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1,431 results on '"Fatehi, P."'

1. The persian version of the fear-avoidance beliefs questionnaire among iranian post-surgery patients: a translation and psychometrics.

Author: Sharif-Nia, Hamid, Froelicher, Erika, Shafighi, Amir, Osborne, Jason, Fatehi, Reza, Nowrozi, Poorya, and Mohammadi, Bita
Subjects: Avoidance beliefs, Fear-avoidance, Persian, Psychometrics, Reliability, Validity, Humans, Psychometrics, Male, Iran, Female, Adult, Fear, Reproducibility of Results, Middle Aged, Surveys and Questionnaires, Avoidance Learning, Translations, Postoperative Period, Young Adult, Aged
Abstract: INTRODUCTION: Fear-avoidance beliefs (FAB) play a crucial role in the treatment outcomes of post-surgery patients. These beliefs can lead to activity avoidance, increased pain, and decreased quality of life. Therefore, accurately measuring these beliefs in Iranian patients is of significant importance. The Fear-Avoidance Belief Questionnaire (FABQ) is a patient-reported questionnaire that evaluates individuals FAB. Since the validity and reliability of the Persian version of FABQ (FABQ-P) have not been assessed based on the Iranian population and sociocultural contexts, the current study has been implemented to determine the reliability and validity of the FABQ-P among Iranian post-operative patients by translation and psychometric properties. METHODS: This methodological study conducted in 2023, a sample of 400 patients who had undergone surgery were selected using a convenience sampling method. The scale used in the study was translated and its psychometric properties were evaluated through network analysis and assessments of construct validity (including exploratory and confirmatory factor analysis), convergent validity, and discriminant validity. Additionally, the study assessed the internal consistency of the scale. RESULTS: The MLEFA results with Promax and Kaiser Normalization rotation yielded two factors explaining 57.91% of the variance, encompassing 13 items. Also, the model was approved by CFA. Convergent and discriminant validity have been confirmed through the following criteria: Average Variance Extracted (AVE) exceeding 0.5, Composite Reliability (CR) surpassing 0.7, and Heterotrait-Monotrait Ratio of Correlations (HTMT) equating to 0.597. As for reliability, Cronbachs alpha, composite reliability (CR), and MaxR for all constructs were greater than 0.7, demonstrating good internal consistency. CONCLUSION: As demonstrated by the results, the FABQ-P has a satisfactory level of reliability along with authentic validity according to the sociocultural contexts of Iranian post-operative patients.
Published: 2024

2. Deep Learning-Based Weather-Related Power Outage Prediction with Socio-Economic and Power Infrastructure Data

Author: Wang, Xuesong, Fatehi, Nina, Wang, Caisheng, and Nazari, Masoud H.
Subjects: Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract: This paper presents a deep learning-based approach for hourly power outage probability prediction within census tracts encompassing a utility company's service territory. Two distinct deep learning models, conditional Multi-Layer Perceptron (MLP) and unconditional MLP, were developed to forecast power outage probabilities, leveraging a rich array of input features gathered from publicly available sources including weather data, weather station locations, power infrastructure maps, socio-economic and demographic statistics, and power outage records. Given a one-hour-ahead weather forecast, the models predict the power outage probability for each census tract, taking into account both the weather prediction and the location's characteristics. The deep learning models employed different loss functions to optimize prediction performance. Our experimental results underscore the significance of socio-economic factors in enhancing the accuracy of power outage predictions at the census tract level., Comment: Accepted in 2024 IEEE PES General Meeting, Seattle, Washington (PES GM 2024)
Published: 2024

3. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author: Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, 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Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, 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Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.
Published: 2024

4. Understanding plant defense mechanisms: exploring the effects of karrikin, salicylic acid, and humic acid treatments on Eustoma grandiflorum

Author: Haratian, Azin, Mortazaeinezhad, Forogh, Kalateh Jari, Sepideh, and Fatehi, Foad
Published: 2024
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5. Single image super-resolution based on deep networks and wavelet transform

Author: Mohammadi Mofrad, Maryam, Fatehi, Mohammad H., Taghizadeh, Mehdi, and Jamali, Jasem
Published: 2024
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6. Microstructural correlates of olfactory dysfunction in Parkinson’s Disease: a systematic review of diffusion MRI studies

Author: Seyedmirzaei, Homa, Rasoulian, Pegah, Parsaei, Mohammadamin, Hamidi, Majid, Ghanbari, Amin, Soltani Khaboushan, Alireza, Fatehi, Farzad, Kamali, Arash, and Sotoudeh, Houman
Published: 2024
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7. Exploring the impact of recent COVID-19 infection on perfusion and functional parameters derived from gated myocardial perfusion imaging in patients undergoing evaluation for coronary artery disease

