177 results on '"Zein, E"'
Search Results
2. A new automatic geo-electric self-potential imaging technique for diverse sustainable development scenarios
- Author
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Mahmoud Elhussein and Zein E. Diab
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Self-potential ,Imaging ,Local wavenumber ,Geothermal exploration ,Mineral exploration ,Medicine ,Science - Abstract
Abstract This study introduces a rapid and efficient inversion algorithm designed for the interpretation of self-potential responses originating from mineralized and ore sources and hydrothermal activity, specifically addressing spherical, vertical, and horizontal cylindrical structures. The algorithm leverages local wavenumber and correlation imaging techniques to enhance accuracy in modeling. The correlation factor (C f value) is crucial in this approach, calculated as the correlation between the local wavenumber of the measured self-potential field and that of the computed field. The algorithm identifies the maximum correlation C f value (C F -max) as indicative of the optimal true model parameters. To validate the proposed algorithm, it was applied to three theoretical examples—one with contamination from regional background and another with multiple sources with and without different types of noises (random Gaussian and white Gaussian noises). Additionally, the approach was tested on three distinct real field cases related to mining, ore investigation and hydrothermal activity in India, Germany and USA. Through a comprehensive analysis of results from theoretical and real-world scenarios, including comparisons with different available data and literature information, the study concludes that the method is effective, applicable to multiple sources, accurate, and does not necessitate prior knowledge of the source shape. This algorithm presents a promising advancement in the field of self-potential interpretation for mineral exploration and geothermal exploration.
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- 2024
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3. A fast imaging method for the interpretation of self-potential data with application to geothermal systems and mineral investigation
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Mehanee, Salah A., Essa, Khalid S., Soliman, Khaled S., and Diab, Zein E.
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- 2023
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4. A fast imaging method for the interpretation of self-potential data with application to geothermal systems and mineral investigation
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Salah A. Mehanee, Khalid S. Essa, Khaled S. Soliman, and Zein E. Diab
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Medicine ,Science - Abstract
Abstract We describe a rapid imaging approach for the interpretation of self-potential data collected along profile by some geometrically simple model of cylinders and spheres. The approach calculates the correlation coefficient between the analytic signal (AS) of the observed self-potential measurements and the AS of the self-potential signature of the idealized model. The depth, electric dipole moment, polarization angle, and center are the inverse parameters we aim to extract from the imaging approach for the interpretative model, and they pertain to the highest value of the correlation coefficient. The approach is demonstrated on noise-free numerical experiments, and reproduced the true model parameters. The accuracy and stability of the proposed approach are examined on numerical experiments contaminated with realistic noise levels and regional fields prior to the interpretation of real data. Following that, five real field examples from geothermal systems and mineral exploration have been successfully analyzed. The results agree well with the published research.
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- 2023
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5. Self-potential data inversion utilizing the Bat optimizing algorithm (BOA) with various application cases
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Essa, Khalid S., Diab, Zein E., and Mehanee, Salah A.
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- 2023
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6. Gravity Data Imaging Using Local Wavenumber-Based Algorithm: Sustainable Development Cases Studies
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Elhussein, Mahmoud and Diab, Zein E.
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- 2023
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7. Magnetic data interpretation for 2D dikes by the metaheuristic bat algorithm: sustainable development cases
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Khalid S. Essa and Zein E. Diab
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Medicine ,Science - Abstract
Abstract Metaheuristic algorithms are increasingly being utilized as a global optimal method in the inversion and modeling of magnetic data. We proposed the Bat Algorithm Optimization (BAO) technique that is based on bat echolocation performance to find the global optimum solution. The best-estimated source parameters that correspond to the objective function minimum value are obtained after achieving the global optimum (best) solution. The suggested BAO technique does not require any prior knowledge; rather, it is a global search method that provides an effective tool for scanning the space of data to appraise sources parameters. The BAO technique is applied to magnetic data in the class of dipping and vertical dikes along 2D profiles to estimate the dimensional source parameters that include the depth to top, origin location, amplitude coefficient, index angle of magnetization, and width of the dipping dikes. The BAO technique has been used for single and multiple dikes structures. The accuracy and stability of the BAO technique are achieved on different synthetic examples of free and noisy data for single and multiple cases. Furthermore, the presented BAO technique was effectively utilized in three field examples from China and Egypt for iron ore deposits and metavolcanics basalt rock investigations. Overall, the BAO technique recovered inversion outcomes are in good agreement with borehole, geology, and published literature results.
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- 2022
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8. Preliminary Site Investigation based on RGB Electromagnetic Energy of Landsat-7 Images in Wadi Fayidah, Saudi Arabia
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Mohammed A. M. Alghamdi and Adel Zein E. A. Bishta
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statistical analysis ,image processing ,structural lineaments ,lithofacies ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Technology (General) ,T1-995 ,Information technology ,T58.5-58.64 - Abstract
In this paper, geostatistical analysis of digital image processing data efficiently contributed to the preliminary site investigation and geotechnical mapping of Wadi Fayidah, Saudi Arabia. 3D modeling, clustering, and chart pattern changes were used to analyze the spectral electromagnetic energy reflected values in red, green, and blue (RGB) ranges on false color composite Landsat-7 images. Therefore, from upstream to downstream, a series of measurements were carried out on a 70km dendritic drainage pattern at 78 stations. Wadi Fayidah was found to have a dominant structural lineament of 56° to 84°. Furthermore, as a preliminary engineering geology mapping, Wadi Fayidah has 9 lithofacies that may differ in engineering geological properties.
