akyea-Djamson, Ayim, Alappan, Rajendran, Alicic, Radica, Al-Karadsheh, Amer, Allison, Dale Crawford, Arauz-Pacheco, Carlos, Arfeen, Shahabul, Arif, Ahmed, Arvind, Moogali, Atray, Naveen, Awad, Ahmed, Barnhill, Peggy, Barranco, Elizabeth, Barrera, Carlos, Beacom, Matthew, Behara, Venkata, Belo, Diogo, Bentley-Lewis, Rhonda, Berenguer, Ramon, Bermudez, Lidia, Bernardo, Marializa, Biscoveanu, Mihaela, Bowman-Stroud, Cynthia, Brandon, Donald, Brusco, Osvaldo, Busch, Robert, Canaan, Yamil, Chilito, Alicia, Christensen, Tom, Christiano, Cynthia, Christofides, Elena, Chuateco, Caroucel, Cohen, Kenneth, Cohen, Robert, Cohen-Stein, Debbie, Cook, Charles, Coyne, Daniel, Daboul, Nizar, Darwish, Riad, Daswani, Adarsh, Deck, Kenneth, Desouza, Cyrus, Dev, Devasmita, Dhillon, Monika, Dua, Sohan, Eder, Frank, Elosegui, Ana Maria, El-Shahawy, Mohamed, Ervin, John, Esquenazi, Alberto, Evans, John, Fishbane, Steven, Frias, Juan, Galindo-Ramos, Eugenia, Galphin, Claude, Ghazi, Adline, Gonzalez, Enrique, Gorson, David, Gowda, Anupama, Greco, Barbara, Grubb, Stephen, Gulati, Rakesh, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Hershon, Kenneth, Hiser, Daniel, Hon, George, Jacob, Radu, Jaime, Maria, Jamal, Aamir, Kaupke, Charles, Keightley, Gerald, Kern, Elizabeth, Khanna, Rakhi, Khitan, Zeid, Kim, Sun, Kopyt, Nelson, Kovesdy, Csaba, Krishna, Gopal, Kropp, Jeffrey (Jay), Kumar, Amrendra, Kumar, Jayant, Kumar, Neil, Kusnir, Jorge, Lane, Wendy, Lawrence, Mary, Lehrner, Lawrence, Lentz, John, Levinson, Dennis, Lewis, Derek, Liss, Kenneth, Maddux, Andreas, Maheshwari, Hiralal, Mandayam, Sreedhar, Marar, Isam, Mehta, Bhasker, Middleton, John, Mordujovich, Jorge, Moreda, Ramon, Moustafa, Moustafa, Trenche, Samuel Mujica, Narayanan, Mohanram, Narvarte, Javier, Nassar, Tareq, Newman, George, Nichol, Brian, Nicol, Philip, Nisnisan, Josier, Nossuli, A. Kaldun, Obialo, Chamberlain, Olelewe, Sarah, Oliver, Michael, O'Shaughnessy, Andrew, Padron, John, Pankhaniya, Rohit, Parker, Reginald, Patel, Devesh, Patel, Gnyandev, Patel, Nina, Pavon, Humberto, Perez, Armando, Perez, Carlos, Perlman, Alan, Pettis, Karlton, Pharr, Walter, Phillips, Andrea, Purighalla, Raman, Quesada-Suarez, Luis, Ranjan, Rajiv, Rastogi, Sanjeev, Reddy, Jakkidi, Rendell, Marc, Rich, Lisa, Robinson, Michael, Rodriguez, Hector, Rosas, Sylvia, Saba, Fadi, Sankaram, Rallabhandi, Sarin, Ravi, Schreiman, Robert, Scott, David, Sekkarie, Mohamed, Sensenbrenner, John, Shakeel, Muhammad, Shanik, Michael, Shaw, Sylvia, Smith, Stephen, Solomon, Richard, Sprague, Amy, Spry, Leslie, Suchinda, Pusadee, Sultan, Senan, Surampudi, Prasanth, Sussman, Sherry, Tan, Anjanette, Terrelonge, Antonio, Thompson, Michael, Trespalacios, Fernando, Trippe, Bruce, Trueba, Pilar, Twahirwa, Marcel, Updegrove, John, Van Buren, Peter, Vannorsdall, Mark, Varghese, Freemu, Velasquez-Mieyer, Pedro, Ventrapragada, Sailaja, Vukotic, Goga, Wadud, Khurram, Warren, Mark, Watson, Henry, Watts, Ronald, Weiner, Daniel, Welker, James, Welsh, Jean, Williams, Shelley, Zaniewski-Singh, Michelle, Yi, Tae Won, Smyth, Brendan, Di Tanna, Gian Luca, Arnott, Clare, Cardoza, Kathryn, and Kang, Amy

Published
2023
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13. Aluminium-Based Metal–Organic Framework Nano Cuboids and Nanoflakes with Embedded Gold Nanoparticles for Carbon Dioxide Fixation with Epoxides into Cyclic Esters

Author

Gabriela Kopacka, Kinga Wasiluk, Pawel W. Majewski, Michał Kopyt, Piotr Kwiatkowski, and Elżbieta Megiel

Subjects
metal–organic frameworks, cyclic carbonates, heterogeneous catalysts, gold nanoparticles, CO2 fixation, epoxides, Biology (General), QH301-705.5, Chemistry, QD1-999
Abstract

The fixation of carbon dioxide with epoxides is one of the most attractive methods for the green utilisation of this greenhouse gas and leads to many valuable chemicals. This process is characterised by 100% atom efficiency; however, an efficient catalyst is required to achieve satisfactory yields. Metal–organic frameworks (MOFs) are recognised as being extremely promising for this purpose. Nevertheless, many of the proposed catalysts are based on ions of rare elements or elements not entirely safe for the environment; this is notable with commercially unavailable ligands. In an effort to develop novel catalysts for CO2 fixation on an industrial scale, we propose novel MOFs, which consist of aluminium ions coordinated with commercially available 1,4-naphthalene dicarboxylic acid (Al@NDC) and their nanocomposites with gold nanoparticles entrapped inside their structure (AlAu@NDC). Due to the application of 4-amino triazole and 5-amino tetrazole as crystallization mediators, the morphology of the synthesised materials can be modified. The introduction of gold nanoparticles (AuNPs) into the structure of the synthesised Al-based MOFs causes the change in morphology from nano cuboids to nanoflakes, simultaneously decreasing their porosity. However, the homogeneity of the nanostructures in the system is preserved. All synthesised MOF materials are highly crystalline, and the simulation of PXRD patterns suggests the same tetragonal crystallographic system for all fabricated nanomaterials. The fabricated materials are proven to be highly efficient catalysts for carbon dioxide cycloaddition with a series of model epoxides: epichlorohydrin; glycidol; styrene oxide; and propylene oxide. Applying the synthesised catalysts enables the reactions to be performed under mild conditions (90 °C; 1 MPa CO2) within a short time and with high conversion and yield (90% conversion of glycidol towards glycerol carbonate with 89% product yield within 2 h). The developed nanocatalysts can be easily separated from the reaction mixture and reused several times (both conversion and yield do not change after five cycles). The excellent performance of the fabricated catalytic materials might be explained by their high microporosity (from 421 m2 g−1 to 735 m2 g−1); many catalytic centres in the structure exhibit Lewis acids’ behaviour, increased capacity for CO2 adsorption, and high stability. The presence of AuNPs in the synthesised nanocatalysts (0.8% w/w) enables the reaction to be performed with a higher yield within a shorter time; this is especially important for less-active epoxides such as propylene oxide (two times higher yield was obtained using a nanocomposite, in comparison with Al-MOF without nanoparticles).

Published
2024
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15. A self-employed taxpayer experimental study on trust, power, and tax compliance in eleven countries

Author

Batrancea, Larissa M., Nichita, Anca, De Agostini, Ruggero, Batista Narcizo, Fabricio, Forte, Denis, de Paiva Neves Mamede, Samuel, Roux-Cesar, Ana Maria, Nedev, Bozhidar, Vitek, Leoš, Pántya, József, Salamzadeh, Aidin, Nduka, Eleanya K., Kudła, Janusz, Kopyt, Mateusz, Pacheco, Luis, Maldonado, Isabel, Isaga, Nsubili, Benk, Serkan, and Budak, Tamer

Published
2022
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16. Frequency of Group A Streptococcus Infection and Analysis of Antibiotic Use in Patients with Pharyngitis—A Retrospective, Multicenter Study.

Author

Biała, Martyna, Babicki, Mateusz, Malchrzak, Wojciech, Janiak, Sandra, Gajowiak, Dominik, Żak, Alan, Kłoda, Karolina, Gibas, Piotr, Ledwoch, Justyna, Myśliwiec, Anna, Kopyt, Daria, Węgrzyn, Anna, Knysz, Brygida, and Leśnik, Patrycja

Subjects
STREPTOCOCCAL diseases, STREPTOCOCCUS pyogenes, MEDICAL records, PRIMARY care, INAPPROPRIATE prescribing (Medicine)
Abstract

Streptococcus pyogenes is responsible for 20–30% of pharyngitis in children and 5–15% in adults. The ineffective treatment of group A Streptococcus (GAS) infections can result in postinfectious sequelae. This study aims to evaluate the frequency of GAS pharyngitis and assess the management of patients with pharyngitis and antibiotic use. We conducted a multicenter, retrospective analysis of medical records from nine primary care centers in Poland. The study enrolled 1949 medical records of patients (children 67.4%, adults 32.6%). An infection of Streptococcus pyogenes, based on a rapid strep test, was diagnosed in 830 patients (42.6%). In the comprehensive study group of 1949 patients, 1054 (54.1%) were given antibiotics. Notably, 224 patients had a negative rapid strep test result but still received antibiotic treatment, underscoring the complexity of treatment decisions. The most commonly used antibiotics were oral penicillin V in 431 cases (41%) and amoxicillin in 219 cases (20.8%). We observed no significant difference between positive rapid strep test results and patients' sociodemographic data and comorbidities. The prevalence of GAS was 42.6% in the analyzed records of patients with pharyngitis, and 54.1% were prescribed antibiotics. Antibiotics were overprescribed for sore throats. Strategies are needed to promote rational antibiotic use. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Short-Term Forecasts of Energy Generation in a Solar Power Plant Using Various Machine Learning Models, along with Ensemble and Hybrid Methods.

Author

Piotrowski, Paweł and Kopyt, Marcin

Subjects
*SOLAR power plants, *MACHINE learning, *SOLAR energy, *PREDICTION models, *METHODS engineering
Abstract

High-quality short-term forecasts of electrical energy generation in solar power plants are crucial in the dynamically developing sector of renewable power generation. This article addresses the issue of selecting appropriate (preferred) methods for forecasting energy generation from a solar power plant within a 15 min time horizon. The effectiveness of various machine learning methods was verified. Additionally, the effectiveness of proprietary ensemble and hybrid methods was proposed and examined. The research also aimed to determine the appropriate sets of input variables for the predictive models. To enhance the performance of the predictive models, proprietary additional input variables (feature engineering) were constructed. The significance of individual input variables was examined depending on the predictive model used. This article concludes with findings and recommendations regarding the preferred predictive methods. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Diagnostic and Therapeutic Challenge Caused by Candida albicans and Aspergillus spp. Infections in a Pediatric Patient as a Complication of Acute Lymphoblastic Leukemia Treatment: A Case Report and Literature Review.