Author: Alvandi, Maryam, Shaghaghi, Zahra, Fatehi, Zhino, Naghshtabrizi, Behshad, Mohammadi, Tayeb, and Nikzad, Safoora
Published: 2024
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8. Mechanical characteristics and crack propagation mechanism in rectangular and trapezoidal specimens of excavated pillars with various cavities: experimental and numerical investigations

Author: Sarfarazi, Vahab, Fu, Jinwei, Haeri, Hadi, Abharian, Soheil, Rasekh, Haleh, Behzadinasab, Masoud, and Fatehi Marji, Mohammad
Published: 2024
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9. Improving the tensile strength of reinforced concrete: evaluating the impact of different fiber additives through numerical and experimental analysis

Author: Fu, Jinwei, Sarfarazi, Vahab, Haeri, Hadi, Wang, Zhihao, and Fatehi Marji, Mohammad
Published: 2024
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10. Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study

Author: van Baal, Simon T., Le, Suong T. T., Fatehi, Farhad, Verdejo-Garcia, Antonio, and Hohwy, Jakob
Published: 2024
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11. Slow manifold analysis of modified burst model in the saccadic system

Author: Mousavinejad, F. S. and Nia, M. Fatehi
Published: 2024
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12. The relationship between fatigue, pruritus, and thirst distress with quality of life among patients receiving hemodialysis: a mediator model to test concept of treatment adherence.

Author: Sharif-Nia, Hamid, Marôco, João, Barzegari, Saeed, Sadeghi, Niloofar, Fatehi, Reza, and Froelicher, Erika
Subjects: Fatigue, Hemodialysis, Pruritus, Quality of life, Thirst distress, Treatment adherence, Humans, Quality of Life, Renal Dialysis, Female, Male, Pruritus, Middle Aged, Fatigue, Cross-Sectional Studies, Thirst, Adult, Kidney Failure, Chronic, Aged, Treatment Adherence and Compliance, Iran, Surveys and Questionnaires
Abstract: Hemodialysis is a conservative treatment for end-stage renal disease. It has various complications which negatively affect quality of life (QOL). This study aimed to examine the relationship between fatigue, pruritus, and thirst distress (TD) with QOL of patients receiving hemodialysis, while also considering the mediating role of treatment adherence (TA). This cross-sectional study was carried out in 2023 on 411 patients receiving hemodialysis. Participants were consecutively recruited from several dialysis centers in Iran. Data were collected using a demographic information form, the Fatigue Assessment Scale, the Thirst Distress Scale, the Pruritus Severity Scale, the 12-Item Short Form Health Survey, and the modified version of the Greek Simplified Medication Adherence Questionnaire for Hemodialysis Patients. Covariance-based structural equation modeling was used for data analysis. The structural model and hypothesis testing results showed that all hypotheses were supported in this study. QOL had a significant inverse association with fatigue, pruritus, and TD and a significant positive association with TA. TA partially mediated the association of QOL with fatigue, pruritus, and TD, denoting that it helped counteract the negative association of these complications on QOL. This model explained 68.5% of the total variance of QOL. Fatigue, pruritus, and TD have a negative association with QOL among patients receiving hemodialysis, while TA reduces these negative associations. Therefore, TA is greatly important to manage the associations of these complications and improve patient outcomes. Healthcare providers need to assign high priority to TA improvement among these patients to reduce their fatigue, pruritus, and TD and improve their QOL. Further studies are necessary to determine the most effective strategies for improving TA and reducing the burden of complications in this patient population.
Published: 2024

13. In the Line of Fire: A Systematic Review and Meta-Analysis of Job Burnout Among Nurses

Author: Kooktapeh, Zahra Ghasemi, Dustmohammadloo, Hakimeh, Mehrdoost, Hooman, and Fatehi, Farivar
Subjects: Economics - General Economics
Abstract: Using a systematic review and meta-analysis, this study investigates the impact of the COVID-19 pandemic on job burnout among nurses. We review healthcare articles following the PRISMA 2020 guidelines and identify the main aspects and factors of burnout among nurses during the pandemic. Using the Maslach Burnout questionnaire, we searched PubMed, ScienceDirect, and Google Scholar, three open-access databases, for relevant sources measuring emotional burnout, personal failure, and nurse depersonalization. Two reviewers extract and screen data from the sources and evaluate the risk of bias. The analysis reveals that 2.75% of nurses experienced job burnout during the pandemic, with a 95% confidence interval and rates varying from 1.87% to 7.75%. These findings emphasize the need for interventions to address the pandemic's effect on job burnout among nurses and enhance their well-being and healthcare quality. We recommend considering individual, organizational, and contextual factors influencing healthcare workers' burnout. Future research should focus on identifying effective interventions to lower burnout in nurses and other healthcare professionals during pandemics and high-stress situations.
Published: 2023

14. Gemini: A Family of Highly Capable Multimodal Models

Author: Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract: This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
Published: 2023