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- 2023
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9. Magnetic data interpretation for 2D dikes by the metaheuristic bat algorithm: sustainable development cases
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Essa, Khalid S. and Diab, Zein E.
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- 2022
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10. An automatic inversion approach for magnetic data applying the global bat optimization algorithm (GBOA): application to ore deposits and basement rock intrusion
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Essa, Khalid S. and Diab, Zein E.
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- 2022
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11. Gravity profile interpretation using the R-parameter imaging technique with application to ore exploration
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Essa, Khalid S., Mehanee, Salah A., Soliman, Khaled S., and Diab, Zein E.
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- 2020
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12. Magnetic Data Interpretation Using a New R-Parameter Imaging Method with Application to Mineral Exploration
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Mehanee, Salah, Essa, Khalid S., and Diab, Zein E.
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- 2021
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13. Gravity Data Imaging Using Local Wavenumber-Based Algorithm: Sustainable Development Cases Studies
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Mahmoud Elhussein and Zein E. Diab
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General Environmental Science - Abstract
A fast effective inversion algorithm is proposed herein to interpret gravitational responses caused by mineralized/ore sources (sphere, vertical and horizontal cylinders). The algorithm relies on local wavenumber and correlation imaging techniques. The correlation factor (R) between the local wavenumber of observed gravitational field and that of computed field was calculated, and the maximum Rmax was considered to correspond to the best true model (parameters). The proposed algorithm was applied to two theoretical examples, including an example contaminated with regional background and another multisource example. Besides, the proposed approach was used on three different real field cases for mining/ore investigation from Canada and Cuba. From the results obtained from the theoretical and real examples and by comparing the results with drilling and literature information, it was concluded that the method is effective, is applicable even for more than one source, is accurate, and does not necessitate any prior knowledge of the source shape.
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- 2022
14. Self-potential data inversion utilizing the Bat optimizing algorithm (BOA) with various application cases
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Khalid S. Essa, Zein E. Diab, and Salah A. Mehanee
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Geophysics - Abstract
The Bat optimizing algorithm (BOA) is one of the metaheuristic algorithms and applied here to interpret self-potential (SP) data. The BOA is depending upon a bat echolocation behavior for global optimization, which the global optimum solution reached at the suggested minimum value of the objective function. The best interpretive source parameters for the subsurface structures occurred at the minimal the objective function value (global best solution). The BOA is applied to 2D SP anomaly data to estimate the characteristic source parameters (i.e., the depth to center, amplitude coefficient, origin location, geometric shape factor, and polarization and inclination angle of the causative buried structure). The BOA can be applied to single and multiple source structures in the restricted class of simple geometric shapes, which these bodies help in the validation of the subsurface ore and mineral targets. The stability and efficiency of the proposed BOA have been examined by several synthetic examples. In addition, three different real field examples from Germany and Indonesia have been successfully applied to ore and mineral investigation and geological structure studies. In general, the achieved results are in good agreement with the available borehole data and results mentioned in the literature.
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- 2022
15. Preliminary Site Investigation based on RGB Electromagnetic Energy of Landsat-7 Images in Wadi Fayidah, Saudi Arabia
- Author
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Alghamdi, Mohammed A. M., primary and Bishta, Adel Zein E. A., additional
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- 2023
- Full Text
- View/download PDF
16. Gravity data inversion applying a metaheuristic Bat algorithm for various ore and mineral models
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Essa, Khalid S., primary and Diab, Zein E., additional
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- 2023
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17. Gravity Data Imaging Using Local Wavenumber-Based Algorithm: Sustainable Development Cases Studies
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Elhussein, Mahmoud, primary and Diab, Zein E., additional
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- 2022
- Full Text
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18. Self-potential data inversion utilizing the Bat optimizing algorithm (BOA) with various application cases
- Author
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Essa, Khalid S., primary, Diab, Zein E., additional, and Mehanee, Salah A., additional
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- 2022
- Full Text
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19. Floating power plant applications for electric battery using thermoelectric generators (TEG) on solar panels
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Zein, E, primary, Safril, M, additional, Sutanto, E, additional, Hamid, M I, additional, Aziz, M, additional, and Fahmi, F, additional
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- 2022
- Full Text
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20. Gravity Anomaly Interpretation Using the R-Parameter Imaging Technique over a Salt Dome
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Khalid S. Essa and Zein E. Diab
- Abstract
Rapid imaging technique, so-called “R-parameter”, utilized for interpreting a gravity anomaly profile. The R-parameter based on calculating the correlation factor between the analytic signal of the real anomaly and the analytic signal of the forward anomaly of assumed buried source denoted by simple geometric shapes. The model parameters (amplitude, origin, depth, and shape factor) picked at the maximum value of the R-parameter. The technique has been proved on noise free and noisy numerical example, numerical example showing the impact of interfering sources. Furthermore, the introduced technique has been successfully applied to visualize a salt dome gravity anomaly profile, USA. The obtained results are in good agreement with those reported in the published studies and that with that obtained from drilling.