Author

Zaj, Natalia, Kopyt, Weronika, Kamizela, Emilia, Zarychta, Julia, Kowalczyk, Adrian, Lejman, Monika, and Zawitkowska, Joanna

Subjects
CHILD patients, MYCOSES, SYMPTOMS, LYMPHOBLASTIC leukemia, CANDIDIASIS
Abstract

Fungal infections constitute a significant challenge and continue to be a predominant cause of treatment failure in pediatric leukemia cases. Despite the implementation of antifungal prophylaxis, these infections contribute to approximately 20% of cases in children undergoing treatment for acute lymphoblastic leukemia (ALL). The aim of this study is to highlight the diagnostic and therapeutic challenges associated with invasive fungal infections (IFIs). We also present a review of the epidemiology, risk factors, treatment, and a clinical presentation of IFI in patients with ALL. This case report details the clinical course of confirmed Candida albicans (C. albicans) and Aspergillus spp. infections during the consolidation phase of ALL treatment in a 5-year-old pediatric patient. This male patient did not experience any complications until Day 28 of protocol II. Then, the patient's condition deteriorated. Blood culture detected the growth of C. albicans. Despite the implementation of targeted therapy, the boy's condition did not show improvement. The appearance of respiratory symptoms necessitated a computed tomography (CT) of the chest, which revealed multiple nodular densities atypical for C. albicans etiology. In spite of ongoing antifungal treatment, the lesions depicted in the CT scans showed no regression. A lung biopsy ultimately identified Aspergillus species as the source of the infection. Overcoming fungal infections poses a considerable challenge; therefore, an accurate diagnosis and the prompt initiation of targeted therapy are crucial in managing these infections in patients with leukemia. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Outcomes with Finerenone in Participants with Stage 4 CKD and Type 2 Diabetes: A FIDELITY Subgroup Analysis