15. Oxalic acid-mediated oxidative depolymerization of kraft lignin for vanillin and vanillic acid production

Author: Sutradhar, Shrikanta, Kang, Kang, and Fatehi, Pedram
Published: 2024
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16. Assessing the Tensile Crack Growth in Rock Involves Employing a Seesawing Apparatus and its Calibrating Through XFEM: A New Approach

Author: Haeri, Hadi, Sarfarazi, Vahab, Ebneabbasi, Pouyan, and Fatehi Marji, Mohammad
Published: 2024
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17. Application of Mesenchymal Stem Cells and Exosome alone or Combination Therapy as a Treatment Strategy for Wound Healing

Author: Nouri, Soheil, Shokraneh, Shahram, Fatehi Shalamzari, Paradise, Ahmed, Mareb Hamed, Radi, Usama Kadem, Idan, Ameer Hassan, Ebrahimi, Mohammad Javad, Moafi, Maral, and Gholizadeh, Nasim
Published: 2024
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18. A Finite Element Analysis of the Effects of TADAS Dampers on the Frame Members’ Performances in Concrete Structures Under Cyclic and Monotonic Loadings

Author: Haeri, Hadi, Talehjerdi, Ahmad Guodarzi, Sarfarazi, Vahab, Moayer, Ali, and Marji, Mohammad Fatehi
Published: 2024
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19. Phenotyping variability and detecting informative SSR and EST-SSR markers for malt and straw quality characteristics in a diverse panel of wild barley (H. spontaneum) under rainfed and irrigated conditions

Author: Shirvani, Hooman, Mehrabi, Ali Ashraf, Farshadfar, Mohsen, Safari, Hooshmand, Arminian, Ali, and Fatehi, Foad
Published: 2024
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20. Rock joint filling breakage under three different instant loading conditions; physical test and PFC simulation

Author: Zhou, Lei, Sarfarazi, Vahab, Haeri, Hadi, Shahbazian, Armin, Moayedi Far, Arsham, and Fatehi Marji, Mohammad
Published: 2024
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21. An interaction network approach predicts protein cage architectures in bionanotechnology

Author: Fatehi, Farzad and Twarock, Reidun
Subjects: Quantitative Biology - Quantitative Methods
Abstract: Protein nanoparticles play pivotal roles in many areas of bionanotechnology, including drug delivery, vaccination and diagnostics. These technologies require control over the distinct particle morphologies that protein nanocontainers can adopt during self-assembly from their constituent protein components. The geometric construction principle of virus-derived protein cages is by now fairly well understood by analogy to viral protein shells in terms of Caspar and Klug's quasi-equivalence principle. However, many artificial, or genetically modified, protein containers violate this principle, because identical protein subunits do not interact in quasi-equivalent ways, leading to gaps in the particle surface. We introduce a method that exploits information on the local interactions between the assembly units, called capsomers, to infer the geometric construction principle of these nanoparticle architectures. The predictive power of this approach is demonstrated here for a prominent system in nanotechnology, the AaLS pentamer. Our method not only rationalises hitherto discovered cage structures, but also predicts geometrically viable options that have not yet been observed. The classification of nanoparticle architecture based on the geometric properties of the interaction network closes a gap in our current understanding of protein container structure and can be widely applied in protein nanotechnology, paving the way to programmable control over particle polymorphism., Comment: 22 pages, 13 figures
Published: 2023

22. Clinical application of next generation sequencing for Mendelian disease diagnosis in the Iranian population

Author: Abolhassani, Ayda, Fattahi, Zohreh, Beheshtian, Maryam, Fadaee, Mahsa, Vazehan, Raheleh, Ahangari, Fatemeh, Dehdahsi, Shima, Faraji Zonooz, Mehrshid, Parsimehr, Elham, Kalhor, Zahra, Peymani, Fatemeh, Mozaffarpour Nouri, Maryam, Babanejad, Mojgan, Noudehi, Khadijeh, Fatehi, Fatemeh, Zamanian Najafabadi, Shima, Afroozan, Fariba, Yazdan, Hilda, Bozorgmehr, Bita, Azarkeivan, Azita, Sadat Mahdavi, Shokouh, Nikuei, Pooneh, Fatehi, Farzad, Jamali, Payman, Ashrafi, Mahmoud Reza, Karimzadeh, Parvaneh, Habibi, Haleh, Kahrizi, Kimia, Nafissi, Shahriar, Kariminejad, Ariana, and Najmabadi, Hossein
Published: 2024
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23. Assessing the validity and reliability of the 10-item Persian version of the perceived stress scale in post-surgery patients.