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- 2022
21. Gravity data inversion applying a metaheuristic Bat algorithm for various ore and mineral models
- Author
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Khalid S. Essa and Zein E. Diab
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Geophysics ,Earth-Surface Processes - Published
- 2023
22. The Global Retinoblastoma Outcome Study: a prospective, cluster-based analysis of 4064 patients from 149 countries
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Alia, DB, Tandili, A, Paiva, L, Wime, AD, Chantada, GL, Fandino, AC, Sgroi, M, Papyan, R, Tamamyan, G, Camuglia, JE, Gole, GA, Clark, A, Lam, GC, Elder, JE, McKenzie, JD, Staffieri, SE, Jones, MM, Manudhane, R, Sia, D, Ritter-Sovinz, P, Schwab, C, Balayeva, R, Khan, Z, Nuruddin, M, Roy, SR, Rashid, R, Sultana, S, Shakoor, SA, Naumenko, L, Zhilyaeva, K, Bartoszek, P, Brichard, BG, De Potter, P, Bio, AIA, Salas, B, Coleoni Suarez, ME, Mbumba, FB, Bonanomi, MTBC, Donato Macedo, CR, Grigorovski, NDAK, Mattosinho, CCDS, Teixeira, LF, Oscar, AH, Veleva-Krasteva, NV, Bouda, GC, Kabore, RL, Philbert, R, Evina, TGA, Nkumbe, HE, Kamsang, P, Muyen, OM, Dimaras, H, Mallipatna, A, Hamel, P, Superstein, R, Paton, KE, Strahlendorf, C, Palet, JEKK, Tyau-Tyau, H, Cavieres, I, Lopez, JP, Oporto, J, Ossandon, D, Chen, W, Xiang, D, Du, Y, Li, K, Ji, X, Tang, J, Li, C, Xu, B, Qian, J, Xue, K, Sun, X, Wang, Y-Z, Zhang, Y, Wu, S-Q, Xiao, Y, Yang, H, Ye, H, Polania, RA, Berete, RC, Couitchere, L, Peric, S, Alemany-Rubio, E, Gonzalez-Rodriguez, L, Autrata, R, Kepak, T, Pochop, P, Svojgr, K, Gregersen, PA, Urbak, SF, Montero, MM, Budiongo, A, Yanga, JM, Amani, TBK, Lukamba, RM, Numbi, MN, Calle Jara, DA, Villacis Chafla, EG, Sanchez, GL, Abouelnaga, S, Afifi, MA, Elhaddad, AM, Ali, AM, Elzembely, M, Said, AMA, Ziko, OAO, Fuentes-Alabi, SL, Goenz, MA, Eerme, K, Klett, A, Hordofa, DF, Mengesha, AA, Sherief, ST, Kivela, TT, Nummi, K, Cassoux, N, Desjardins, L, Obono-Obiang, G, Kardava, T, Khotenashvili, Z, Bechrakis, NE, Biewald, EM, Schlueter, S, Ketteler, P, Amankwaa-Frempong, D, Essuman, VA, Paintsil, V, Renner, LA, Alejos, A, Giron, A, Carreras, YA, Fu, LD, Maldonado, C, Wong, ES, Yam, JC, Csoka, M, Maka, E, Aggarwal, P, Gupta, V, Bhaduri, A, Bhattacharyya, A, Das, A, Chawla, B, Das, P, Das, S, Gupta, H, Gupta, S, Verma, N, Kaliki, S, Khetan, V, Maitra, P, Mahajan, A, Menon, V, Mishra, DKC, Palanivelu, MS, Ramanjulu, R, Mudaliar, SS, Nair, AG, Natarajan, S, Seth, R, Singh, U, Bhat, S, Dudeja, G, Tripathy, D, Akib, IMNR, Pagarra, H, Amiruddin, PO, Kuntorini, MW, Armytasari, I, Supriyadi, E, Sutyawan, IWE, Yuliawati, P, Lutfi, D, Soebagjo, HD, Rahman, A, Sitorus, RS, Victor, AA, Tehuteru, ES, Widiarti, W, Nency, YM, Faranoush, M, Mehrvar, A, Tashvighi, M, Sedaghat, A, Ghassemi, F, Khodabande, A, Abdulqader, RA, Al-Shaheen, AASM, Al Ani, MH, Haydar, H, Al-Badri, SAF, Al-Jadiry, MF, Sabhan, AH, Al-Jumaily, U, Al-Mafrachi, AARM, Al-Shammary, EH, Al-Janabi, ANH, Qadir, AO, Capra, M, Blum, S, Gomel, N, Fabian, ID, Goldberg, H, Kapelushnik, N, Madgar, S, Vishnevskia-Dai, V, Frenkel, S, Pe'er, J, Gorfine, M, Refaeli, D, Steinberg, DM, Lavy, Y, Toledano, H, Caspi, S, De Francesco, S, Hadjistilianou, T, Ida, R, Valente, P, Midena, E, Parrozzani, R, Cowan-Lyn, KE, Vaughan, LO, Suzuki, S, Mohammad, MT, Yousef, YA, Manzhuova, L, Atsiaya, R, Matende, IO, Begimkulova, AS, Makimbetov, EK, Keomisy, J, Sayalith, P, Valeina, S, Viksnins, M, Al-Haddad, CE, Saab, RH, Alsawidi, KM, Elbahi, AM, Krivaitiene, D, Tateshi, B, Randrianarisoa, HL, Raobela, L, Msukwa, G, Nyirenda, C, Hamzah, N, Teh, KH, Sylla, F, Traore, F, Cheikh, SS, Zein, E, Perez, GG, Sanchez