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3. Results of the COVID-19 mental health international for the health professionals (COMET-HP) study: depression, suicidal tendencies and conspiracism

Author

N. Fountoulakis, Konstantinos, N. Karakatsoulis, Grigorios, Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Cabrera Abud, Indira Indiana, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, de Berardis, Domenico, Zamora Delgado, Sergio, de Lucena, David, de Sousa, Avinash, di Stefano, Ramona, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Paz, Gonda, Xenia, Gondek, Tomasz M., Morera González, Daniela, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, Tasdik M., Azreen Hashim, Nurul, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Yilmaz Kafali, Helin, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kopishinskaia, Svetlana, Kosenko, Korneliia, Koupidis, Sotirios A., Kovacs, Illes, Kulig, Barbara, Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Iqbal Malik, Najma, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Meza Martínez, Xarah Elenne, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Pinto da Costa, Mariana, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Vargas Ramírez, Francisca, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Reyes Flores, Elena Ninoska, Rivera-Encinas, María Teresa, Saiz, Pilar A., Sánchez de Carmona, Manuel, Saucedo Martínez, David, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva-Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vrublevska, Jelena, Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, Prezerakos, Panagiotis E., Berk, Michael, Levaj, Sarah, and Smirnova, Daria

Published
2023
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5. Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study

Author

Fountoulakis, Konstantinos N., Vrublevska, Jelena, Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Berk, Michael, Bjedov, Sarah, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Abud, Indira Indiana Cabrera, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, De Berardis, Domenico, Delgado, Sergio Zamora, De Lucena, David, De Sousa, Avinash, Di Stefano, Ramona, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Maria Paz, Gonda, Xenia, Gondek, Tomasz M., González, Daniela Morera, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, Tasdik M., Hashim, Nurul Azreen, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Kafali, Helin Yilmaz, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kosenko, Korneliia, Koupidis, Sotirios A., Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Malik, Najma Iqbal, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Martínez, Xarah Elenne Meza, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Da Costa, Mariana Pinto, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Ramírez, Francisca Vargas, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Flores, Elena Ninoska Reyes, Rivera-Encinas, María Teresa, Saiz, Pilar, de Carmona, Manuel Sánchez, Martínez, David Saucedo, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, and Smirnova, Daria

Published
2024
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16. Short-term air traffic flow and capacity management measures in multi-airport systems

Author

Amaro Carmona, Manuel Angel, Saez Nieto, Francisco, and Jia, Huamin

Subjects
Dynamic demand and capacity balancing (dDCB), air traffic management (ATM), trajectory-based operations (TBO), terminal manoeuvring area (TMA), airspace resources, deviation
Abstract

Dynamic Demand and Capacity Balancing (dDCB) focuses on reducing the existent gap between the Air Traffic Flow and Capacity Management (ATFCM) and the Air Traffic Control (ATC) activities by introducing a more dynamic management of the airspace resources. This dynamism could be achieved by the application of Short-Term ATFCM Measures (STAM) that consists of detecting potential hotspots, identifying the flights producing the complexity, and applying minor changes to selected flights. This thesis presents a research about the application of STAM in a Multi-Airport System (MAS). Firstly, it is proposed an Operational Concept (OpsCon) designed to apply those STAMs that suggest changes in the take-off time of selected flights (temporal displacements in the planned trajectory). The operational concept is tested by real-time simulations (including the human- in-the-loop) with the objective of evaluating the performance of the ground ATCOs while dealing with most of the uncertainties produced before take-off. Subsequently, it is proposed a methodology that characterizes and evaluates the performance of the aircraft operation in a complex systemized TMA based on the study of its standard routes and their actual traffic in order to reduce the uncertainties after take-off. The process is composed of two main components. The first component identifies recurrent deviation patterns by comparing the Spatio-Temporal (S-T) differences between the actual and planned trajectories. The second component identifies and characterizes concurrence events based on the analysis of the standard routes and the along-track deviation derived from the first component with the objective to analyse the causes that produce recurrent patterns in the terminal airspace. The developed framework is applied to a study case of a representative MAS. The quantitative effectiveness of the framework is derived by simulations using historical traffic data samples of the London TMA.