Author

Sarafidis, Pantelis, Agarwal, Rajiv, Pitt, Bertram, Wanner, Christoph, Filippatos, Gerasimos, Boletis, John, Tuttle, Katherine R., Ruilope, Luis M., Rossing, Peter, Toto, Robert, Anker, Stefan D., Liu, Zhi-Hong, Joseph, Amer, Ahlers, Christiane, Brinker, Meike, Lawatscheck, Robert, Bakris, George, Aizenberg, Diego, Bartolacci, Inés, Besada, Diego, Bittar, Julio, Chahin, Mariano, Elbert, Alicia, Gelersztein, Elizabeth, Liberman, Alberto, Maffei, Laura, Manghi, Federico Pérez, Sanabria, Hugo, Vallejos, Augusto, Viñes, Gloria, Wassermann, Alfredo, Abhayaratna, Walter, Acharya, Shamasunder, Ekinci, Elif, Lee, Darren, MacIsaac, Richard, Mah, Peak Mann, Nelson, Craig, Packham, David, Pape, Alexia, Roger, Simon, Stephenson, Hugo, Suranyi, Michael, Wittert, Gary, Vale, Elizabeth, Colman, Peter, Colquhoun, David, Ellis, Chris, Joshua, Kim, Pedagogos, Eugenia, Regal, Paul, Topliss, Duncan, Vandeleur, James, Verjans, Johan, Wittert, Gary, Wynne, Katie-Jane, Clodi, Martin, Ebenbichler, Christoph, Fliesser-Görzer, Evelyn, Hanusch, Ursula, Krebs, Michael, Lhotta, Karl, Ludvik, Bernhard, Mayer, Gert, Neudorfer, Peter, Paulweber, Bernhard, Prager, Rudolf, Preiß, Wolfgang, Prischl, Friedrich, Schernthaner, Gerit-Holger, Sourij, Harald, Wiesholzer, Martin, Drexel, Heinz, Oberbauer, Rainer, Schönherr, Hans-Robert, Doubel, Peter, Engelen, Wendy, Gillard, Pieter, Hougardy, Jean-Michel, Krzesinski, Jean-Marie, Maes, Bart, Speeckaert, Marijn, Stas, Koen, van Gaal, Luc, Vanbelleghem, Hilde, Duyck, Francis, Scheen, André, Antunes, Daniela, Botelho, Roberto, Brito, Claudia, Canani, Luis, Canziani, Maria Eugenia, Cerqueira, Maria, de Paula, Rogerio, Eliaschewitz, Freddy, Figueiredo, Carlos Eduardo, Forti, Adriana, Hissa, Miguel, Leite, Emerson Lima Maurilo, Jr, Noronha, Irene, Paolino, Bruno, Paschoalin, Nathalia, Paschoalin, Raphael, Filho, Roberto Pecoits, Pereira, Marcio, Portes, Evandro, Precoma, Dalton, Rea, Rosangela, Riella, Miguel, Salles, Joao Eduardo, Vasconcellos, Eduardo, Vencio, Sergio, Bacci, Marcelo, Maia, Lilia, Villacorta, Aline, Apostolova, Emiliya, Boshnyashka, Radostina, Farah, Ghassan, Georgiev, Dimitar, Gushterova, Valentina, Klyuchkova, Neli, Lucheva, Mariya, Manova, Petya, Minkova, Dotska, Nonchev, Boyan, Pichmanova, Mariyana, Prakova, Zhulieta, Rangelov, Rangel, Rashkov, Rosen, Stanchev, Pavel, Stoyanovska-Elencheva, Bilyana, Tagarev, Zhivko, Temelkova-Kurktschieva, Theodora, Vasileva, Svetla, Yoncheva-Mihaylova, Mariana, Marinchev, Angel, Miteva, Mariya, Barre, Paul, Carlson, Brian, Conway, James, Cournoyer, Serge, Dumas, Richard, Fikry, Sameh, Goluch, Richard, Hamet, Pavel, Hart, Randolph, Henein, Sam, Liutkus, Joanne, Madore, Francois, Martinho, Valdemar, Mazza, Giuseppe, McFarlane, Philip, Keefe, Dennis O′, Peterson, Sean, Schwartz, Daniel, Shu, Daniel, Steele, Andrew, Tellier, Guy, Tennankore, Karthik, Tobe, Sheldon, Tsoukas, George, Tytus, Richard, Vitou, Louise, Walsh, Michael, Weisnagel, Stanley, Wilderman, Igor, Yale, Jean-Francois, El Boreky, Fadia, Kelly, Alan, Leiter, Lawrence, Teitelbaum, Ivor, Cobos, Jorge, Godoy, Juan, González, Fernando, Lobos, Sergio, Palma, Juan Carlos, Prieto Dominguez, Juan Carlos, Reyes, Eliana, Romero, Carmen, Saavedra, Victor, Vega, Mario, Medina, Marcelo, Varleta, Paola, Bu, Ruifang, Cai, Hanqing, Chen, Nan, Chen, Qinkai, Chen, Dejun, Cheng, Jinluo, Dong, Youping, Dong, Junwu, Guan, Tianjun, Hao, Chuanming, Huang, Wen, Jiang, Fangfang, Lei, Minxiang, Li, Ling, Li, Zhonghe, Li, Xuemei, Li, Jingmei, Li, Yan, Liang, Xinling, Liang, Bo, Liu, Fang, Liu, Yinghong, Liu, Yuantao, Liu, Zhihong, Long, Gang, Lu, Guoyuan, Lu, Weiping, Lu, Yibing, Luo, Ping, Ma, Jianhua, Mo, Zhaohui, Niu, Jianying, Peng, Ai, Shen, Jiansong, Shen, Feixia, Shi, Bingyin, Su, Qing, Sun, Zhuxing, Tang, Shuifu, Tong, Nanwei, Wang, Hao, Wang, Xinjun, Wang, Guixia, Wang, Jianqin, Wang, Yangang, Wang, Li, Wei, Jiali, Wu, Tianfeng, Wu, Chaoqing, Xing, Changying, Xiong, Fei, Xu, Xudong, Xu, Ning, Yan, Tiekun, Yang, Jinkui, Yin, Aiping, Zeng, Longyi, Zhang, Hao, Zhang, Yanlin, Zhang, Ying, Zhao, Wenjing, Zhao, Zhiquan, Zheng, Hongguang, Zhong, Ling, Zhu, Dalong, Zhuang, Yongze, Du, Yuming, Fang, Yi, Guo, Weiying, Jiang, Sheng, Kuang, Jian, Li, Dongmei, Li, Hongmei, Li, Yinan, Li, Yuxiu, Liu, Jian, Liu, Yu, Miao, Heng, Peng, Wen, Wang, Lihua, Xu, Mingtong, Zhong, Liyong, Zhu, Jun, Arango, Clara, Barrera, Sandra, López, Nelly Beltrán, Benitez, Diego, Blanco, Guillermo, Cadena, Andrés, Coronel, Julian, Cure, Carlos, Durán, Carlos, González, Alexander, Guzmán, Gustavo, Hernández, Eric, Ibarra, Jaime, Jaramillo, Carlos, Jaramillo, Nicolás, Kattah, William, Molina, Dora, Sánchez, Gregorio, Terront, Mónica, Trujillo, Freddy, Urina, Miguel, Vargas, Ruben, Villegas, Iván, Yupanqui, Hernán, Arcos, Edgar, Aroca, Gustavo, Barreto, Germán, Bermudez, Andres, Botero, Rodrigo, Cárdenas, Tatiana, Figueroa, Wilmer, Jaramillo, Mónica, Liévano, Manuel, López, Mónica, Molina, Dora, Rosero, Ricardo, Trillos, Pedro, Dino Alferi, Brada, Michal, Brezina, Jiri, Bucek, Petr, Edelsberger, Tomas, Gulakova, Drahomira, Zapletalova, Jitka Hasalova, Hola, Olga, Hornova, Lucie, Houdova, Jana, Hrmova, Helena, Karasek, David, Kopecka, Sarka, Kovar, Richard, Krcova, Eva, Kuchar, Jiri, Kutejova, Vlasta, Lubanda, Hana, Matyasek, Ivo, Mokrejsova, Magdalena, Okenka, Libor, Prazny, Martin, Pumprla, Jiri, Tomanek, Pavel, Andersen, Ulla, Andries, Alin, Bech, Jesper, Faber, Jens, Gislason, Gunnar, Hangaard, Jørgen, Pacyk, Grzegorz Jaroslaw, Juhl, Claus, Krarup, Thure, Lindhardt, Morten, Madsbad, Sten, Nielsen, Joan, Pedersen-Bjergaard, Ulrik, Poulsen, Per, Rasmussen, Ole, Rossing, Peter, Schousboe, Karoline, Gram, Jeppe, Lauridsen, Thomas, Pedersen, Erling, Thorsteinsson, Birger, Flöjt, Päivi, Honkasalo, Mikko, Honkasalo, Mikko, Humaloja, Kari, Kananen, Kristiina, Kantola, Ilkka, Koistinen, Arvo, Korsoff, Pirkko, Lahtela, Jorma, Nieminen, Sakari, Nieminen, Tuomo, Sadeharju, Karita, Strand, Jorma, Sulosaari, Sakari, Cariou, Bertrand, Chantrel, François, Clavel, Sylvaine, Combe, Christian, Fauvel, Jean-Pierre, Gallouj, Karim, Gouet, Didier, Guerci, Bruno, Guerrot, Dominique, Hourmant, Maryvonne, Klein, Alexandre, Mariat, Christophe, Marre, Michel, Mesbah, Rafik, Le Meur, Yannick, Monier, Arnaud, Moranne, Olivier, Roussel, Ronan, Serusclat, Pierre, Vendrely, Benoit, Verges, Bruno, Zaoui, Philippe, Axthelm, Christoph, Bergmann, Andreas, Birkenfeld, Andreas L., Braun, Hermann, Busch, Klaus, Contzen, Christel, Degenhardt, Stefan, Derwahl, Karl, Giebel, Thomas, Hagenow, Andreas, Haller, Hermann, Hasslacher, Christoph, Horacek, Thomas, Jungmair, Wolfgang, Kloos, Christof, Koch, Thorsten, Krüger, Thilo, Mühlfeld, Anja, Müller, Joachim, Pfützner, Andreas, Pistrosch, Frank, Rinke, Andrea, Rose, Ludger, Rump, Lars, Schettler, Volker, Schiefke, Ingolf, Schlichthaar, Heike, Schröppel, Bernd, Schöll, Norbert, Schubert, Kristin, Schürholz, Thomas, Sigal, Helena, Stemler, Lutz, Strack, Georg, Täschner, Heidrun, Toursarkissian, Nicole, Tschöpe, Diethelm, Ulmer, Achim, van der Giet, Markus, Wanner, Christoph, Winkelmann, Bernhard R., Boletis, Ioannis, Dimitriadis, George, Hatziagelaki, Erifili, Iatrou, Christos, Ioannidis, Ioannis, Kounadi, Theodora, Makriniotou, Ioanna, Papadopoulou, Dorothea, Papagianni, Aikaterini, Passadakis, Ploumis, Piaditis, George, Stefanidis, Ioannis, Tai Pang Ip, Lee, Paul, Andrea Luk, On Yan, Ma, Ronald, Chow, Wing Sun, Wang, Angela, Yeung, Vincent, Bajcsi, Dora, Danos, Peter, Harcsa, Eleonora, Kalina, Akos, Kazup, Szilvia, Keltai, Katalin, Kirschner, Robert, Kiss, Julianna, Kovacs, Laszlo, Lamboy, Beata, Literati-Nagy, Botond, Mileder, Margit, Nagy, Laszlo, Noori, Ebrahim, Nyirati, Gabor, Petro, Gizella, Schneider, Karoly, Simon, Judit, Szocs, Albert, Vasas, Szilard, Wudi, Krisztina, Zilahi, Zsolt, Zsom, Marianna, Eustace, Joe, Holian, John, Reddan, Donal, Meara, Yvonne O′, Abramof Ness, Rosane, Adawi, Faiad, Armaly, Zaher, Atar, Shaul, Bashkin, Amir, Ben Chetrit, Sydney, Yanay, Noa Berar, Chernin, Gil, Darawsha, Mahmud, Efrati, Shai, Elias, Mazen, Farber, Evgeny, Glandt, Mariela, Grossman, Ehud, Halabi, Majdi, Harman-Boehm, Ilana, Khazim, Khaled, Liberty, Idit, Minuchin, Oscar, Mosenzon, Ofri, Nakhoul, Farid, Nimer, Assy, Schwartz, Doron, Wainstein, Julio, Yagil, Yoram, Zukermann, Robert, Avogaro, Angelo, Battaglia, Giovanni Giorgio, Bevilacqua, Maurizio Tiziano, Bonora, Enzo, Bossi, Carlo Antonio, Calabrò, Paolo, Cavalot, Franco Luigi, Cimino, Roberto, Cozzolino, Mario Gennaro, David, Salvatore, Emdin, Michele, Fiaccadori, Enrico, Fiorina, Paolo, Giorda, Carlo Bruno, Gregorini, Maria Cristina, La Manna, Gaetano, Maggi, Davide Carlo, Manti, Roberta, Meregalli, Giancarla, Pani, Antonello, Parvanova, Aneliy Ilieva, Perico, Norberto, Piatti, PierMarco, Pisani, Antonio, Pontiroli, Antonio Ettore, Ponzani, Paola, Santorelli, Gennaro, Santoro, Domenico, Scanziani, Renzo, Teatini, Ugo, Tonolo, Giancarlo, Trevisan, Roberto, Veronelli, Anna Maria, Viviani, Giorgio Luciano, Araki, Hideo, Bando, Yukihiro, Ebisui, Osamu, Fujita, Naruhiro, Fukasawa, Hirotaka, Furuya, Ryuichi, Hamamoto, Yoshiyuki, Hamasaki, Akihiro, Hasegawa, Kotaro, Hatazaki, Masahiro, Hayashi, Terumasa, Higashi, Takayuki, Hirohata, Yoshihide, Horinouchi, Shuji, Hoshi, Ayumu, Imoto, Hirofumi, Inagaki, Akemi, Inagaki, Masayuki, Inaguma, Daijo, Inoue, Toshihiko, Ishii, Masao, Ishiko, Tamayo, Isono, Motohide, Jinnouchi, Hideaki, Kanai, Hidetoshi, Kanda, Daisuke, Kanehara, Hideo, Kashima, Masayuki, Kataoka, Yuko, Katayama, Shigehiro, Kato, Kiyoe, Katsuki, Takeshi, Kawamitsu, Katsunori, Kawasaki, Satsuki, Kikuchi, Fumi, Kikuchi, Hidetoshi, Kishimoto, Rui, Kobayashi, Kunihisa, Koide, Junko, Komi, Rieko, Kubota, Miyuki, Kuriya, Genpei, Kurose, Takeshi, Kusano, Yoshiro, Hajime, Maeda, Matsubayashi, Sunao, Matsumoto, Kazunari, Matsumura, Naoya, Matsuo, Yasuto, Matsuoka, Naoki, Miyaoka, Hiroaki, Miyata, Satoshi, Morita, Takeshi, Murakami, Isao, Murao, Satoshi, Nakamura, Udai, Nakayama, Mikihiro, Nakazawa, Jun, Nohara, Sakae, Nomiyama, Takashi, Noritake, Masayuki, Oda, Yoshiaki, Ogiwara, Takayuki, Ohashi, Hiroshi, Okamoto, Hideki, Okino, Shinichi, Osonoi, Takeshi, Sasaki, Nobuhiro, Sayo, Yoshitaka, Sekigami, Taiji, Shibasaki, Taro, Shibata, Hirotaka, Shimoyama, Tatsushi, Shinoda, Junji, Sobajima, Hiroshi, Sugitatsu, Kazuya, Sugiura, Toshiyuki, Sugiyama, Toru, Suzuki, Daisuke, Suzuki, Hiroyuki, Suzuki, Masaaki, Takeda, Asami, Tanaka, Asami, Tanaka, Seiichi, Tsunematsu, Izumi, Ueda, Yasuo, Uekihara, Soichi, Ujihara, Makoto, Yajima, Ken, Yamada, Daishiro, Yamada, Masayo, Yamagata, Kazuo, Yamakawa, Ken, Yamakawa, Fumiko, Yamasaki, Yoshimitsu, Yambe, Yuko, Yanagida, Taihei, Yanai, Hidekatsu, Yanase, Toshihiko, Yasuda, Tetsuyuki, Kriauciuniene, Dovile, Lasiene, Jurate, Navickas, Antanas, Radzeviciene, Lina, Urbanaviciene, Egle, Urbonas, Gediminas, Velaviciene, Audrone, Abd Ghani, Rohana, Aziz, Nor Azizah, Lee, Li Yuan, Loh, Chek Loong, Ali, Norhaliza Mohd, Noor, Nurain Mohd, Fatnoon Nik Ahmad, Nik Nur, Ratnasingam, Jeyakantha, Halimi Bin Wan Hasan, Wan Hasnul, Izani Wan Mohamed, Wan Mohd, Khir, Rizmy Najme, Mohamad, Masni, Alexander Tan, Tong Boon, Avila Pardo, Sandro, Adrian, Miriam Bastidas, Wong, Alfredo Chew, Escobedo de la Peña, Jorge, Salmón, Guillermo Fanghänel, Gálvez, Guillermo González, Ochoa, Ramiro Gutiérrez, Santana, Saúl Irizar, Rovalo, Magdalena Madero, Machado, Gustavo Méndez, Ruiz, Luis Nevarez, Ibarra, Denisse Ramos, López, Gabriel Ramos, Reyna, Leobardo Sauque, Ortiz, Gustavo Solache, Ortiz, Rafael Valdez, Mesa, Juan Villagordoa, Salazar, Melchor Alpizar, Hernández, Pedro