Orozco, AJ, Ortega-Hernandez, M, Ramirez-Ortiz, MA, Chuluunbat, T, Abdallah, E, Benmiloud, S, El Kettani, A, Hessissen, L, Almeida, AA, Limbu, B, Rajkarnikar, P, Saiju, R, Moll, AC, Wijsard, MVH, Cockcroft, RL, Ng, Y, Dodgshun, AJ, Calderon-Sotelo, P, Abdullahi, SU, Hassan, S, Umar, AB, Abdulrahaman, AA, Wali, AH, Ademola-Popoola, DS, Adio, A, Aghaji, AE, Ezegwui, IR, Akinsete, A, Musa, KO, Fasina, O, Ibanga, A, Nkanga, ED, Mustapha, T, Ribadu, D, Hummelen, M, Ahmad, A, Mushtaq, A, Qayyum, S, Chaudhry, S, Fadoo, Z, Jeeva, I, Masud, S, Hamid, SA, Zia, N, Siddiqui, SN, Janjua, T, Yaqub, MA, Khaqan, HA, Quintero D, K, Yee, R, Jairaj, V, Cano, MR, Fernandez, DDPG, Diaz Coronado, RY, Zapata Lopez, AM, Garcia, JL, Ponce, J, Garcia Pacheco, HN, Pascual Morales, CR, Vasquez Anchaya, JK, Tarrillo Leiva, FF, Alcasabas, APA, Mercado, GJ, Cieslik, K, Hautz, W, Rogowska, A, Castela, G, Silva, S, Jo, DH, Kim, JH, Comsa, C, Dragomir, MD, Neroev, V, Saakyan, S, Polyakov, V, Ushakova, TL, Yarovaya, VA, Yarovoy, AA, Theophile, T, Al Mesfer, S, Maktabi, A, Al-Dahmash, SA, Alkatan, HM, Moreira, C, Roth, PAN, Ilic, VR, Nikitovic, M, Latinovic, S, Quah, B, Tan, D, Hederova, S, Husakova, K, Groznik, AL, Pompe, MT, Davidson, A, Du Bruyn, M, Du Plessis, J, Stones, DK, Geel, JA, Myezo, KH, Kruger, M, Mayet, I, Naidu, G, Naidu, N, Mustak, H, Reynders, D, Wetter, J, Alarcon Portabella, S, Martin-Begue, N, Wolley Dod, C, Balaguer, J, Barranco, H, Catala-Mora, J, Correa Llano, MG, Fernandez-Teijeiro, A, Garcia Aldana, D, Peralta Calvo, J, San Roman Pacheco, S, Gunasekera, DS, Elhassan, MMA, Mohamedani, AA, All-Eriksson, C, Bartuma, K, Popovic, MB, Munier, FL, Liu, C-H, Chiwanga, FS, Kyara, A, Mndeme, FG, Msina, MS, Scanlan, TA, Atchaneeyasakul, L-O, Buaboonnam, J, Dangboon, W, Singha, P, Hongeng, S, Kulvichit, K, Rojanaporn, D, Surukrattanaskul, S, Wangtiraumnuay, N, Wiwatwongwana, A, Wiwatwongwana, D, Wongwai, P, Sharma, MK, Guedenon, KM, Bouguila, H, Atalay, HT, Hasanreisoglu, M, Ataseven, E, Kantar, M, Gunduz, AK, Kebudi, R, Kiratli, H, Koc, I, Tuncer, S, Unal, E, Kalinaki, A, Matua, M, Waddell, K, Musika, AA, Ssali, G, Al Harby, L, Reddy, MA, Astbury, NJ, Bascaran, C, Bowman, R, Burton, MJ, Foster, A, Zondervan, M, Sagoo, MS, Bobrova, N, Sorochynska, T, Lysytsia, L, Castillo, L, Afshar, AR, Berry, JL, Kim, JW, Randhawa, JK, Binkley, E, Boldt, HC, Larson, SA, Brennan, RC, Chandramohan, A, Stacey, AW, Corson, TW, Plager, DA, Davanzo, JM, Singh, AD, Demirci, H, Ericksen, C, Magrath, GN, Gold, AS, Murray, TG, Gonzalez, E, Shah, AS, Hansen, ED, Hartnett, ME, Harbour, JW, Hubbard, GB, Uner, OE, Laurenti, KD, Mets, MB, Leverant, AA, Ramasubramanian, A, Luna-Fineman, S, Miller, A, Skalet, AH, Mruthyunjaya, P, Hassan, M, Oliver, SC, Shields, CL, Yaghy, A, Stahl, ED, Wilson, MW, Villegas, VM, Islamov, Z, Usmanov, RH, Graells, J, Romero, L, Pham, CTM, Trang, DL, Al-Hussaini, HH, Thawaba, ADM, Muma, KIM, Nyaywa, M, Alia, DB, Tandili, A, Paiva, L, Wime, AD, Chantada, GL, Fandino, AC, Sgroi, M, Papyan, R, Tamamyan, G, Camuglia, JE, Gole, GA, Clark, A, Lam, GC, Elder, JE, McKenzie, JD, Staffieri, SE, Jones, MM, Manudhane, R, Sia, D, Ritter-Sovinz, P, Schwab, C, Balayeva, R, Khan, Z, Nuruddin, M, Roy, SR, Rashid, R, Sultana, S, Shakoor, SA, Naumenko, L, Zhilyaeva, K, Bartoszek, P, Brichard, BG, De Potter, P, Bio, AIA, Salas, B, Coleoni Suarez, ME, Mbumba, FB, Bonanomi, MTBC, Donato Macedo, CR, Grigorovski, NDAK, Mattosinho, CCDS, Teixeira, LF, Oscar, AH, Veleva-Krasteva, NV, Bouda, GC, Kabore, RL, Philbert, R, Evina, TGA, Nkumbe, HE, Kamsang, P, Muyen, OM, Dimaras, H, Mallipatna, A, Hamel, P, Superstein, R, Paton, KE, Strahlendorf, C, Palet, JEKK, Tyau-Tyau, H, Cavieres, I, Lopez, JP, Oporto, J, Ossandon, D, Chen, W, Xiang, D, Du, Y, Li, K, Ji, X, Tang, J, Li, C, Xu, B, Qian, J, Xue, K, Sun, X, Wang, Y-Z, Zhang, Y, Wu, S-Q, Xiao, Y, Yang, H, Ye, H, Polania, RA, Berete, RC, Couitchere, L, Peric, S, Alemany-Rubio, E, Gonzalez-Rodriguez, L, Autrata, R, Kepak, T, Pochop, P, Svojgr, K, Gregersen, PA, Urbak, SF, Montero, MM, Budiongo, A, Yanga, JM, Amani, TBK, Lukamba, RM, Numbi, MN, Calle