Author: Sharif-Nia, Hamid, Froelicher, Erika, Hoseinzadeh, Esmail, Kaveh, Omolhoda, Fatehi, Reza, and Nowrozi, Poorya
Subjects: Iran, perceived stress, psychometrics, reliability, validity
Abstract: INTRODUCTION: The 10-item Perceived Stress Scale (PSS-10) is commonly used to measure stress levels in postoperative patients, as research shows that high levels of stress can affect postoperative outcomes. By using the PSS-10, healthcare providers can understand patients psychological well-being before and after surgery, helping improve recovery and overall health. This study focuses on assessing the reliability and validity of the 10-item Persian version of the PSS (PSS-10-P) in postoperative patients. METHODS: In a methodological study conducted between October to December 2023, a sample of 400 patients who had undergone surgery in 17 Shahrivar Hospital, Amol, Iran were selected using a convenience sampling method. The PSS-10 scale utilized in the study was translated, and its psychometric properties were evaluated through assessments of construct validity, including exploratory (n = 200) and confirmatory (n = 200) factor analysis, convergent validity, and discriminant validity. Furthermore, the study examined the internal consistency of the scale to ensure its reliability. RESULTS: The mean age of the participants was 44.38 (SD= 13.49) years. The results of exploratory factor analysis with Promax rotation extracted two factors accounting for 83.82% of the variance comprising 10 items. After necessary modifications during CFA, the final model was approved. As for reliability, the Cronbachs alpha, CR, and MaxR for all constructs were greater than 0.7, demonstrating good internal consistency and construct reliability. CONCLUSION: According to these results, the Persian version of PSS-10 has a valid structure and acceptable reliability. This scale can be used by health professionals in many ways.
Published: 2024

24. Purification Processes for Generating Cationic Lignin-Acrylamide Polymers

Author: Xiaoqi Wang, Weijue Gao, Fangong Kong, and Pedram Fatehi
Subjects: Chemistry, QD1-999
Published: 2024
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25. Comparative efficacy of oral and vaginal probiotics in reducing the recurrence of bacterial vaginosis: a double-blind clinical trial

Author: Mahnaz Boroumand Rezazadeh, Minoo Zanganeh, Lida Jarahi, and Zahra Fatehi
Subjects: Bacterial vaginosis, Probiotics, Recurrence, Adjuvant treatment, Gynecology and obstetrics, RG1-991, Public aspects of medicine, RA1-1270
Abstract: Abstract Objective The primary goal of this study is to discern the optimal adjuvant treatment for patients diagnosed with bacterial vaginosis, focusing on reducing recurrence rates. Methods This study is a double-blind clinical trial with no previous similar trials conducted to date. The study population consisted of non-pregnant, married women visiting teaching hospitals’ clinics in Mashhad, complaining of vaginal discharge. After informed consent and questionnaire completion, samples were obtained from vaginal discharge surrounding the cervix of clinically diagnosed bacterial vaginosis patients. Using Gram staining, a gold standard method for bacterial vaginosis diagnosis, samples were examined under a microscope according to the Nugent score. After initial treatment with metronidazole, patients were divided into two groups receiving either vaginal or oral probiotics. Results Of the 55 participating women, 20 were in the vaginal probiotic group and 35 were in the oral probiotic group. No significant demographic or clinical differences existed between groups at baseline. The Nugent score decreased from 8.5 to 3 in the vaginal group and from 9 to 3 in the oral group, suggesting the effectiveness of both treatments. While the difference between groups was not statistically significant, each group showed significant improvements from their initial states (p-value
Published: 2024
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26. Fixed versus flexible gonadotropin releasing hormone antagonist protocol in women with polycystic ovary syndrome undergoing in vitro fertilization: An RCT

Author: Hanieh Fatehi, Robab Davar, Elham Nikfarjam, and Fatemeh Bayati
Subjects: gonadotropin-releasing hormone, polycystic ovary syndrome, fertilization in vitro, oocytes., Gynecology and obstetrics, RG1-991, Reproduction, QH471-489
Abstract: Background: Despite the extensive use of the gonadotropin-releasing hormone (GnRH) antagonist protocol in treating infertile women, particularly those with polycystic ovary syndrome (PCOS), there have not been sufficient evidence to compare the flexible and fixed variants in in vitro fertilization (IVF) cycles. Objective: This study aims to assess the treatment outcomes of flexible and fixed types of GnRH-antagonist protocol for IVF in women with PCOS. Materials and Methods: In this randomized clinical trial, 150 infertile women with PCOS, who were candidates for IVF, and referred to the Yazd Research and Clinical Center for Infertility, Yazd, Iran between October 2023 and February 2024 were included. Participants were divided into 2 groups (n = 75/each) based on the type of antagonist protocol (fixed or flexible). GnRH antagonist administration started on the 5 th day of gonadotropin treatment in the fixed group. In the flexible group when there was at least one follicle 12–14 mm, GnRH antagonist was started. Finally, the number of metaphase II oocyte, the quality of embryos, the duration of the stimulation cycle, the dose of gonadotropin, the number of GnRH-antagonist, and the rate of ovarian hyperstimulation syndrome were evaluated. Results: No statistically significant difference was observed in terms of cycle length and the total dose of gonadotropin between groups. Nevertheless, a notable distinction was observed in the total number of oocytes (17.84 vs. 15.5, p = 0.023) and mature oocytes (13.64 vs. 11.83, p = 0.019) in the flexible group compared to the fixed group. Conclusion: In conclusion, the IVF outcomes are more favorable in women with PCOS undergoing the flexible GnRH-antagonist protocol compared to the fixed protocol.
Published: 2024
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27. Psychometric Properties of the Short-form-12 Questionnaire of Quality of Life Among Iranian Hemodialysis Patients