Published
2019

18. The effect of different degrees of lockdown and self-identified gender on anxiety, depression and suicidality during the COVID-19 pandemic: Data from the international COMET-G study.

Author

Fountoulakis, Konstantinos N., Karakatsoulis, Grigorios N., Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Berk, Michael, Bjedov, Sarah, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Abud, Indira Indiana Cabrera, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, De Berardis, Domenico, Delgado, Sergio Zamora, De Lucena, David, De Sousa, Avinash, Stefano, Ramona Di, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Maria Paz, Gonda, Xenia, Gondek, Tomasz M., González, Daniela Morera, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, Tasdik M., Hashim, Nurul Azreen, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Kafali, Helin Yilmaz, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kopishinskaia, Svetlana, Kosenko, Korneliia, Koupidis, Sotirios A., Kovacs, Illes, Kulig, Barbara, Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Malik, Najma Iqbal, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Martínez, Xarah Elenne Meza, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Da Costa, Mariana Pinto, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Ramírez, Francisca Vargas, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Flores, Elena Ninoska Reyes, Rivera-Encinas, María Teresa, Saiz, Pilar, de Carmona, Manuel Sánchez, Martínez, David Saucedo, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vrublevska, Jelena, Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, Prezerakos, Panagiotis E., and Smirnova, Daria

Published
2022
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20. Results of the COVID-19 mental health international for the general population (COMET-G) study

Author

Fountoulakis, Konstantinos N, Karakatsoulis, Grigorios, Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Berk, Michael, Bjedov, Sarah, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Abud, Indira Indiana Cabrera, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, De Berardis, Domenico, Zamora Delgado, Sergio, De Lucena, David, De Sousa, Avinash, Stefano, Ramona Di, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Maria Paz, Gonda, Xenia, Gondek, Tomasz M., González, Daniela Morera, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, M. Tasdik, Hashim, Nurul Azreen, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Kafali, Helin Yilmaz, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kopishinskaia, Svetlana, Kosenko, Korneliia, Koupidis, Sotirios A., Kovacs, Illes, Kulig, Barbara, Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Malik, Najma Iqbal, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Martínez, Xarah Elenne Meza, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Pinto Da Costa, Mariana, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Ramírez, Francisca Vargas, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Flores, Elena Ninoska Reyes, Rivera-Encinas, María Teresa, Saiz, Pilar, de Carmona, Manuel Sánchez, Martínez, David Saucedo, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vrublevska, Jelena, Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, Prezerakos, Panagiotis E., and Smirnova, Daria

Published
2022
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24. Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments1.

Author

Fernandez-Carmona, Manuel, Mghames, Sariah, and Bellotto, Nicola

Subjects
HUMAN activity recognition, ANOMALY detection (Computer security), INTELLIGENT sensors, CONGREGATE housing, WAVELET transforms, HUMAN ecology
Abstract

Detecting anomalies in patterns of sensor data is important in many practical applications, including domestic activity monitoring for Active Assisted Living (AAL). How to represent and analyse these patterns, however, remains a challenging task, especially when data is relatively scarce and an explicit model is required to be fine-tuned for specific scenarios. This paper, therefore, presents a new approach for temporal modelling of long-term human activities with smart-home sensors, which is used to detect anomalous situations in a robot-assisted environment. The model is based on wavelet transforms and used to forecast smart sensor data, providing a temporal prior to detect unexpected events in human environments. To this end, a new extension of Hybrid Markov Logic Networks has been developed that merges different anomaly indicators, including activities detected by binary sensors, expert logic rules, and wavelet-based temporal models. The latter in particular allows the inference system to discover deviations from long-term activity patterns, which cannot be detected by simpler frequency-based models. Two new publicly available datasets were collected using several smart-sensors to evaluate the approach in office and domestic scenarios. The experimental results demonstrate the effectiveness of the proposed solutions and their successful deployment in complex human environments, showing their potential for future smart-home and robot integrated services. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Immunomodulatory activity of argentatins A and B isolated from guayule.