Jara, DA, Villacis Chafla, EG, Sanchez, GL, Abouelnaga, S, Afifi, MA, Elhaddad, AM, Ali, AM, Elzembely, M, Said, AMA, Ziko, OAO, Fuentes-Alabi, SL, Goenz, MA, Eerme, K, Klett, A, Hordofa, DF, Mengesha, AA, Sherief, ST, Kivela, TT, Nummi, K, Cassoux, N, Desjardins, L, Obono-Obiang, G, Kardava, T, Khotenashvili, Z, Bechrakis, NE, Biewald, EM, Schlueter, S, Ketteler, P, Amankwaa-Frempong, D, Essuman, VA, Paintsil, V, Renner, LA, Alejos, A, Giron, A, Carreras, YA, Fu, LD, Maldonado, C, Wong, ES, Yam, JC, Csoka, M, Maka, E, Aggarwal, P, Gupta, V, Bhaduri, A, Bhattacharyya, A, Das, A, Chawla, B, Das, P, Das, S, Gupta, H, Gupta, S, Verma, N, Kaliki, S, Khetan, V, Maitra, P, Mahajan, A, Menon, V, Mishra, DKC, Palanivelu, MS, Ramanjulu, R, Mudaliar, SS, Nair, AG, Natarajan, S, Seth, R, Singh, U, Bhat, S, Dudeja, G, Tripathy, D, Akib, IMNR, Pagarra, H, Amiruddin, PO, Kuntorini, MW, Armytasari, I, Supriyadi, E, Sutyawan, IWE, Yuliawati, P, Lutfi, D, Soebagjo, HD, Rahman, A, Sitorus, RS, Victor, AA, Tehuteru, ES, Widiarti, W, Nency, YM, Faranoush, M, Mehrvar, A, Tashvighi, M, Sedaghat, A, Ghassemi, F, Khodabande, A, Abdulqader, RA, Al-Shaheen, AASM, Al Ani, MH, Haydar, H, Al-Badri, SAF, Al-Jadiry, MF, Sabhan, AH, Al-Jumaily, U, Al-Mafrachi, AARM, Al-Shammary, EH, Al-Janabi, ANH, Qadir, AO, Capra, M, Blum, S, Gomel, N, Fabian, ID, Goldberg, H, Kapelushnik, N, Madgar, S, Vishnevskia-Dai, V, Frenkel, S, Pe'er, J, Gorfine, M, Refaeli, D, Steinberg, DM, Lavy, Y, Toledano, H, Caspi, S, De Francesco, S, Hadjistilianou, T, Ida, R, Valente, P, Midena, E, Parrozzani, R, Cowan-Lyn, KE, Vaughan, LO, Suzuki, S, Mohammad, MT, Yousef, YA, Manzhuova, L, Atsiaya, R, Matende, IO, Begimkulova, AS, Makimbetov, EK, Keomisy, J, Sayalith, P, Valeina, S, Viksnins, M, Al-Haddad, CE, Saab, RH, Alsawidi, KM, Elbahi, AM, Krivaitiene, D, Tateshi, B, Randrianarisoa, HL, Raobela, L, Msukwa, G, Nyirenda, C, Hamzah, N, Teh, KH, Sylla, F, Traore, F, Cheikh, SS, Zein, E, Perez, GG, Sanchez Orozco, AJ, Ortega-Hernandez, M, Ramirez-Ortiz, MA, Chuluunbat, T, Abdallah, E, Benmiloud, S, El Kettani, A, Hessissen, L, Almeida, AA, Limbu, B, Rajkarnikar, P, Saiju, R, Moll, AC, Wijsard, MVH, Cockcroft, RL, Ng, Y, Dodgshun, AJ, Calderon-Sotelo, P, Abdullahi, SU, Hassan, S, Umar, AB, Abdulrahaman, AA, Wali, AH, Ademola-Popoola, DS, Adio, A, Aghaji, AE, Ezegwui, IR, Akinsete, A, Musa, KO, Fasina, O, Ibanga, A, Nkanga, ED, Mustapha, T, Ribadu, D, Hummelen, M, Ahmad, A, Mushtaq, A, Qayyum, S, Chaudhry, S, Fadoo, Z, Jeeva, I, Masud, S, Hamid, SA, Zia, N, Siddiqui, SN, Janjua, T, Yaqub, MA, Khaqan, HA, Quintero D, K, Yee, R, Jairaj, V, Cano, MR, Fernandez, DDPG, Diaz Coronado, RY, Zapata Lopez, AM, Garcia, JL, Ponce, J, Garcia Pacheco, HN, Pascual Morales, CR, Vasquez Anchaya, JK, Tarrillo Leiva, FF, Alcasabas, APA, Mercado, GJ, Cieslik, K, Hautz, W, Rogowska, A, Castela, G, Silva, S, Jo, DH, Kim, JH, Comsa, C, Dragomir, MD, Neroev, V, Saakyan, S, Polyakov, V, Ushakova, TL, Yarovaya, VA, Yarovoy, AA, Theophile, T, Al Mesfer, S, Maktabi, A, Al-Dahmash, SA, Alkatan, HM, Moreira, C, Roth, PAN, Ilic, VR, Nikitovic, M, Latinovic, S, Quah, B, Tan, D, Hederova, S, Husakova, K, Groznik, AL, Pompe, MT, Davidson, A, Du Bruyn, M, Du Plessis, J, Stones, DK, Geel, JA, Myezo, KH, Kruger, M, Mayet, I, Naidu, G, Naidu, N, Mustak, H, Reynders, D, Wetter, J, Alarcon Portabella, S, Martin-Begue, N, Wolley