García, González, José, Soto, José Lazcano, Mendoza, Arturo Saldaña, Santana, Sergio Irizar, Vilchis, Elvira González, Bakker, R.C., Barendregt, J.N.M., Boonstra, A.H., Bos, Willem, Brouwer, C.B., Buren, M. van, Gansevoort, Ron, Kooy, Adriaan, Krekels, Marielle, Leendert, Ruud J.M. van, Lieverse, Louis A.G., Luik, P.T., Penne, E. Lars, Gregoor, Peter Smak, Vogt, Liffert, Born, Bert-Jan van den, John Baker, Crawford, Veronica, Cutfield, Rick, Dunn, Peter, Krebs, Jeremy, Nirmalaraj, Kingsley, Scott, Russell, Smuts, Nine, Titchener, Janet, Eriksen, Erik, Finnes, Trine, Høivik, Hans, Karlsson, Thomas, Munk, Peter Scott, Radtke, Maria, Risberg, Knut, Rocke, Jan, Solnør, Leidulv, Stenehjem, Aud-Eldrid, Tafjord, Anne-Beathe, Asprusten, Emil, Hagemeier, Robert, Høye, Kjetil, Selsås, Hilde, Thorup, Frode, Wium, Cecilie, Pamugas, Glenda, Panelo, Araceli, Perez, Ronald, Tanque, Maribel, Tirador, Louie, Villa, Michael, Bautista, Albert, Catindig, Elizabeth, Manalo, Carlo, Mirasol, Roberto, Butrymowicz, Patrycja, Ciechanowski, Kazimierz, Cieslik, Grazyna, Franek, Edward, Gumprecht, Janusz, Hoffmann, Michal, Krzykowska, Jolanta, Kurnatowska, Ilona, Landa, Katarzyna, Madrzejewski, Adam, Madziarska, Katarzyna, Mazur, Stanislaw, Napora, Piotr, Nowicki, Michal, Ocicka-Kozakiewicz, Anna, Rewerska, Barbara, Rusicka, Teresa, Ruxer, Jan, Skokowska, Ewa, Stankiewicz, Andrzej, Stompor, Tomasz, Tiuryn-Petrulewicz, Agnieszka, Wasilewska, Katarzyna, Wierusz-Wysocka, Bogna, Wnetrzak-Michalska, Renata, Jedynasty, Krystyna, Anand, Izabela Sein, Almeida, Edgar, Ballesteros, Rosa, Barreto, Carlos, Beirao, Idalina, Birne, Rita, Esteves, Cesar, Guia, Jose, Heitor, Susana, Marques, Olinda, Melo, Pedro, Nolasco, Fernando, Pereira, Amalia, Roque, Cristina, Rosario, Francisco, Silva, Gil, Silva, Ana, Teixeira e Costa, Fernando, Lobos, Ana Vila, Alves, Ana Rita, Brandao, Ilidio, Carvalho, Rui, Coelho, Joao, Lourenco, Ana, Matos, Pedro, Rosario, Vanisa, Neves, Joao Sergio, Cortes-Maisonet, Gregorio, Roman-Miranda, Amaury, Brito-Peguero, Yudit, Colon-Vega, Gildred, Albota, Adrian, Bala, Cornelia, Barbonta, Hortensia, Caceaune, Elena, Catrinoui, Doina, Constantin, Ciprian, Dumitrescu, Adriana, Mindrescu, Nicoleta, Mistode, Cristina, Negrisanu, Gabriela, Onaca, Adriana, Paveliu, Silvia, Pintilei, Ella, Pop, Lavinia, Popa, Amorin, Popescu, Alexandrina, Radulian, Gabriela, Szilagyi, Iosif, Turcu, Liana, Vacaru, Georgeta, Vlad, Adrian, Filimon, Adriana, Veresiu, Ioan, Antsiferov, Mikhail, Arkhipov, Mikhail, Babkin, Andrey, Barbarash, Olga, Baranov, Vitaliy, Chernyavskaya, Elena, Demko, Arkadiy, Dreval, Alexander, Edin, Anton, Ermakova, Polina, Fadeev, Valentin, Galyavich, Albert, Gaysina, Leyla, Gordeev, Ivan, Ipatko, Irina, Kalashnikova, Marina, Khalimov, Yuriy, Klimontov, Vadim, Kobalava, Zhanna, Kosmacheva, Elena, Koziolova, Natalya, Sergey Levashov, Lyudmila Kvitkova, Libis, Roman, Marasaev, Vyacheslav, Malykh, Natalia, Martynenko, Vladimir, Malyutina, Sofya, Merai, Imad, Mkrtumyan, Ashot, Nechaeva, Galina, Petunina, Nina, Palyutin, Shamil, Pimenov, Leonid, Rechkova, Elena, Rodionova, Tatyana, Rymar, Oksana, Sardinov, Ruslan, Semenova, Olga, Sherenkov, Alexander, Solovev, Oleg, Smolyarchuk, Elena, Strongin, Leonid, Ukhanova, Olga, Verlan, Nadezhda, Vorokhobina, Natalya, Yakhontov, Davyd, Yakushin, Sergey, Zakharova, Elena, Zalevskaya, Alsu, Zanozina, Olga, Zhdanova, Elena, Zhukova, Larisa, Zykova, Tatyana, Argunova, Yulia, Nikolaev, Konstantin, Villevalde, Svetlana, Fang Sum, Chee, Suhail, Sufi Muhummad, San Tan, Ru, Vathsala, Anantharaman, Wong, Edmund, Bee, Yong Mong, Babikova, Jana, Buganova, Ingrid, Dzupina, Andrej, Ochodnicka, Zuzana, Sosovec, Dalibor, Spodniakova, Denisa, Minarik, Peter, Fayzal Ahmed, Amod, Aslam, Bhana, Sindeep, Distiller, Larry, Jansen van Rensburg, Dirkie, Joshi, Mukesh, Joshi, Shaifali, Lakha, Deepak, Mitha, Essack, Podgorski, Gracjan, Ranjith, Naresh, Rayner, Brian, Rheeder, Paul, Sarvan, Mohamed, Seeber, Mary, Siebert, Heidi, Tayob, Mohammed, Trokis, Julien, Urbach, Dorothea, van Zyl, Louis, Jansen van Rensburg, Dirkie, Bum-Soon Choi, Choi, Moon Gi, Chung, ChoonHee, Hwang, YouCheol, Kim, ChongHwa, Kim, InJoo, Kim, JaeHyeon, Kim, SinGon, Kim, SungGyun, Kim, Tae Hee, Lee, WooJe, Lee, ByungWan, Lee, Kang Wook, Oh, Kook-Hwan, Oh, Ji Eun, Oh, Yun Kyu, Oh, Dong-Jin, Park, Junbeom, Shin, Seok Joon, Sung, Su-Ah, Yu, Jae Myung, Chung, HyeSoo, Huh, Ji Hye, Kang, JunGoo, Kim, ChulSik, Kim, HyeSoon, Kim, NamHoon, Lim, Soo, Cho, Young Min, Park, Cheol Young, Agraz, Irene, Ampudia, Francisco Javier, Bouarich, Hanane, Calero, Francesca, Castro, Cristina, Guldris, Secundino Cigarrán, Garrit, Josep Cruzado, de Álvaro, Fernando, Galcerán, Josep, Albarrán, Olga González, Jaras, Julio Hernández, Ibernón, Meritxell, Deben, Francisco Martínez, Ma, Esteban, Dolores Martínez, Pascual Izuel, José María, Martins, Judith, Mediavilla, Juan, Michán, Alfredo, Santos, Julio Pascual, Poch, Esteban, Rusillo, Manuel Polaina, Juan, Carlos Sánchez, Olmo, Rafael Santamaría, Segura de la Morena, José Julián, Soto, Alfonso, Troya, Maribel, Castro, Fernando Cereto, Fernández, Pablo Gómez, Sánchez, Laura Fuentes, Moya, Mercedes González, Marrero, Domingo Hernández, Maroto, Gonzalo Piedrola, Redón, Josep, Seron, Daniel, Bruchfeld, Annette, Curiac, Dan, Eliasson, Ken, Frank, Malin, Guron, Gregor, Hellberg, Olof, Hellgren, Margareta, Larnefeldt, Hans, Lindholm, Carl-Johan, Löndahl, Magnus, Rein-Hedin, Erik, Soveri, Inga, Spaak, Jonas, Tengmark, Bengt-Olov, Lif-Tiberg, Cornelia, Månflod, Johan, Nguyen, Han, Ackermann, Daniel, Bilz, Stefan, Burnier, Michel, Forster, Christian, Kalbermatter, Stefan, Kistler, Andreas, Pechère-Bertschi, Antoinette, Schultes, Bernd, Laimer, Markus, Rudofsky, Gottfried, Strey, Christopher, Wuerzner, Gregoire, Chiz-Tzung Chang, Hung, Cheng-Chieh, Jiang, Ju-Ying, Lee, Chien-Te, Lin, Shuei-Liong, Tarng, Der-Cherng, Tu, Shih-Te, Wu, Mai-Szu, Wu, Ming-Ju, Chuang, Lee-Ming, Deerochanawong, Chaicharn, Kitiyakara, Chagriya, Ophascharoensuk, Vuddhidej, Pongchaiyakul, Chatlert, Satirapoj, Bancha, Kosachunhanan, Natapong, Sritara, Piyamitr, Eren, Necmi, Gul, Ibrahim, Gulel, Okan, Kocyigit, Ismail, Kumbasar, Abdulbaki, Sahin, Idris, Sari, Ramazan, Sayin, Burak, Tavli, Talat, Ustundag, Sedat, Yenicerioglu, Yavuz, Badak, Ozer, Cayli, Murat, Oguz, Aytekin, Ozdogan, Oner, Sari, Ibrahim, Temizhan, Ahmet, Tigen, Mustafa, Turk, Ugur, Yilmaz, Huseyin, Yilmaz, Mehmet, Bondarets, Iryna, Botsyurko, Volodymyr, Chernikova, Viktoriia, Donets, Oleksandra, Fushtey, Ivan, Grachova, Mariia, Isayeva, Anna, Kogut, Dmytro, Komisarenko, Julia, Kravchun, Nonna, Malyar, Kateryna, Mankovsky, Borys, Martynyuk, Liliya, Maslyanko, Vitaliy, Myshanych, Halyna, Pererva, Larysa, Pertseva, Nataliia, Serhiyenko, Oleksandr, Smirnov, Ivan, Sokolova, Liubov, Stryzhak, Vasyl, Vlasenko, Maryna, Isayeva, Ganna, Larin, Oleksandr, Ahmad AbouSaleh, Barratt, Jonathan, Dang, Cuong, Kahal, Hassan, Kirk, Adam, Kilvert, Anne, Kon, Sui Phi, McCafferty, Kieran, Patel, Dipesh, Rice, Sam, Vijayaraman, Arutchelvam, Wong, Yuk-ki, Gibson, Martin, Wahba, Mona, Zaidi, Reza, Bilous, Rudy, Johnson, Andrew, Kalathil, Dhanya, Kilvert, Anne, Kyriakidou, Christina, Mathew, Amit, Mukhtar, Rasha, Munsoor, Imrozia, Poterajlo, Anton, Swift, Pauline, Idalia Acosta, Adams, Atoya, Adler, Sharon, Ajani, Dilawar, Ali, Slamat, Alicic, Radica, Al-Karadsheh, Amer, Alla, Sreedhara, Allison, D., Andrawis, Nabil, Arif, Ahmed, Awad, Ahmed, Azizad, Masoud, Bahrami, Michael, Bansal, Shweta, Barag, Steven, Barakzoy, Ahmad, Barney, Mark, Barzilay, Joshua, Bashir, Khalid, Bautista, Jose, Beddhu, Srinivasan, Belo, Diogo, Benjamin, Sabrina, Berenji, Ramin, Bhargava, Anuj, Birriel, Jose, Brietzke, Stephen, Brosius, Frank, Brusco, Osvaldo, Burgner, Anna, Busch, Robert, Canadas, Rafael, Caramori, Maria, Cardona, Jose, Case, Christopher, Cruz, Humberto, Dandillaya, Ramprasad, Dawoud, Dalia, Din, Zia, Dixon, Bradley, Doshi, Ankur, Drakakis, James, El Shahawy, Mahfouz, El-Meanawy, Ashraf, El-Shahawy, Mohammed, Evans, John, Fadda, George, Farooq, Umar, Fernando, Roland, Fink, Raymond, First, Brian, Fitz-Patrick, David, Flack, John, Fluck, Patrick, Fogelfeld, Leon, Fonseca, Vivian, Frias, Juan, Galphin, Claude, Garcia-Mayol, Luis, Goldstein, Gary, Gonzalez, Edgar, Gonzalez-Abreu, Francisco, Gore, Ashwini, Grant, David, Habwe, Violet, Hamilton, Maxine, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Heigerick, Glenn, Henry, Andrew, Hernandez, German, Hernandez-Cassis, Carlos, Herrera, Carlos, Hertel, Joachim, Huang, Wenyu, Iglesias, Rogelio, Iranmanesh, Ali, Jackson, Timothy, Jain, Mahendra, Jamerson, Kenneth, Johnson, Karen, Judd, Eric, Kaplan, Joshua, Kayali, Zeid, Khan, Bobby, Khan, Muhammad, Kharait, Sourabh, Kirkman, M. Sue, Kopyt, Nelson, Kotzker, Wayne, Kovesdy, Csaba, Kreit, Camil, Krishna, Arvind, Kronfli, Saeed, Lee, Keung, LeJeune, Derek, Lemus, Brenda, Leon-Forero, Carlos, Linfert, Douglas, Lora, Henry, Lurie, Alexander, Maddukuri, Geetha, Magno, Alexander, Maletz, Louis, Mandayam, Sreedhar, Markell, Mariana, Mayfield, Ronald, Mbogua, Caroline, McMullen, Dierdre, Meisner, Carl, Minton, Stephen, Mocherla, Bharat, Mohandas, Rajesh, Montero, Manuel, Moustafa, Moustafa, Nadkarni, Salil, Nakhle, Samer, Navarro, Jesus, Neyra, Nilda, Nica, Romanita, Nicol, Philip, Norwood, Paul, Numrungroad, Visal, Donovan, Richard O′, Odugbesan, A., Paoli-Bruno, Jorge, Parikh, Samir, Patel, Rakesh, Peixoto, Aldo, Pergola, Pablo, Perlman, Alan, Pettis, Karlton, Pisoni, Roberto, Ponduchi, Mirela, Posada, Jorge, Prabhakar, Sharma, Radhakrishnan, Jai, Rahman, Mahboob, Raina, Rupesh, Rastogi, Anjay, Reisin, Efrain, Rendell, Marc, Robertson, David, Rocco, Michael, Romeu, Hugo, Rosas, Sylvia, Rosenfeld, Jack, Ross, Dennis, Rothman, Jeffrey, Rudolph, Lance, Ruhullah, Yusuf, Ruoff, Gary, Ryu, Jeffrey, Sahani, Mandeep, Sam, Ramin, Samuels, Garfield, Sanchez, William, Santos, Vladimir, Satko, Scott, Saxena, Sanjeev, Scott, David, Seco, Gilberto, Seek, Melvin, Serota, Harvey, Shafi, Tariq, Shahid, Nauman, Shanik, Michael, Sharma, Santosh, Sinha, Arjun, Smelser, James, Smith, Mark, Soe, Kyaw, Solomon, Richard, Soroka, Eugene, Soufer, Joseph, Spinowitz, Bruce, Spry, Leslie, Suarez, Rosa, Subramanian, Bala, Szerlip, Harold, Tamirisa, Aparna, Thomson, Stephen, Tran, Tuan-Huy, Treger, Richard, Trullenque, Gretel, Turk, Thomas, Umpierrez, Guillermo, Urbach, Daniel, Valdes, Martin, Valika, Shujauddin, Vega, Damaris, Weissman, Peter, Whaley-Connell, Adam, Winston, Jonathan, Wise, Jonathan, Wynne, Alan, Zeig, Steven, Abdel-Rahman, Emaad, Abreu, Edel, Awad, Alaa, Bahri, Nader, Bertsch, John, Bleich, David, Bornfreund, Jonathan, Brar, Harjeet, Brian, Susan, Brinson, Cynthia, Bruschetta, Humberto, Carpio, Jose, Cohen, Steven, Cosby, John, Dhanireddy, Soni, Diaz, Jorge, Dunn, Fredrick, Eppanapally, Sabitha, Fayad, Joseph, Goel, Archana, Govindaraju, Kanakadurga, Halpern, Stephen, Jones, Audrey, Kaye, William, Knight, Herbert, Koch, Stanley, Kohli, Nandini, Lastra, Guido, Lerman, Sam, Loredo, Jorge, Lovre, Dragana, Mandviwala, Mustafa, Martin, Earl, Meyer, Jill, Murray, John, Oliver, David, Oparil, Suzanne, Penabad, Jesus, Pereira, Isabel, Popeil, Larry, Quesada, Gonzalo, Ramanathan, Kodangudi, Ramos-Gonez, Luis, Rastegar, Mandana, Rastogi, Padmashri, Rondon, Juan, Roy-Chaudhury, Prabir, Smith, David, Williamson, Don, Womack, Catherine, Yamout, Hala, Yuryev, Michael, Chu, Phuong, Van Hoang, Lam, Khanh, Tran, Phi Nga, Nguyen Thi, Son, Pham Nguyen, Tran, Lan Phuong, Le, Thuy Khuong, Nguyen, Boi Ngoc, Nguyen, Thao, Nui, Nguyen Minh, Nam, Tran Quang, and Tran, Kim Chi