Author: Hamid Sharif-Nia, Reza Fatehi, Lida Hosseini, and Poorya Nowrozi
Subjects: reliability, psychometric, validity, short-form-12 questionnaire of quality of life, hemodialysis, Medicine, Medicine (General), R5-920
Abstract: Background and purpose:. The quality of life of patients with chronic kidney failure undergoing hemodialysis is influenced by physical, psychological, and social factors. Accurate assessment of these dimensions using standardized tools is of great importance. This study aimed to determine the psychometric properties of the 12-item Quality of Life Questionnaire in patients undergoing hemodialysis in the Iranian population. Materials and methods: In this cross-sectional study conducted in 2023, 411 hemodialysis patients in Mazandaran were selected through convenience sampling. After translating the Short Form-12 Quality of Life Questionnaire, its psychometric properties were assessed through exploratory factor analysis, network analysis, and confirmatory factor analysis, along with construct validity (convergent and divergent validity). Internal consistency was calculated using Cronbach's alpha and McDonald's omega coefficients. Results: The results of the exploratory factor analysis indicated that two factors—physical health status and mental health status—accounted for 44.55% of the variance in the quality of life among hemodialysis patients. Furthermore, confirmatory factor analysis showed that the hypothesized model had a good fit (CFI= 0.930, IFI= 0.931, RFI= 0.936, TLI= 0.954). The extracted mental health factor in men demonstrated convergent validity (AVE above 0.5), and both factors exhibited appropriate divergent validity. Ultimately, the internal consistency of the Quality of Life Questionnaire was found to be within an acceptable range (greater than 0.7). Conclusion: The psychometric analysis of the Quality of Life Questionnaire indicates that patients with chronic kidney failure undergoing hemodialysis perceive their quality of life through two primary dimensions: physical and mental health status. This study confirmed the psychometric properties (validity and reliability) and the appropriate factor structure of the Persian version of the Quality of Life Questionnaire for patients undergoing hemodialysis. Healthcare providers can use this tool in various studies to assess and improve the quality of life of hemodialysis patients The use of this questionnaire allows researchers and healthcare professionals to more accurately and comprehensively evaluate the different aspects of quality of life in hemodialysis patients. Employing this tool can enhance treatment processes and improve patient satisfaction, serving as a valuable instrument for future research. This study emphasizes the importance of using valid and reliable tools to assess quality of life and recommends that nurses and other healthcare professionals integrate the Persian version of the 12-item Quality of Life Questionnaire into their treatment and research programs to help improve the quality of life of hemodialysis patients and achieve better treatment outcomes. Future studies are recommended to investigate the impact of factors such as nutrition, social support, and rehabilitation programs on the quality of life of hemodialysis patients. Additionally, utilizing this questionnaire in different populations and therapeutic contexts can contribute to the generalizability of the findings and offer a more effective tool for quality of life assessments. Overall, the findings of this study indicate that the 12-item Quality of Life Questionnaire is a reliable and valid tool for assessing the quality of life in hemodialysis patients, making it valuable for both research and clinical programs. Using this tool can help improve patients' quality of life and treatment outcomes while providing essential data for clinical decision-making.
Published: 2024

28. The Persian version of the fear of pain questionnaire mong Iranian post-surgery patients: a translation and psychometrics