Author

Silva-Nolasco, Aniela M., de la Cruz-Morcillo, Miguel A., García-Martínez, M. Mercedes, Zalacain, Amaya, Gálvez, Beatriz G., and Carmona, Manuel

Subjects
TH2 cells, HUMAN stem cells, INSECT growth, MESENCHYMAL stem cells, IMMUNE response
Abstract

Argentatins are secondary metabolites synthesized by guayule (Parthenium argentatum A. Gray) with numerous potential medical applications. In addition to inhibiting insect growth, they are endowed with several pharmacological properties including antimicrobial and antitumorigenic activity. However, their potential as immunomodulators remains unexplored. The aim of the present study was to investigate whether argentatins can modulate the function of the immune system. Human mesenchymal stem cells were treated with argentatins and the production of several anti- and proinflammatory cytokines was evaluated. The effect of argentatins on the polarization of CD4+ T-lymphocytes and macrophages was also assessed. Results demonstrated that argentatins can modulate the production of proinflammatory cytokines and the polarization of cellular phenotypes, including Th2 lymphocytes and M1 macrophages. These findings suggest that argentatins are promising therapeutic agents in autoimmune or allergic diseases, and open new perspectives for the investigation of argentatins in immune response and in the development of more targeted and effective immunomodulatory therapies. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Evaluating Guayule (Parthenium argentatum A. Gray) Germplasm Grown in Spain: Rubber and Resin along Three Production Cycles.

Author

Jara, Francisco Miguel, García-Martínez, María de las Mercedes, López-Córcoles, Horacio, Carrión, María Engracia, Zalacain, Amaya, and Carmona, Manuel

Subjects
GERMPLASM, ALTERNATIVE crops, RUBBER, CROPS, INDUSTRIAL management
Abstract

Rubber and resin are potentially important products of guayule (Parthenium argentatum A. Gray) that can assure the profitability of this crop as an agricultural alternative for the semi-arid areas of central and eastern Spain. This study analyzes, for the first time, the changes in rubber and resin production across 27 guayule accessions (traditional and modern) and along three cycles under the agroclimatic conditions of Castilla-La Mancha, simulating industrial management with a biannual harvest. The rubber content (% of dry mass) increased from 4.2% in one-year-old plants to 6.6% in two-year-old plants, but decreased after harvesting. Contrastingly, the rubber yield doubled in contiguous sampling, reaching a mean of 303.6 kg ha−1, with a maximum yield of 341.2 kg ha−1 after the first harvest. Three patterns of rubber production were established based on the production periods. A similar analysis was performed for resin production, which was heterogeneous across accessions belonging to the same rubber groups. In this case, three independent groups were established to classify the resin accumulation profiles following the same criteria of production periods. Here, we demonstrate that biannual harvesting has the potential to enhance rubber accumulation in summer, although more research is needed for its adaption to current harvesting techniques in this area. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Monogenic early-onset lymphoproliferation and autoimmunity: Natural history of STAT3 gain-of-function syndrome

Author

Leiding, Jennifer W, Vogel, Tiphanie P, Santarlas, Valentine G J, Mhaskar, Rahul, Smith, Madison R, Carisey, Alexandre, Vargas-Hernández, Alexander, Silva-Carmona, Manuel, Heeg, Maximilian, Rensing-Ehl, Anne, Neven, Bénédicte, Hadjadj, Jérôme, Hambleton, Sophie, Ronan Leahy, Timothy, Meesilpavikai, Kornvalee, Cunningham-Rundles, Charlotte, Dutmer, Cullen M, Sharapova, Svetlana O, Taskinen, Mervi, Chua, Ignatius, Hague, Rosie, Klemann, Christian, Kostyuchenko, Larysa, Morio, Tomohiro, Thatayatikom, Akaluck, Ozen, Ahmet, Scherbina, Anna, Bauer, Cindy S, Flanagan, Sarah E, Gambineri, Eleonora, Pachlopnik Schmid, Jana, et al, University of Zurich, and Leiding, Jennifer W

Subjects
2403 Immunology, 10036 Medical Clinic, 2723 Immunology and Allergy, 610 Medicine & health
Published
2023

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