Published
2023
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20. Pharmacological effects of ex vivo mesenchymal stem cell immunotherapy in patients with acute kidney injury and underlying systemic inflammation

Author

Madhav Swaminathan, Nelson Kopyt, Mohamed G. Atta, Jai Radhakrishnan, Kausik Umanath, Sunny Nguyen, Brian O'Rourke, Ashley Allen, Natalie Vaninov, Arno Tilles, Elizabeth LaPointe, Andrew Blair, Chris Gemmiti, Brian Miller, Biju Parekkadan, and Rita N. Barcia

Subjects
adult stem cells, cellular therapy, clinical trials, cytokines, immunotherapy, lymphocytes, Medicine (General), R5-920, Cytology, QH573-671
Abstract

Abstract Mesenchymal stem cells (MSCs) have natural immunoregulatory functions that have been explored for medicinal use as a cell therapy with limited success. A phase Ib study was conducted to evaluate the safety and immunoregulatory mechanism of action of MSCs using a novel ex vivo product (SBI‐101) to preserve cell activity in patients with severe acute kidney injury. Pharmacological data demonstrated MSC‐secreted factor activity that was associated with anti‐inflammatory signatures in the molecular and cellular profiling of patient blood. Systems biology analysis captured multicompartment effects consistent with immune reprogramming and kidney tissue repair. Although the study was not powered for clinical efficacy, these results are supportive of the therapeutic hypothesis, namely, that treatment with SBI‐101 elicits an immunotherapeutic response that triggers an accelerated phenotypic switch from tissue injury to tissue repair. Ex vivo administration of MSCs, with increased power of testing, is a potential new biological delivery paradigm that assures sustained MSC activity and immunomodulation.

Published
2021
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22. Digital Energy Path for Planning and Operation of the sustainable grid, products and society – project objectives and selected preliminary results in Polish conditions.

Author

ROKICKI, Łukasz, PAROL, Mirosław, PIOTROWSKI, Paweł, KOPYT, Marcin, DOMASZEWSKI, Jakub, ARENDARSKI, Bartłomiej, and KOMARNICKI, Przemysław

Subjects
ELECTRIC power systems, ELECTRIC power production, STATISTICAL measurement, ELECTRIC power failures, DEMAND forecasting, ENERGY consumption, ELECTRIC power
Abstract

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny 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
2024
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24. Randomized Controlled Trial of Difelikefalin for Chronic Pruritus in Hemodialysis Patients

Author

Steven Fishbane, Vandana Mathur, Michael J. Germain, Shayan Shirazian, Sarbani Bhaduri, Catherine Munera, Robert H. Spencer, Frédérique Menzaghi, Michael Aaronson, Kelly Alford, Ahmed Awad, Premila Bhat, Varshab Broumand, Wesley Calhoun, Riad Darwish, Sohan Dua, Carl Dukes, Ayodele Erinle, Alexander Hadley, John Hsieh, Mohammad Kashif, Nelson Kopyt, Jayant Kumar, Jorge Kusnir, Jean Lee, Essam Maasarani, Richard Miller, M. Reza Mizani, Jesus Navarro, Amber Podoll, Thomas Pohlman, Denise Rivers, Derrick Robinson, Lisa Rich, Arnold Silva, Mark Smith, Joel Topf, James Tumlin, Scott Ungar, and Steven Zeig

Subjects
Diseases of the genitourinary system. Urology, RC870-923
Abstract

Introduction: There is an unmet medical need for pruritus associated with chronic kidney disease, a distressing complication characterized by generalized and persistent itch affecting 20% to 40% of patients undergoing hemodialysis. Here we report the results of a phase 2 trial evaluating the efficacy and safety of a novel peripherally restricted kappa opioid receptor agonist, difelikefalin, in adult patients undergoing hemodialysis with pruritus. Methods: In this study, 174 hemodialysis patients with moderate-to-severe pruritus were randomly assigned to receive difelikefalin (0.5, 1.0, or 1.5 μg/kg) or placebo intravenously thrice weekly after each hemodialysis session for 8 weeks in a double-blind, controlled trial. The primary endpoint was the change from baseline at week 8 in the weekly mean of the 24-hour Worst Itching Intensity Numerical Rating Scale score. The secondary efficacy endpoint was the change in itch-related quality of life measured by the Skindex-10 questionnaire. Other endpoints included safety, sleep quality, and additional measures including the 5-D itch scale. Results: A significant reduction from baseline in itch intensity scores at week 8 favored all difelikefalin doses combined versus placebo (P = 0.002). Difelikefalin also showed improvement over placebo in Skindex-10, 5-D itch, and sleep disturbance scores (P ≤ 0.005). Overall, 78% of patients receiving difelikefalin reported treatment-emergent adverse events versus 42% of patients given placebo, with diarrhea, dizziness, nausea, somnolence, and fall being the most frequent (≥5%). Conclusion: In this trial, difelikefalin effectively reduced itching intensity and improved sleep and itch-related quality of life. Keywords: chronic kidney disease, CKD-aP, CR845, hemodialysis, kappa opioid receptor agonist, uremic pruritus

Published
2020
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25. Kidney and Cardiovascular Effects of Canagliflozin According to Age and Sex