Author: Hamid Sharif-Nia, Erika Sivarajan Froelicher, Reza Fatehi, Poorya Nowrozi, Amir Hossein Shafighi, and Bita Mohammadi
Subjects: Fear of pain, Validity, Reliability, Psychometrics, Persian, Iran, Psychology, BF1-990
Abstract: Abstract Introduction The Fear of Pain Questionnaire (FOPQ) is a self-report tool designed to measure an individual’s fear of pain (FOP). While the Persian version of the FOPQ (FOPQ-P) has been developed, its validity and reliability have not yet been assessed in the Iranian context. This study aims to evaluate the psychometric properties of the FOPQ-P among Iranian patients after surgery. Methods A methodological study was conducted in 2023 involving 400 post-surgery patients selected with a convenience sampling. The FOPQ was translated into Persian, and its psychometric properties were analyzed using network analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), as well as assessments of convergent and discriminant validity. Internal consistency was measured using Cronbach’s alpha, McDonald’s Omega, average inter-item correlation coefficient, Composite Reliability, and Maximal Reliability. Results The EFA results with Promax and Kaiser Normalization rotation identified two factors that explained 54.32% of the variance, comprising seven items. The CFA confirmed the model’s validity. Both convergent and discriminant validity were established. The reliability analyses showed that Cronbach’s alpha, McDonald’s omega, composite reliability, and MaxR for all constructs were above 0.7. Additionally, the average inter-item correlation coefficient was greater than 0.5, indicating strong internal consistency and construct reliability. Conclusion The findings suggest that the FOPQ-P possesses a valid structure and was acceptable reliability in patients cultural context of Iran post-surgery, making it a suitable instrument for measuring fear of pain in this population.
Published: 2024
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29. Temperature Dependent Failure of Atomically Thin MoTe2

Author: Haider, A S M Redwan, Hezam, Ahmad Fatehi Ali Mohammed, Islam, Md Akibul, Arafat, Yeasir, Ferdaous, Mohammad Tanvirul, Salehin, Sayedus, and Karim, Md. Rezwanul
Subjects: Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Classical Physics
Abstract: In this study, we systematically investigated the mechanical responses of monolayer molybdenum ditelluride (MoTe2) using molecular dynamics (MD) simulations. The tensile behavior of trigonal prismatic phase (2H phase) MoTe2 under uniaxial strain was simulated in the armchair and zigzag directions. We also investigated the crack formation and propagation in both armchair and zigzag directions at 10K and 300K to understand the fracture behavior of monolayer MoTe2 at different temperatures. The MD simulations show clean cleavage for the armchair direction, and the cracks were numerous and scattered in the case of the zigzag direction. Finally, we investigated the effect of temperature on Young's modulus and fracture stress of monolayer MoTe2. The results show that at a strain rate of 10^-4 ps^-1, the fracture strength of monolayer MoTe2 in the armchair and zigzag directions at 10K is 16.33 GPa (11.43 N/m) and 13.71 GPa (9.46 N/m) under a 24% and 18% fracture strain, respectively. The fracture strength of monolayer MoTe2 in the armchair and zigzag direction at 600K is 10.81 GPa (7.56 N/m) and 10.13 GPa (7.09 N/m) under a 12.5% and 12.47% fracture strain, respectively., Comment: 22 Pages, 7 Figures
Published: 2023

30. Calcium accumulation or iron deposition: Delving into the temporal sequence of amyotrophic lateral sclerosis pathophysiology in the primary motor cortex

Author: Sadegh Ghaderi, Sana Mohammadi, and Farzad Fatehi
Subjects: ALS, calcium, iron, primary motor cortex, QSM, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Amyotrophic lateral sclerosis (ALS) causes progressive motor neuron degeneration, but an in vivo understanding of its early pathology remains limited. A recent study used topographic layer imaging to investigate iron and calcium accumulation in the primary motor cortex (M1) of patients with ALS compared with controls. Despite the preserved cortical thickness, ALS patients showed increased iron in layer 6 and calcium accumulation in layer 5a and the superficial layer. Calcium accumulation was particularly prominent in the low‐myelin borders, potentially preceding the demyelination. This study reveals a novel in vivo pathology in ALS, suggesting that calcium dysregulation may precede iron accumulation and contribute to early M1 cell degeneration. Further investigation using quantitative susceptibility mapping and complementary techniques, such as diffusion kurtosis imaging, along with ultrahigh‐field magnetic resonance imaging, into the role of calcium and early intervention strategies is warranted.
Published: 2024
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31. The Persian version of the fear of pain questionnaire mong Iranian post-surgery patients: a translation and psychometrics

Author: Sharif-Nia, Hamid, Froelicher, Erika Sivarajan, Fatehi, Reza, Nowrozi, Poorya, Shafighi, Amir Hossein, and Mohammadi, Bita
Published: 2024
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32. Regional citrate anticoagulation with continuous renal replacement therapy as a cause of hypercalcemia

Author: Needleman, Leor, Hughes, Michael S., Fatehi, Pedram, and Sellmeyer, Deborah E.
Published: 2024
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33. The association between physical activity and risk of gastric cancer; an umbrella review

Author: Maleki, Mahsa, Fatehi, Vahid, and Mohammadzadeh, Zeinab
Published: 2024
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34. The awareness of treatment plans of craniosynostosis: guideline for patient and family version

Author: Aminmansour, Bahram, Fatehi, Samaneh, Mokhtari, Ali, Riazi, Ali, and Tehrani, Donya Sheibani
Published: 2024
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35. Investigation of the morphological, physiological, biochemical, and catabolic characteristics and gene expression under drought stress in tolerant and sensitive genotypes of wild barley [Hordeum vulgare subsp. spontaneum (K. Koch) Asch. & Graebn.]