Dod, C, Balaguer, J, Barranco, H, Catala-Mora, J, Correa Llano, MG, Fernandez-Teijeiro, A, Garcia Aldana, D, Peralta Calvo, J, San Roman Pacheco, S, Gunasekera, DS, Elhassan, MMA, Mohamedani, AA, All-Eriksson, C, Bartuma, K, Popovic, MB, Munier, FL, Liu, C-H, Chiwanga, FS, Kyara, A, Mndeme, FG, Msina, MS, Scanlan, TA, Atchaneeyasakul, L-O, Buaboonnam, J, Dangboon, W, Singha, P, Hongeng, S, Kulvichit, K, Rojanaporn, D, Surukrattanaskul, S, Wangtiraumnuay, N, Wiwatwongwana, A, Wiwatwongwana, D, Wongwai, P, Sharma, MK, Guedenon, KM, Bouguila, H, Atalay, HT, Hasanreisoglu, M, Ataseven, E, Kantar, M, Gunduz, AK, Kebudi, R, Kiratli, H, Koc, I, Tuncer, S, Unal, E, Kalinaki, A, Matua, M, Waddell, K, Musika, AA, Ssali, G, Al Harby, L, Reddy, MA, Astbury, NJ, Bascaran, C, Bowman, R, Burton, MJ, Foster, A, Zondervan, M, Sagoo, MS, Bobrova, N, Sorochynska, T, Lysytsia, L, Castillo, L, Afshar, AR, Berry, JL, Kim, JW, Randhawa, JK, Binkley, E, Boldt, HC, Larson, SA, Brennan, RC, Chandramohan, A, Stacey, AW, Corson, TW, Plager, DA, Davanzo, JM, Singh, AD, Demirci, H, Ericksen, C, Magrath, GN, Gold, AS, Murray, TG, Gonzalez, E, Shah, AS, Hansen, ED, Hartnett, ME, Harbour, JW, Hubbard, GB, Uner, OE, Laurenti, KD, Mets, MB, Leverant, AA, Ramasubramanian, A, Luna-Fineman, S, Miller, A, Skalet, AH, Mruthyunjaya, P, Hassan, M, Oliver, SC, Shields, CL, Yaghy, A, Stahl, ED, Wilson, MW, Villegas, VM, Islamov, Z, Usmanov, RH, Graells, J, Romero, L, Pham, CTM, Trang, DL, Al-Hussaini, HH, Thawaba, ADM, Muma, KIM, and Nyaywa, M
- Abstract
BACKGROUND: Retinoblastoma is the most common intraocular cancer worldwide. There is some evidence to suggest that major differences exist in treatment outcomes for children with retinoblastoma from different regions, but these differences have not been assessed on a global scale. We aimed to report 3-year outcomes for children with retinoblastoma globally and to investigate factors associated with survival. METHODS: We did a prospective cluster-based analysis of treatment-naive patients with retinoblastoma who were diagnosed between Jan 1, 2017, and Dec 31, 2017, then treated and followed up for 3 years. Patients were recruited from 260 specialised treatment centres worldwide. Data were obtained from participating centres on primary and additional treatments, duration of follow-up, metastasis, eye globe salvage, and survival outcome. We analysed time to death and time to enucleation with Cox regression models. FINDINGS: The cohort included 4064 children from 149 countries. The median age at diagnosis was 23·2 months (IQR 11·0-36·5). Extraocular tumour spread (cT4 of the cTNMH classification) at diagnosis was reported in five (0·8%) of 636 children from high-income countries, 55 (5·4%) of 1027 children from upper-middle-income countries, 342 (19·7%) of 1738 children from lower-middle-income countries, and 196 (42·9%) of 457 children from low-income countries. Enucleation surgery was available for all children and intravenous chemotherapy was available for 4014 (98·8%) of 4064 children. The 3-year survival rate was 99·5% (95% CI 98·8-100·0) for children from high-income countries, 91·2% (89·5-93·0) for children from upper-middle-income countries, 80·3% (78·3-82·3) for children from lower-middle-income countries, and 57·3% (52·1-63·0) for children from low-income countries. On analysis, independent factors for worse survival were residence in low-income countries compared to high-income countries (hazard ratio 16·67; 95% CI 4·76-50·00), cT4 advanced tumour compared to
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- 2022
23. Managing the Difficult Soft Tissue Envelope in Facial and Rhinoplasty Surgery
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Kosins, Aaron M. and Obagi, Zein E.