Author

Tae Won Yi, Brendan Smyth, Gian Luca Di Tanna, Clare Arnott, Kathryn Cardoza, Amy Kang, Carol Pollock, Rajiv Agarwal, George Bakris, David M. Charytan, Dick de Zeeuw, Hiddo J.L. Heerspink, Bruce Neal, David C. Wheeler, Christopher P. Cannon, Hong Zhang, Bernard Zinman, Vlado Perkovic, Adeera Levin, Kenneth W. Mahaffey, Meg Jardine, Barry M. Brenner, Tom Greene, Meg J. Jardine, Gary Meininger, Nicole Li, Inna Kolesnyk, Diego Aizenberg, Roberto Pecoits-Filho, David Cherney, Gregorio Obrador, Glenn Chertow, Tara Chang, Carmel Hawley, Linong Ji, Takashi Wada, Vivekanand Jha, Soo Kun Lim, Mary Anne Lim-Abrahan, Florence Santos, Dong-Wan Chae, Shang-Jyh Hwang, Evgueniy Vazelov, Ivan Rychlík, Samy Hadjadj, Vera Krane, László Rosivall, Luca De Nicola, Alexander Dreval, Michał Nowicki, Adalbert Schiller, Larry Distiller, Jose L. Górriz, Mykola Kolesnyk, null David, C. Wheeler, Rodolfo Andres Ahuad Guerrero, Juan Pablo Albisu, Andres Alvarisqueta, Ines Bartolacci, Mario Alberto Berli, Anselmo Bordonava, Pedro Calella, Maria Cecilia Cantero, Luis Rodolfo Cartasegna, Esteban Cercos, Gabriela Cecilia Coloma, Hugo Colombo, Victor Commendatore, Jesus Cuadrado, Carlos Alberto Cuneo, Ana Maria Cusumano, Walter Guillermo Douthat, Ricardo Dario Dran, Eduardo Farias, Maria Florencia Fernandez, Hernan Finkelstein, Guillermo Fragale, Jose Osvaldo Fretes, Nestor Horacio Garcia, Anibal Gastaldi, Elizabeth Gelersztein, Jorge Archibaldo Glenny, Joaquin Pablo Gonzalez, Patricia del Carmen Gonzalez Colaso, Claudia Goycoa, Gustavo Cristian Greloni, Adrian Guinsburg, Sonia Hermida, Luis Isaias Juncos, Maria Isabel Klyver, Florencia Kraft, Fernando Krynski, Paulina Virginia Lanchiotti, Ricardo Alfonso Leon de la Fuente, Nora Marchetta, Pablo Mele, Silvia Nicolai, Pablo Antonio Novoa, Silvia Ines Orio, Fabian Otreras, Alejandra Oviedo, Pablo Raffaele, Jorge Hector Resk, Lucas Rista, Nelson Rodriguez Papini, Jorgelina Sala, Juan Carlos Santos, Lilia Beatriz Schiavi, Horacio Sessa, Tomas Smith Casabella, Maria Rosa Ulla, Maria Valdez, Augusto Vallejos, Adriana Villarino, Virginia Esther Visco, Alfredo Wassermann, Cesar Javier Zaidman, Ngai Wah Cheung, Carolyn Droste, Ian Fraser, David Johnson, Peak Mann Mah, Kathy Nicholls, David Packham, Joseph Proietto, Anthony Roberts, Simon Roger, Venessa Tsang, Roberto Abrão Raduan, Fernando Augusto Alves da Costa, Celso Amodeo, Luiz Alberto Andreotti Turatti, Rachel Bregman, Fernanda Cristina Camelo Sanches, Luis Henrique Canani, Antônio Roberto Chacra, João Lindolfo Cunha Borges, Sérgio Alberto Cunha Vêncio, Roberto Jorge da Silva Franco, Domingos d’Avila, Evandro de Souza Portes, Pedro de Souza, Luciane Mônica Deboni, Fadlo Fraige Filho, Bruno Geloneze Neto, Marcus Gomes, Suely Keiko Kohara, Elizete Keitel, Jose Francisco Kerr Saraiva, Hugo Roberto Kurtz Lisboa, Fabiana Loss de Carvalho Contieri, Rosângela Milagres, Renan Montenegro Junior, Claudia Moreira de Brito, Miguel Nasser Hissa, Ângela Regina Nazario Sabbag, Irene Noronha, Daniel Panarotto, Roberto Pecoits Filho, Márcio Antônio Pereira, Wladmir Saporito, Antonio Scafuto Scotton, Tiago Schuch, Roberto Simões de Almeida, Cássio Slompo Ramos, João Soares Felício, Fernando Thomé, Jean Carlo Tibes Hachmann, Sérgio Yamada, Cesar Yoiti Hayashida, Tarissa Beatrice Zanata Petry, Maria Teresa Zanella, Viktoria Andreeva, Angelina Angelova, Stefan Dimitrov, Veselka Genadieva, Gabriela Genova-Hristova, Kiril Hristozov, Zdravko Kamenov, Atanas Koundurdjiev, Lachezar Lozanov, Viktor Margaritov, Boyan Nonchev, Rangel Rangelov, Alexander Shinkov, Margarita Temelkova, Ekaterina Velichkova, Andrian Yakov, Naresh Aggarwal, Ronnie Aronson, Harpreet Bajaj, Guy Chouinard, James Conway, Serge Cournoyer, Gerald DaRoza, Sacha De Serres, François Dubé, Ronald Goldenberg, Anil Gupta, Milan Gupta, Sam Henein, Hasnain Khandwala, Lawrence Leiter, François Madore, Alan McMahon, Norman Muirhead, Vincent Pichette, Remi Rabasa-Lhoret, Andrew Steele, Navdeep Tangri, Ali Torshizi, Vincent Woo, Nadia Zalunardo, María Alicia Fernández Montenegro, Juan Gonzalo Godoy Jorquera, Marcelo Medina Fariña, Victor Saavedra Gajardo, Margarita Vejar, Nan Chen, Qinkai Chen, Shenglian Gan, Yaozhong Kong, Detian Li, Wenge Li, Xuemei Li, Hongli Lin, Jian Liu, Weiping Lu, Hong Mao, Yan Ren, Weihong Song, Jiao Sun, Lin Sun, Ping Tu, Guixia Wang, Jinkui Yang, Aiping Yin, Xueqing Yu, Minghui Zhao, Hongguang Zheng, Jose Luis Accini Mendoza, Edgar Arcos, Jorge Avendano, Jorge Ernesto Andres Diaz Ruiz, Luis Hernando Garcia Ortiz, Alexander Gonzalez, Eric Hernandez Triana, Juan Diego Higuera, Natalia Malaver, Dora Inés Molina de Salazar, Ricardo Rosero, Monica Alexandra Terront Lozano, Luis Valderrama Cometa, Alex Valenzuela, Ruben Dario Vargas Alonso, Ivan Villegas, Hernan Yupanqui, Dagmar Bartaskova, Petr Barton, Jana Belobradkova, Lenka Dohnalova, Tomas Drasnar, Richard Ferkl, Katarina Halciakova, Vera Klokocnikova, Richard Kovar, Jiri Lastuvka, Martin Lukac, Satu Pesickova, Karel Peterka, Jiri Pumprla, Ivan Rychlik, Frantisek Saudek, Vladimir Tesar, Martin Valis, Pavel Weiner, Stanislav Zemek, Eric Alamartine, Sophie Borot, Bertrand Cariou, Bertrand Dussol, Jean-Pierre Fauvel, Pierre Gourdy, Alexandre Klein, Yannick Le Meur, Alfred Penfornis, Ronan Roussel, Pierre-Jean Saulnier, Eric Thervet, Philippe Zaoui, Volker Burst, Markus Faghih, Grit Faulmann, Hermann Haller, Reinhold Jerwan-Keim, Stephan Maxeiner, Björn Paschen, Georg Plassmann, Ludger Rose, Ronaldo Arturo Gonzalez Orellana, Franklin Paul Haase, Juan Pablo Moreira Diaz, Luis Alberto Ramirez Roca, Jose Antonio Sánchez Arenales, José Vicente Sanchez Polo, Erick Turcios Juarez, Gyongyi Csecsei, Botond Csiky, Peter Danos, Laszlo Deak, Mihaly Dudas, Eleonora Harcsa, Katalin Keltai, Sandor Keresztesi, Krisztian Kiss, Laszlo Konyves, Lajos Major, Margit Mileder, Marta Molnar, Janos Mucsi, Tamas Oroszlan, Ivan Ory, Gyorgy Paragh, Eva Peterfai, Gizella Petro, Katalin Revesz, Robert Takacs, Sandor Vangel, Szilard Vasas, Marianna Zsom, Oomman Abraham, Raju Sree Bhushan, Dewan Deepak, Fernando M. Edwin, Natarajan Gopalakrishnan, Noble Gracious, Alva Hansraj, Dinesh Jain, C.B. Keshavamurthy, Dinesh Khullar, Sahay Manisha, Jayameena Peringat, Narayan Prasad, Rao K. Satyanarayana, Reddy Sreedhar, Melemadathil Sreelatha, Bhimavarapu Sudhakar, Ramesh Chandra Vyasam, Riccardo Bonadonna, Pietro Castellino, Antonio Ceriello, Luca Chiovato, Salvatore De Cosmo, Giuseppe Derosa, Alberto Di Carlo, Graziano Di Cianni, Giovanni Frascà, Giorgio Fuiano, Giovanni Gambaro, Giacomo Garibotto, Carlo Giorda, Fabio Malberti, Marcora Mandreoli, Edoardo Mannucci, Emanuela Orsi, Piermarco Piatti, Domenico Santoro, Ferdinando Carlo Sasso, Gaetano Serviddio, Andrea Stella, Roberto Trevisan, Anna Maria Veronelli, Luca Zanoli, Hitoshi Akiyama, Hiromi Aoki, Akimichi Asano, Tadashi Iitsuka, Shizuo Kajiyama, Susumu Kashine, Toshio Kawada, Takamoto Kodera, Hiroshi Kono, Kazunori Koyama, Yasuro Kumeda, Shozo Miyauchi, Kazuyuki Mizuyama, Tetsuji Niiya, Hiroko Oishi, Satoshi Ota, Terue Sakakibara, Masahiko Takai, Osamu Tomonaga, Mitsuru Tsujimoto, Masakiyo Wakasugi, Yasushi Wakida, Takayuki Watanabe, Masayo Yamada, Kazuhiro Yanagida, Toshihiko Yanase, Wataru Yumita, Egle Gaupsiene, Dalia Kozloviene, Antanas Navickas, Egle Urbanaviciene, Rohana Abdul Ghani, Khalid Abdul Kadir, Norsiah Ali, Mohd Daud Che Yusof, Chye Lee Gan, Mastura Ismail, Wei Yen Kong, Swee Win Lam, Li Yuan Lee, Chek Loong Loh, Anita Bhajan Manocha, Kee Sing Ng, Nik Nur Fatnoon Nik Ahmad, Vanassa Ratnasingam, Saiful Shahrizal Bin Shudim, Paranthaman Vengadasalam, Luis David Abraira Munoz, Melchor Alpizar Salazar, Juan Baas Cruz, Mario Burgos Soto, Jose Chevaile Ramos, Alfredo Chew Wong, Jose Ricardo Correa Rotter, Tonatiu Diaz Escalante, Favio Edmundo Enriquez Sosa, Fernando Flores Lozano, Luis Fernando Flota Cervera, Paul Frenk Baron, Cecilia Garcia Ballesteros, Jose David Gomez Rangel, Luis Enrique Herrera Jimenez, Sergio Saul Irizar Santana, Fernando Jimenez Flores, Hugo Laviada Molina, Rosa Isela Luna Ceballos, Belia Martin del Campo Blanco, Guadalupe Morales Franco, Oscar Tarsicio Moreno Loza, Cynthia Mustieles Rocha, Gregorio Obrador Vera, Ricardo Orozco Castellanos, Juan Peralta Calcaneo, Miguel Angel Reyes Rosano, Hiromi Rodriguez Pattzi, Juan Rosas Guzman, Isabel Erika Rucker Joerg, Sandra Berenice Saavedra Sanchez, Jose Hector Sanchez Mijangos, Pablo Serrano Sanson, Juan Alfredo Tamayo y Orozco, Eloisa Tellez Chavez, Alejandro Valdes Cepeda, Luis Venegas Carrillo, Juan Villagordoa Mesa, Rolando Zamarripa Escobedo, John Baker, Paul Noonan, Russell Scott, Robert Walker, Edward Watson, Michael Williams, Simon Young, Zaynab Abejuela, Jeimeen Agra, Grace Aquitania, Clodoaido Caringal, Rhea Severina Comia, Lalaine Delos Santos, Olivert Gomez, Cecilia Jimeno, Gerry Tan, Marsha Tolentino, Christy Yao, Yvette Ethel Yap, Ma. Dovie Lallaine Ygpuara, Renata Bijata-Bronisz, Lucyna Hotlos, Andrzej Januszewicz, Barbara Kaczmarek, Anna Kaminska, Lech Lazuka, Andrzej Madej, Stanislaw Mazur, Dorota Mlodawska-Choluj, Michal Nowicki, Grazyna Orlowska-Kowalik, Grazyna Popenda, Barbara Rewerska, Dariusz Sowinski, Liliana Monica Angelescu, Veronica Anghel, Rodica-Ioana Avram, Mihaela-Magdalena Busegeanu, Adriana Cif, Dana Cosma, Carmen Crisan, Luiza Despina Demian, Ioana Emilia Ferariu, Ildiko Halmagyi, Nicolae Hancu, Mircea Munteanu, Doru Negru, Adriana Gabriela Onaca, Ligia Petrica, Amorin Remus Popa, Aurelian-Emil Ranetti, Cristian Serafinceanu, Cristina Toarba, Alina Agafyina, Olga Barbarash, Olga Barysheva, Daniil Chizhov, Vladimir Dobronravov, Irina Glinkina, Elena Grineva, Vladimir Khirmanov, Elena Kolmakova, Tatiana Koroleva, Liudmila Kvitkova, Viacheslav Marasaev, Ashot Mkrtumyan, Tatiana Morugova, Galina Nagibovich, Oleg Nagibovich, Sergei Nedogoda, Irina Osipova, Tatiana Raskina, Yulia Samoylova, Olga Sazonova, Minara Shamkhalova, Elena Shutemova, Yuriy Shwartz, Oleg Uriasyev, Sergey Vorobyev, Anna Zateyshchikova, Dmitry Zateyshshikov, Tatyana Zykova, Slobodan Antic, Miodrag Djordjevic, Aleksandra Kendereski, Katarina Lalic, Nebojsa Lalic, Vesna Popovic-Radinovic, Jana Babikova, Olga Benusova, Ingrid Buganova, Jan Culak, Andrej Dzupina, Jana Dzuponova, Peter Fulop, Adriana Ilavska, Emil Martinka, Zuzana Ochodnicka, Daniel Pella, Iveta Smatanova, Fayzal Ahmed, Aysha Badat, Johannes Breedt, Lawrence Distiller, Vimladhevi Govender, Ravendran Govender, Mukesh Joshi, Jaco Jurgens, Gulam Latiff, Landman Lombard, Mohamed Mookadam, Nomangesi Ngcakani, Hendrik Nortje, Helena Oosthuizen, Larisha Pillay-Ramaya, Hans Prozesky, Jeevren Reddy, Paul Rheeder, Mary Seeber, Young Min Cho, In-Kyung Jeong, Sin Gon Kim, Yeong Hoon Kim, Hyuk-Sang Kwon, Min Jeong Kwon, Byung-Wan Lee, JungEun Lee, Moon-Kyu Lee, Moon-Suk Nam, Kook-Hwan Oh, Cheol- Young Park, Sun-Hee Park, Kun Ho Yoon, Pere Alvarez Garcia, Luis Asmarats Mercadal, Clara Barrios, Fernando Cereto Castro, Secundino Cigarran Guldris, Marta Dominguez Lopez, Jesus Egido de los Rios, Gema Fernandez Fresnedo, Antonio Galan Serrano, Isabel Garcia, Francisco Javier Gonzalez Martinez, Jose Esteban Jodar Gimeno, Manuel Lopez Mendoza, Tamara Malek Marin, Cristobal Morales Portillo, Maria Antonia Munar Vila, Manuel Muñoz Torres, Javier Nieto Iglesias, Jonay Pantoja Perez, Merce Perez Vera, Jose M. Portoles Perez, María Angustias Quesada Simón, Rafael Simo Canonge, Alfonso Soto Gonzalez, Manel Terns Riera, Francisco Jose Tinahones Madueno, Mercedes Velo Plaza, Chwen-Tzuei Chang, Lee-Ming Chuang, Te-Lin Hsia, Chang-Hsun Hsieh, Chih-Ching Lin, Yung- Chuan Lu, Wayne H-H Sheu, Olga Barna, Svitlana D. Bilyk, Volodymyr Botsyurko, Iryna Dudar, Ivan Fushtey, Olga Godlevska, Oleksandr Golovchenko, Olga Gyrina, Anatoliy Kazmirchuk, Iuliia Komisarenko, Oleksii Korzh, Nonna Kravchun, Oleg Legun, Borys Mankovskyy, Liliya Martynyuk, Yuriy Mostovoy, Nataliia Pashkovska, Larysa Pererva, Tetyana Pertseva, Oleksandr Samoylov, Ivan Smirnov, Yevgeniya Svyshchenko, Halyna Tomashkevych, Ivan Topchii, Nadiya Tryshchuk, Vira Tseluyko, Vadym Vizir, Maryna Vlasenko, Tetiana Zlova, Liliia Zub, Salah Abusnana, Mohamed Railey, Kamal Abouglila, Paul Ainsworth, Zishan Ali, Vijayaraman Arutchelvam, Maria Barnard, Srikanth Bellary, Emyr Davies, Mark Davies, Simon Davies, Alison Dawson, Mohsen El Kossi, Patrick English, Donald Fraser, Luigi Gnudi, Anthony Gunstone, Timothy Hall, Wasim Hanif, Alan Jackson, Andrew Johnson, Franklin Joseph, Singhan Krishnan, Mick Kumwenda, Iain MacDougall, Paul Nixon, Joseph O'Hare, Sam Philip, Shenaz Ramtoola, Manish Saxena, Davesh Sennik, Godwin Simon, Baldev Singh, Jeffrey Stephens, Anna Strzelecka, Rehan Symonds, Wayne Turner, Mona Wahba, John Wakeling, David Wheeler, Peter Winocour, Joseph Abdallah, Raied Abdullah, Matthew Abramowitz, Idalia Acosta, Joseph Aiello, Laura Akright, Ayim Akyea-Djamson, Rajendran Alappan, Radica Alicic, Amer Al-Karadsheh, Dale Crawford Allison, Carlos Arauz-Pacheco, Shahabul Arfeen, Ahmed Arif, Moogali Arvind, Naveen Atray, Ahmed Awad, Peggy Barnhill, Elizabeth Barranco, Carlos Barrera, Matthew Beacom, Venkata Behara, Diogo Belo, Rhonda Bentley-Lewis, Ramon Berenguer, Lidia Bermudez, Marializa Bernardo, Mihaela Biscoveanu, Cynthia Bowman-Stroud, Donald Brandon, Osvaldo Brusco, Robert Busch, Yamil Canaan, Alicia Chilito, Tom Christensen, Cynthia Christiano, Elena Christofides, Caroucel Chuateco, Kenneth Cohen, Robert Cohen, Debbie Cohen-Stein, Charles Cook, Daniel Coyne, Nizar Daboul, Riad Darwish, Adarsh Daswani, Kenneth Deck, Cyrus Desouza, Devasmita Dev, Monika Dhillon, Sohan Dua, Frank Eder, Ana Maria Elosegui, Mohamed El-Shahawy, John Ervin, Alberto Esquenazi, John Evans, Steven Fishbane, Juan Frias, Eugenia Galindo-Ramos, Claude Galphin, Adline Ghazi, Enrique Gonzalez, David Gorson, Anupama Gowda, Barbara Greco, Stephen Grubb, Rakesh Gulati, Jamal Hammoud, Stuart Handelsman, Israel Hartman, Kenneth Hershon, Daniel Hiser, George Hon, Radu Jacob, Maria Jaime, Aamir Jamal, Charles Kaupke, Gerald Keightley, Elizabeth Kern, Rakhi Khanna, Zeid Khitan, Sun Kim, Nelson Kopyt, Csaba Kovesdy, Gopal Krishna, Jeffrey (Jay) Kropp, Amrendra Kumar, Jayant Kumar, Neil Kumar, Jorge Kusnir, Wendy Lane, Mary Lawrence, Lawrence Lehrner, John Lentz, Dennis Levinson, Derek Lewis, Kenneth Liss, Andreas Maddux, Hiralal Maheshwari, Sreedhar Mandayam, Isam Marar, Bhasker Mehta, John Middleton, Jorge Mordujovich, Ramon Moreda, Moustafa Moustafa, Samuel Mujica Trenche, Mohanram Narayanan, Javier Narvarte, Tareq Nassar, George Newman, Brian Nichol, Philip Nicol, Josier Nisnisan, A. Kaldun Nossuli, Chamberlain Obialo, Sarah Olelewe, Michael Oliver, Andrew O'Shaughnessy, John Padron, Rohit Pankhaniya, Reginald Parker, Devesh Patel, Gnyandev Patel, Nina Patel, Humberto Pavon, Armando Perez, Carlos Perez, Alan Perlman, Karlton Pettis, Walter Pharr, Andrea Phillips, Raman Purighalla, Luis Quesada-Suarez, Rajiv Ranjan, Sanjeev Rastogi, Jakkidi Reddy, Marc Rendell, Lisa Rich, Michael Robinson, Hector Rodriguez, Sylvia Rosas, Fadi Saba, Rallabhandi Sankaram, Ravi Sarin, Robert Schreiman, David Scott, Mohamed Sekkarie, John Sensenbrenner, Muhammad Shakeel, Michael Shanik, Sylvia Shaw, Stephen Smith, Richard Solomon, Amy Sprague, Leslie Spry, Pusadee Suchinda, Senan Sultan, Prasanth Surampudi, Sherry Sussman, Anjanette Tan, Antonio Terrelonge, Michael Thompson, Fernando Trespalacios, Bruce Trippe, Pilar Trueba, Marcel Twahirwa, John Updegrove, Peter Van Buren, Mark Vannorsdall, Freemu Varghese, Pedro Velasquez-Mieyer, Sailaja Ventrapragada, Goga Vukotic, Khurram Wadud, Mark Warren, Henry Watson, Ronald Watts, Daniel Weiner, James Welker, Jean Welsh, Shelley Williams, and Michelle Zaniewski-Singh