Author: Shirvani, Hooman, Mehrabi, Ali Ashraf, Farshadfar, Mohsen, Safari, Hooshmand, Arminian, Ali, Fatehi, Foad, Pouraboughadareh, Alireza, and Poczai, Peter
Published: 2024
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36. COLQ-Congenital myasthenic syndrome in an Iranian cohort: the clinical and genetics spectrum

Author: Hesami, Omid, Ramezani, Mahtab, Ghasemi, Aida, Fatehi, Farzad, Okhovat, Ali Asghar, Ziaadini, Bentolhoda, Kariminejad, Ariana, and Nafissi, Shahriar
Published: 2024
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37. The effect of using a sports application on the quality of sleep in patients with heart failure: a randomized clinical trial study

Author: Arezomand, Mohsen, Dehghan, Mahlagha, Rigi, Zahra Ebrahimi, Fatehi, Farhad, and Shahrbabaki, Parvin Mangolian
Published: 2024
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38. Putamen iron quantification in diseases with neurodegeneration: a meta-analysis of the quantitative susceptibility mapping technique

Author: Mohammadi, Sana, Ghaderi, Sadegh, and Fatehi, Farzad
Published: 2024
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39. Effect of Nasal Inhalation on Drug Particle Deposition and Size Distribution in the Upper Airway: With Soft Mist Inhalers

Author: Sadeghi, Taha, Fatehi, Pedram, and Pakzad, Leila
Published: 2024
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40. Premature Ventricular Contractions Detection by Multi-Domain Feature Extraction and Auto-Encoder-based Feature Reduction

Author: Ebrahimpoor, Maryam, Taghizadeh, Mehdi, Fatehi, Mohammad Hossein, Mahdiyar, Omid, and Jamali, Jasem
Published: 2024
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41. Multi-agent based optimal UAV deployment for throughput maximization in 5 G communications

Author: Baghnoi, Farjam Mohammadi, Jamali, Jasem, Taghizadeh, Mehdi, and Fatehi, Mohammah Hossein
Published: 2024
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42. Pollination of the Mediterranean Fig Tree, Ficus Carica L.: Caprification Practices and Social Networks of Exchange of Caprifigs among Jbala Farmers in Northern Morocco

Author: Hmimsa, Y., Ramet, A., Dubuisson, C., El Fatehi, S., Hossaert-McKey, M., Kahi, H., Munch, J., Proffit, M., Salpeteur, M., and Aumeeruddy-Thomas, Y.
Published: 2024
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43. The CompactLight Design Study

Author: D’Auria, G., Adli, E., Aicheler, M., Aksoy, A., Alesini, D., Apsimon, R., Arnsberg, J., Auchettl, R., Bainbridge, A., Balazs, K., Bantekas, D., Bedolla, J., Behtouei, M., Bellaveglia, M., vd Berg, M., Bernhard, A., Bignami, A., Breitenbach, M., Breukers, M., Burt, G., Cai, J., Calvi, M., Cardelli, F., Carpanese, M., Cortes, H. M. Castaneda, Castilla, A., Cianchi, A., Clarke, J., Cowie, L., Croia, M., Cross, A., Danailov, M., Dattoli, G., Deleval, S., Mitri, S. Di, Diomede, M., Dowd, R., Dunning, D., Easton, J., Fang, W., Fatehi, S., Faus-Golfe, A., Ferianis, M., Ferrario, M., Ficcadenti, L., Gallo, A., Gazis, E., Gazis, N., Geometrante, R., Gethmann, J., Gioppo, R., Giribono, A., González-Iglesias, D., Goryashko, V., Grohmann, S., Gu, Q., Han, Y., Hinton, A., Hobi, A., Hoekstra, R., Huang, X., Jacewicz, M., Jones, J., Kaertner, F., Karagiannaki, A., Kokole, M., Kotitsa, R., Kotsopoulos, D., Krasch, B., Latina, A., Lepercq, P., Liu, X., Lucas, T. G., Luiten, O. J., Maheshwari, M., Mahnic, J., Mak, A., Marcos, J., Marin, E., Marinov, K., Martínez, B. G., Mercier, B., Migliorati, M., Milharcic, T., Mostacci, A., Mu noz, R., Musat, V., Mutsaers, P. H. A., Nergiz, Z., Nguyen, F., Nix, L., Palumbo, L., Parodi, M., Pavlica, R., Pellegrino, L., Pereira, D. E., Perez, F., Petralia, A., Piersanti, L., Pockar, J., Pramatari, K., Priem, H., Primozic, U., Rassool, R., Reiche, S., Revilak, P., Richter, S. C., Rochow, R., Rossi, C., Salén, P., Schmidt, T., Schoerling, D., Schulte, D., Scifo, J., Sheehy, S., Shepherd, B., Spataro, B., Stapnes, S., Stragier, X. F. D., Syratchev, I., Tabacco, C., Tan, J., Tanke, E., Taylor, G., Telahi, I., Thompson, N., Trachanas, E., Tzanetou, K. S., Vaccarezza, C., Vainola, J., Vannozzi, A., Volpi, M., Wang, C., Williams, P., Wu, X., Wuensch, W., Yap, J., Zangrando, M., Zhang, K., Zhang, L., Zhao, Y., Zhao, Z., and Zhu, D.
Published: 2024
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44. Assessment of quality of life in thyroid cancer patients using the EORTC thyroid-specific questionnaire: a prospective cross-sectional study