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- 2017
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24. Magnetic Data Interpretation Using a New R-Parameter Imaging Method with Application to Mineral Exploration
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Khalid S. Essa, Salah Mehanee, and Zein E. Diab
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Field (physics) ,Noise (signal processing) ,Mathematical analysis ,010502 geochemistry & geophysics ,01 natural sciences ,Magnetization ,Amplitude ,Interference (communication) ,Simple (abstract algebra) ,SPHERES ,Analytic signal ,0105 earth and related environmental sciences ,General Environmental Science ,Mathematics - Abstract
A new imaging method has been developed for elucidating the observed magnetic data gauged along profile. The method is based on the calculation of the correlation factor (the R-parameter) between the analytic signal of the measured magnetic anomaly and the analytic signal of the calculated response of some geometrically simple interpretive models in the confined category of sheets, cylinders, and spheres. The characteristic parameters (amplitude coefficient, depth, location, approximative shape of the buried structure, and effective angle of magnetization) of the interpretive model correspond to the maximum R-parameter value. The scheme has been verified on a number of noise-free synthetic examples and recovered the actual model parameters. Prior to applying the developed scheme to real-field examples, the accuracy of it has been carefully investigated on synthetic examples which are contaminated with realistic noise levels, interference effects, and regional field. Finally, the method has been successfully applied to three real-field data examples from the USA, Senegal, and Egypt for mineral exploration, and it is found that the obtained results are in good concordance with those obtained from drilling and/or the published literature.
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- 2020
25. Self-potential Data Interpretation for Two Co-axial Structures Utilizing the RMS Parameter
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Zein E. Diab, Khalid S. Essa, and Mahmoud Elhussein
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Geophysics ,Environmental Engineering ,010504 meteorology & atmospheric sciences ,Data interpretation ,Coaxial ,010502 geochemistry & geophysics ,Geotechnical Engineering and Engineering Geology ,01 natural sciences ,Geology ,0105 earth and related environmental sciences ,Computational physics - Abstract
We have developed an algorithm to obtain the model parameters for two co-axial structures from self-potential data. The method uses the first numerical horizontal derivatives calculated from the observed self-potential anomaly employing filters of sequential window lengths (s-values) so as to gauge the model constraints for the shallow and deep structures. In addition, this algorithm uses a standard inversion method for solving a non-linear equation based on the lowest root-mean-square (RMS) error of the estimated model parameters. The body constraints are the depth, polarization angle and electric dipole moment of each structure. Our approach models the self-potential dataset as an aggregation of spheres, horizontal cylinders, and vertical cylinders. These simple bodies are used to approximate, without a priori expectations, the furthermost plausible position and/or area of intersection. In other words, the bodies are used to estimate the true values of the source parameters for the two-co-axial bodies at different s-values. Minimizing the RMS error has the advantage of optimizing all model factors. The proposed technique is tested using a numerical model with and without noise and on self-potential field data acquired at a site in Germany. In all cases, the assessed body parameters are reasonable approximations of the known values.