Subjects
age, diabetes, Nephrology, kidney outcomes, sex, Diabetic kidney disease, canagliflozin, cardiovascular outcomes, chronic kidney disease, sodium/glucose cotransporter 2 inhibitors
Abstract

Rationale & Objective: It is unclear whether the effect of canagliflozin on adverse kidney and cardiovascular events in those with diabetic kidney disease varies by age and sex. We assessed the effects of canagliflozin among age group categories and between sexes in the Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study.Study Design: Secondary analysis of a randomized controlled trial.Setting & Participants: Participants in the CREDENCE trial.Intervention: Participants were randomly assigned to receive canagliflozin 100 mg/d or placebo.Outcomes: Primary composite outcome of kidney failure, doubling of serum creatinine concentration, or death due to kidney or cardiovascular disease. Prespecified secondary and safety outcomes were also analyzed. Outcomes were evaluated by age at baseline (Results: The mean age of the cohort was 63.0 ± 9.2 years, and 34% were female. Older age and female sex were independently associated with a lower risk of the composite of adverse kidney outcomes. There was no evidence that the effect of canagliflozin on the primary outcome (a composite of kidney failure, a doubling of serum creatinine concentration, or death from kidney or cardiovascular causes) differed between age groups (HRs, 0.67 [95% CI, 0.52-0.87], 0.63 [0.48-0.82], and 0.89 [0.61-1.29] for ages Limitations: This was a post hoc analysis with multiple comparisons.Conclusions: Canagliflozin consistently reduced the relative risk of kidney events in people with diabetic kidney disease in both sexes and across age subgroups. As a result of greater background risk, the absolute reduction in adverse kidney outcomes was greater in younger participants.Funding: This post hoc analysis of the CREDENCE trial was not funded. The CREDENCE study was sponsored by Janssen Research and Development and was conducted collaboratively by the sponsor, an academic-led steering committee, and an academic research organization, George Clinical.Trial Registration: The original CREDENCE trial was registered at ClinicalTrials.gov with study number NCT02065791.

Published
2023

33. FDTD modeling and experimental verification of electromagnetic power dissipated in domestic microwave ovens.

Author

Kopyt, Paweł and Celuch-Marcysiak, Małgorzata

Subjects
TELECOMMUNICATION, FINITE differences, COMPUTATIONAL electromagnetics, MICROWAVES, ENGINEERING, MICROWAVE ovens
Abstract

The FDTD (Finite Difference Time Domain) method has proven to be effective in modeling high-frequency electromagnetic problems in telecommunications industry. Recently it has been successfully applied in microwave power engineering. In order to accurately model scenarios typical in this field one has to deal with the movement of objects placed inside cavities. This paper describes a simple algorithm that makes it possible to take into account object rotation -- important in simulations of domestic microwave ovens. Results of example simulations are presented and an experimental verification of the simulation tool is performed. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Medium-Term Forecasts of Load Profiles in Polish Power System including E-Mobility Development

Author

Paweł Piotrowski, Dariusz Baczyński, and Marcin Kopyt

Subjects
mid-term forecast, e-mobility, electric vehicles (EVs), power system demand, load profile forecast, machine learning (ML), Technology
Abstract

The main objective of this study was to conduct multi-stage and multi-variant prognostic research to assess the impact of e-mobility development on the Polish power system for the period 2022–2027. The research steps were as follows: forecast the number of electric vehicles (using seven methods), forecast annual power demand arising solely out of the operation of the forecast number of electric vehicles, forecast annual power demand with and without the impact of e-mobility growth (using six methods), forecast daily profiles of typical days with and without the impact of e-mobility growth (using three methods). For the purpose of this research, we developed a unique Growth Dynamics Model to forecast the number of electric vehicles in Poland. The application of Multi-Layer Perceptron (MLP) to the extrapolation of non-linear functions (to the forecast number of electric vehicles and forecast annual power demand without the impact of e-mobility growth) is our original, unique proposal to use the Artificial Neural Network (ANN). Another unique, innovative proposal is to include Artificial Neural Networks (Multi-Layer Perceptron and Long short-term memory (LSTM)) in an Ensemble Model for simultaneous extrapolation of 24 non-linear functions to forecast daily profiles of typical days without taking e-mobility into account. This research determined the impact of e-mobility development on the Polish power system, both in terms of annual growth of demand for power and within particular days (hourly distribution) for two typical days (summer and winter). Under the (most likely) balanced growth variant of annual demand for power, due to e-mobility, such demand would grow by more than 4%, and almost 7% under the optimistic variant. Percentage growth of power demand in terms of variation according to time of day was determined. For instance, for the balanced variant, the largest percentage share of e-mobility was in the evening “peak” time (about 6%), and the smallest percentage was in the night “valley” (about 2%).

Published
2022
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38. Electrodynamic theory of ferromagnetic resonance and its applications in precise measurements of ferromagnetic linewidth, permeability tensor and saturation magnetization

Author

Jerzy Krupka, Adam Pacewicz, Bartłomiej Salski, and Paweł Kopyt

Subjects
Physics, QC1-999
Abstract

This review paper describes the state of the art in measurements of ferromagnetic linewidth, permeability tensor and saturation magnetization employing electrodynamic theory of ferromagnetic resonance. It is shown that the electrodynamic theory allows significant improvements of measurement accuracy of these parameters with respect to the commonly used perturbation and magnetostatics theories. Contrary to the perturbation method the electrodynamic theory is not limited to small samples. It allows determination of the resonance frequencies and Q-factors for arbitrary size spherical and cylindrical gyromagnetic samples in suitably chosen metal enclosures. Results obtained with the electrodynamic theory for very small samples are identical to those obtained with perturbation and magnetostatics theories. Results of measurements of the ferromagnetic linewidth, permeability tensor and saturation magnetization at microwave frequencies are presented.

Published
2020
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39. Advanced Ensemble Methods Using Machine Learning and Deep Learning for One-Day-Ahead Forecasts of Electric Energy Production in Wind Farms

Author

Paweł Piotrowski, Dariusz Baczyński, Marcin Kopyt, and Tomasz Gulczyński

Subjects
wind energy, wind farm, ensemble methods, short-term forecasting, electric energy production, machine learning, Technology
Abstract

The ability to precisely forecast power generation for large wind farms is very important, since such generation is highly unstable and creates problems for Distribution and Transmission System Operators to properly prepare the power system for operation. Forecasts for the next 24 h play an important role in this process. They are also used in energy market transactions. Even a small improvement in the quality of these forecasts translates into more security of the system and savings for the economy. Using two wind farms for statistical analyses and forecasting considerably increases credibility of newly created effective prediction methods and formulated conclusions. In the first part of our study, we have analysed the available data to identify potentially useful explanatory variables for forecasting models with additional development of new input data based on the basic data set. We demonstrate that it is better to use Numerical Weather Prediction (NWP) point forecasts for hourly lags: −3, 2, −1, 0, 1, 2, 3 (original contribution) as input data than lags 0, 1 that are typically used. Also, we prove that it is better to use forecasts from two NWP models as input data. Ensemble, hybrid and single methods are used for predictions, including machine learning (ML) solutions like Gradient-Boosted Trees (GBT), Random Forest (RF), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), K-Nearest Neighbours Regression (KNNR) and Support Vector Regression (SVR). Original ensemble methods, developed for researching specific implementations, have reduced errors of forecast energy generation for both wind farms as compared to single methods. Predictions by the original ensemble forecasting method, called “Ensemble Averaging Without Extremes” have the lowest normalized mean absolute error (nMAE) among all tested methods. A new, original “Additional Expert Correction” additionally reduces errors of energy generation forecasts for both wind farms. The proposed ensemble methods are also applicable to short-time generation forecasting for other renewable energy sources (RES), e.g., hydropower or photovoltaic (PV) systems.