Author: Thiagarajan, Shivakumar, Fatehi, Khuzema, Menon, Nandini, Sawant, Mahesh, and Pal, Ankita
Published: 2024
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45. Synthesis of γ-Al2O3–CeO2 catalyst with high surface area, high stability, and less coke formation for methanol dehydration reaction process

Author: Fatehi Haghighat, Mohammad, Mortazavi-Manesh, Anahita, Hashemi Dehkordi, Seyedeh Afagh, Goshtasbi Hassanabadi, Parnian, Bahadoran, Farzad, and Safari, Nasser
Published: 2024
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46. Improving the Efficiency of Automatic Cardiac Arrhythmias Classification by a Novel Patient-Specific Feature Space Mapping

Author: Shafaatfar, Hamid, Taghizadeh, Mehdi, Valizadeh, Morteza, and Fatehi, Mohammad Hossein
Published: 2024
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47. Deep learning and classic machine learning models in the automatic diagnosis of multiple sclerosis using retinal vessels

Author: Yaghoubi, Neda, Masumi, Hassan, Fatehi, Mohammad Hossein, Ashtari, Fereshteh, and Kafieh, Rahele
Published: 2024
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48. Clinical and genetic features of patients suffering from CMT4J

Author: Beloribi-Djefaflia, Sadia, Morales, Raul Juntas, Fatehi, Farzad, Isapof, Arnaud, Servais, Laurent, Leonard-Louis, Sarah, Michaud, Maud, Verdure, Pierre, Gidaro, Teresa, Pouget, Jean, Poinsignon, Vianney, Bonello-Palot, Nathalie, and Attarian, Shahram
Published: 2024
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49. A Critical Evaluation of a Self-Driving Laboratory for the Optimization of Electrodeposited Earth-Abundant Mixed-Metal Oxide Catalysts for the Oxygen Evolution Reaction (OER)

Author: Fatehi, Erfan, Thadani, Manish, Birsan, Gabriel, and Black, Robert W
Subjects: Physics - Applied Physics, Condensed Matter - Materials Science
Abstract: This work highlights the potential of earth-abundant mixed-metal oxide catalysts for the acid-based oxygen evolution reaction. These catalysts offer numerous combinations of metal-centre compositions, which can enhance catalytic activity and stability compared to precious-metal-based catalysts commonly used today. Despite substantial research in this field, there is a need for new methods and approaches to accelerate the exploration of these materials. In this study, we present a comprehensive approach to designing, developing, and implementing a self-driving laboratory to optimize the electrodeposition synthesis of amorphous mixed-metal oxide catalysts for the acidic oxygen evolution reaction. We particularly emphasize the development of methodologies to address experimental variability. We investigate crucial parameters and considerations when transitioning from manual bench-top synthesis and evaluation to automation and machine learning guided optimization. We address both experimental and optimization algorithm considerations in the presence of experimental variability. To illustrate our approach, we demonstrate the optimization of CoFeMnPbOx electrodeposited catalyst materials through multiple campaigns. Our results highlight considerations for optimizing overpotential and stability based on the outcomes of our experiments., Comment: 46 pages, 8 main body figures, 11 supporting information figures
Published: 2023

50. A new approach to simulating stochastic delayed systems

Author: Fatehi, F., Kyrychko, Y. N., and Blyuss, K. B.
Subjects: Nonlinear Sciences - Chaotic Dynamics, Mathematics - Probability, Physics - Chemical Physics
Abstract: In this paper we present a new method for deriving It\^{o} stochastic delay differential equations (SDDEs) from delayed chemical master equations (DCMEs). Considering alternative formulations of SDDEs that can be derived from the same DCME, we prove that they are equivalent both in distribution, and in sample paths they produce. This allows us to formulate an algorithmic approach to deriving equivalent It\^{o} SDDEs with a smaller number of noise variables, which increases the computational speed of simulating stochastic delayed systems. The new method is illustrated on a simple model of two interacting species, and it shows excellent agreement with the results of direct stochastic simulations, while also demonstrating a much superior speed of performance., Comment: 15 pages, 3 figures
Published: 2023
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