Published
2022
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40. Spatial Interactions in Business and Housing Location Models

Author

Katarzyna Kopczewska, Mateusz Kopyt, and Piotr Ćwiakowski

Subjects
business location, housing valuation, density, multimodality, urban structure, Agriculture
Abstract

The paper combines theoretical models of housing and business locations and shows that they have the same determinants. It evidences that classical, behavioural, new economic geography, evolutionary and co-evolutionary frameworks apply simultaneously, and one should consider them jointly when explaining urban structure. We use quantitative tools in a theory-guided factors induction approach to show the complexity of location models. The paper discusses and measures spatial phenomena as distance-decaying gradients, spatial discontinuities, densities, spillovers, spatial interactions, agglomerations, and as multimodal processes. We illustrate the theoretical discussion with an empirical case of interacting point-patterns for business, housing, and population. The analysis reveals strong links between housing valuation and business location and profitability, accompanied by the related spatial phenomena. It also shows that assumptions concerning unimodal spatial urban structure, the existence of rational maximisers, distance-decaying externalities, and a single pattern of behaviour, do not hold. Instead, the reality entails consideration of multimodality, a mixture of maximisers and satisfiers, incomplete information, appearance of spatial interactions, feed-back loops, as well as the existence of persistence of behaviour, with slow and costly adjustments of location.

Published
2021
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41. Aluminium-Based Metal–Organic Framework Nano Cuboids and Nanoflakes with Embedded Gold Nanoparticles for Carbon Dioxide Fixation with Epoxides into Cyclic Esters.

Author

Kopacka, Gabriela, Wasiluk, Kinga, Majewski, Pawel W., Kopyt, Michał, Kwiatkowski, Piotr, and Megiel, Elżbieta

Subjects
CARBON dioxide fixation, GOLD nanoparticles, EPOXY compounds, METAL-organic frameworks, PROPYLENE oxide, MICROPOROSITY, NITRILE oxides, NAPHTHALENE derivatives
Abstract

The fixation of carbon dioxide with epoxides is one of the most attractive methods for the green utilisation of this greenhouse gas and leads to many valuable chemicals. This process is characterised by 100% atom efficiency; however, an efficient catalyst is required to achieve satisfactory yields. Metal–organic frameworks (MOFs) are recognised as being extremely promising for this purpose. Nevertheless, many of the proposed catalysts are based on ions of rare elements or elements not entirely safe for the environment; this is notable with commercially unavailable ligands. In an effort to develop novel catalysts for CO2 fixation on an industrial scale, we propose novel MOFs, which consist of aluminium ions coordinated with commercially available 1,4-naphthalene dicarboxylic acid (Al@NDC) and their nanocomposites with gold nanoparticles entrapped inside their structure (AlAu@NDC). Due to the application of 4-amino triazole and 5-amino tetrazole as crystallization mediators, the morphology of the synthesised materials can be modified. The introduction of gold nanoparticles (AuNPs) into the structure of the synthesised Al-based MOFs causes the change in morphology from nano cuboids to nanoflakes, simultaneously decreasing their porosity. However, the homogeneity of the nanostructures in the system is preserved. All synthesised MOF materials are highly crystalline, and the simulation of PXRD patterns suggests the same tetragonal crystallographic system for all fabricated nanomaterials. The fabricated materials are proven to be highly efficient catalysts for carbon dioxide cycloaddition with a series of model epoxides: epichlorohydrin; glycidol; styrene oxide; and propylene oxide. Applying the synthesised catalysts enables the reactions to be performed under mild conditions (90 °C; 1 MPa CO2) within a short time and with high conversion and yield (90% conversion of glycidol towards glycerol carbonate with 89% product yield within 2 h). The developed nanocatalysts can be easily separated from the reaction mixture and reused several times (both conversion and yield do not change after five cycles). The excellent performance of the fabricated catalytic materials might be explained by their high microporosity (from 421 m2 g−1 to 735 m2 g−1); many catalytic centres in the structure exhibit Lewis acids' behaviour, increased capacity for CO2 adsorption, and high stability. The presence of AuNPs in the synthesised nanocatalysts (0.8% w/w) enables the reaction to be performed with a higher yield within a shorter time; this is especially important for less-active epoxides such as propylene oxide (two times higher yield was obtained using a nanocomposite, in comparison with Al-MOF without nanoparticles). [ABSTRACT FROM AUTHOR]

Published
2024
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44. Ferromagnetic Resonance Revised – Electrodynamic Approach

Author

Jerzy Krupka, Pavlo Aleshkevych, Bartlomiej Salski, Pawel Kopyt, and Adam Pacewicz

Subjects
Medicine, Science
Abstract

Abstract Resonance in a ferromagnetic sphere, known in the body of literature as the mode of uniform precession, has recently been proven to be magnetic plasmon resonance (MPR). This finding has prompted research which is presented in this paper on the relation between the Q-factor at the MPR and the ferromagnetic resonance (FMR) linewidth ΔH, which is a parameter of magnetized gyromagnetic materials. It is proven in this paper that ΔH can be unequivocally determined from the Q-factor measured at the MPR, if all losses in the resonance system are properly accounted for. It can be undertaken through a rigorous but simple electrodynamic study involving the transcendental equation, as proposed in this paper. The present study also reveals that electric losses have a substantially reduced impact on ΔH due to the large magnetic to electric energy storage ratio at the MPR. Theoretical results are supported by measurements of the Q-factors on a monocrystalline yttrium iron garnet (YIG) sphere.

Published
2017
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45. An unmanned aerial vehicle optimal selection methodology for object tracking

Author

Antoni Kopyt, Janusz Narkiewicz, and Paweł Radziszewski

Subjects
Mechanical engineering and machinery, TJ1-1570
Abstract

In this article, an optimal method of unmanned aerial vehicle selection for following a moving ground target is presented. The most suitable unmanned aerial vehicle from an aircraft operating fleet is selected for tracking task. The aircraft choice is done taking regarding the unmanned aerial vehicle distribution in the mission zone, individual performance of fleet platforms, and maneuverability of a ground platform. The unmanned aerial vehicle fleet members’ flying qualities are various, so an optimization process is used to assign an aircraft to follow the ground target. A target trajectory prediction is embedded in tracking algorithm. The simulation results demonstrated the effectiveness of algorithms developed, and in-flight demonstration proved the possibility of realization of computed trajectories by the unmanned aerial vehicle.

Published
2018
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46. Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine

Author

Paweł Piotrowski, Marcin Kopyt, Dariusz Baczyński, Sylwester Robak, and Tomasz Gulczyński

Subjects
wind energy, wind turbine, hybrid methods, ensemble methods, short-term forecasting, electric energy production, Technology
Abstract

The ability to forecast electricity generation for a small wind turbine is important both on a larger scale where there are many such turbines (because it creates problems for networks managed by distribution system operators) and for prosumers to allow current energy consumption planning. It is also important for owners of small energy systems in order to optimize the use of various energy sources and facilitate energy storage. The research presented here addresses an original, rarely predicted 48 h forecasting horizon for small wind turbines. This topic has been rather underrepresented in research, especially in comparison with forecasts for large wind farms. Wind speed forecasts with a 48 h horizon are also rarely used as input data. We have analyzed the available data to identify potentially useful explanatory variables for forecasting models. Eight sets with increasing data amounts were created to analyze the influence of the types and amounts of data on forecast quality. Hybrid, ensemble and single methods are used for predictions, including machine learning (ML) solutions like long short-term memory (LSTM), multi-layer perceptron (MLP), support vector regression (SVR) and K-nearest neighbours regression (KNNR). Original hybrid methods, developed for research of specific implementations and ensemble methods based on hybrid methods’ decreased errors of energy generation forecasts for small wind turbines in comparison with single methods. The “artificial neural network (ANN) type MLP as an integrator of ensemble based on hybrid methods” ensemble forecasting method incorporates an original combination of predictors. Predictions by this method have the lowest mean absolute error (MAE). In addition, this paper presents an original ensemble forecasting method, called “averaging ensemble based on hybrid methods without extreme forecasts”. Predictions by this method have the lowest root mean square error (RMSE) error among all tested methods. LSTM, a deep neural network, is the best single method, MLP is the second best one, while SVR, KNNR and, especially, linear regression (LR) perform less well. We prove that lagged values of forecasted time series slightly increase the accuracy of predictions. The same applies to seasonal and daily variability markers. Our studies have also demonstrated that using the full set of available input data and the best proposed hybrid and ensemble methods yield the lowest error. The proposed hybrid and ensemble methods are also applicable to other short-time generation forecasting in renewable energy sources (RES), e.g., in photovoltaic (PV) systems or hydropower.

Published
2021
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48. Green Spaces in Urban Environments: Network Planning of Plant Species Composition.

Author

Mityagin, Sergey, Kopyt, Nikita, Shmeleva, Irina A., Malysheva, Sofia, Malysheva, Ekaterina, Antonov, Aleksandr, Sokol, Aleksey, Zakharenko, Nikita, Churiakova, Tatiana, Budennyy, Semen A., and Boukhanovsky, Alexander V.

Abstract

The article deals with the problem of automation and decision-making support in forming sustainable assortments of plant species for landscaped areas of cities, taking into account environmental factors, conditions of growing, properties of plant species, and landscaping practices adopted in the region. The automation of plant species and composition planning for planted territories requires formation of a knowledge base and output algorithms, as well as consideration of specific landscaping practices and techniques adopted in the region. It also requires the application of new modeling methods in combination with methods of spatial analysis, which together with the database of available regional plant species forms a recommendation system and provides decision support in the tasks of landscaping for city planners. The feature of the proposed method based on network analysis is the combination and composition of plant species, as well as the properties of invasive species, which require the use of graph models to form a knowledge base. The proposed method can be useful for forming sustainable assortments of plant species for landscaping squares, boulevards, small courtyards in the city, technical areas and other cases that do not involve the creation of individual complex landscape design. As part of the testing of the proposed method, the authors have formed a unique information base of species. The use of such a database, together with the method of selecting the species composition based on their resistances and interspecies compatibility will ensure the expansion of the diversity of species in the created ecosystem, which will make green areas more resistant to external anthropogenic factors and diseases, as well as preventing the spread of species invasive to the region. [ABSTRACT FROM AUTHOR]

Published
2023
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49. A comprehensive experimental study on head trauma in a 3-year-old child due to unmanned aerial vehicle collisions.

Author

PERZ, RAFAŁ, DĄBROWSKI, IGOR, ZAKRZEWSKI, FILIP, KUMINIARCZYK, MICHAŁ, and KOPYT, ANTONI

Subjects
HEAD injuries
Abstract

Purpose: This research aimed to evaluate the biomechanical impact on a 3-year-old child's head during collisions with unmanned aerial vehicles (UAVs), focusing on the effects of UAV mass, impact velocity, and impact direction, using the Head Injury Criterion (HIC) for assessment. Methods: Experiments simulated impacts with UAVs of varying masses (249, 500 and 900 g) and velocities (19.0, 24.0 and 29.0 m/s) from different directions. HIC values were measured for each scenario and analyzed in relation to the Abbreviated Injury Scale to determine potential injury severity. Results: The findings showed that both the UAV's mass and impact velocity have a significant influence on the HIC value, with higher figures indicating a greater risk of serious injury. For the UAVs weighing 249 g and 500 g, frontal impacts resulted in the highest HIC values; however, for the UAV weighing 900 g, the highest HIC value occurred for the back hit. Moreover, injury risk was found to escalate non-linearly with increased velocity, especially for heavier UAVs. Conclusions: The study emphasizes the critical influence of UAV mass and impact velocity on the severity of head injuries in children. Increased mass and velocity correlated with higher HIC values, indicating a greater likelihood of severe injury. Frontal impacts were particularly hazardous for lighter UAVs, while rear impacts were more dangerous for heavier UAVs. These findings support the need for stringent regulations on UAV operational parameters, focusing on speed and mass limitations, to mitigate the risk of severe head injuries in children. [ABSTRACT FROM AUTHOR]

Published
2023
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