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- 2020
26. The Art of Skin Health Restoration and Rejuvenation
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Obagi, Zein E., primary
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- 2014
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27. Intrathecal dexmedetomidine versus magnesium sulphate for postoperative analgesia and stress response after caesarean delivery; randomized controlled double‐blind study
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Mohamed F Mostafa, Ahmed K. Ibrahim, Zein E. A. Zareh Hassan, Ragaa Herdan, Ahmed Talaat, Hanan Galal, and Golnar M. Fathy
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medicine.drug_class ,Visual analogue scale ,medicine.medical_treatment ,Sedation ,Magnesium Sulfate ,03 medical and health sciences ,0302 clinical medicine ,Double-Blind Method ,Pregnancy ,medicine ,Humans ,Caesarean section ,030212 general & internal medicine ,Anesthetics, Local ,Dexmedetomidine ,Adverse effect ,Injections, Spinal ,Bupivacaine ,Cesarean Section ,business.industry ,Infant, Newborn ,Anesthesiology and Pain Medicine ,Sedative ,Anesthesia ,Female ,Analgesia ,medicine.symptom ,business ,030217 neurology & neurosurgery ,medicine.drug ,Hormone - Abstract
Background Various adjuvants were added to intrathecal anaesthetics to improve quality of the block and postoperative analgesia. We hypothesized that intrathecal dexmedetomidine and magnesium sulphate (MgSO4 ) may add similar effects. Our objectives were to compare their effects as adjuvants to intrathecal bupivacaine on postoperative analgesia, stress hormones, sedative properties and the neonatal outcome after caesarean section. Methods A randomized double-blind controlled study; 90 parturients were divided into three groups. All patients received intrathecal hyperbaric bupivacaine 12.5 mg. NaCl 0.9% was added to intrathecal block in group C, 5 μg dexmedetomidine in the group D and 50 mg MgSO4 in group M. Visual analogue scale (VAS) score, stress hormones were assessed within the first 12 postoperative hours, sensory block, and neonatal outcome were also assessed. Results VAS scores were significantly lower in groups D and M. Onset of postoperative pain was significantly prolonged in group D. Time to peak sensory level was shorter in group D. Sedation score was significantly higher in group D only after 30 min of intrathecal block. Although stress hormones increased in all groups during intraoperative and postoperative periods, their levels were significantly lower in group D compared to other groups. No differences were noted regarding neonatal outcomes. Conclusion Intrathecal dexmedetomidine is superior to intrathecal MgSO4 during caesarean section with regard to duration of analgesia, pain severity and stress hormone levels. Dexmedetomidine has a rapid onset and longer duration of sensory block compared to MgSO4 . No significant adverse effects to the parturients or newborns.
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- 2019
28. Shallow geophysical techniques to investigate the groundwater table at the Great Pyramids of Giza, Egypt
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Mohamed A. S. Youssef, Sharafeldin M. Sharafeldin, Khalid S. Essa, Zein E. Diab, Nilgün Sayil, and Hakan Karsli
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Hydrology ,Atmospheric Science ,Topographic relief ,geography.geographical_feature_category ,Plateau ,Water table ,lcsh:QC801-809 ,Elevation ,020206 networking & telecommunications ,Geology ,Aquifer ,02 engineering and technology ,Geophysics ,010502 geochemistry & geophysics ,Oceanography ,01 natural sciences ,lcsh:Geophysics. Cosmic physics ,Geography ,0202 electrical engineering, electronic engineering, information engineering ,Seismic refraction ,Electrical resistivity tomography ,Surface runoff ,0105 earth and related environmental sciences - Abstract
The near-surface groundwater aquifer that threatened the Great Pyramids of Giza, Egypt, was investigated using integrated geophysical surveys. A total of 10 electrical resistivity imaging, 26 shallow seismic refraction, and 19 ground-penetrating radar surveys were conducted in the Giza Plateau. Collected data for each method were evaluated by state-of-the art processing and modeling techniques. A three-layer model depicts the subsurface layers and better delineates the groundwater aquifer and water table elevation. The resistivity of the aquifer layer and seismic velocity vary between 40 and 80 Ωm and between 1500 and 2500 m s−1, respectively. The average water table elevation is about +15 m, which is safe for the Great Sphinx, but it is still subjected to potential hazards from the Nazlet El-Samman suburb where the water table elevation reaches 17 m. A shallower water table at the Valley Temple and the tomb of Queen Khentkawes, with a low topographic relief, represents severe hazards. It can be concluded that a perched groundwater table is detected in the elevated topography to the west and southwest that might be due to runoff and capillary seepage.
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- 2019
29. Thermal stability of some metal-palmitate soaps which find various industrial applications
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M. F.R. Fouda, Elham A.A. Yousef, S. S. Mohamed, and Zein E. Shoeb
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catalyst ,lubricant ,metal-palmitate soap ,thermal stability ,Nutrition. Foods and food supply ,TX341-641 - Abstract
The soaps of alkaline earth's and transition elements and closed ‘d’ orbitals were prepared by the double decomposition method by the reaction between metallic salts and sodium palmitate. The thermal stability of these soaps was studied in order to throw the light on their suitability for using as catalysts or lubricants. The soaps of alkaline earth's were found to be more stable than transition and ‘d’ closed shell soaps.
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- 2001
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30. Oleochemicals I: Studies on the preparation and the structure of lithium soaps.
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Zein E. Shoeb, Bayed M. Hammad, and A. A. Yousef
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elementary analysis ,infrared spectrophotometry ,lithium hydroxide ,metallic soap ,thermal gravimetric analysis ,x-ray diffraction ,Nutrition. Foods and food supply ,TX341-641 - Abstract
Lithium stéarate, palmitate, myristate, laurate, caprate and caprylate were prepared by means of fusion method. Elementary analysis and the infrared absorptions spectra of the prepared lithium soaps as well as their X-ray diffractions and the thermogravimetric analyses were carried out. The anhydrous lithium salts of fatty acids with 12 carbon atoms or less showed thermal stability up to ca. 300 ± 78 °C depending on the chain length. On other hand the salts with 14 carbon atoms or more were decomposed at 126 ± 4 °C leading to formation of lithium carbonate. The homologous lithium soaps had very similar crystal structure among them and their metal -to- oxygen bonds were similar for the acyl chains between 8 and 18 carbons. However the angle of inclination of the molecular axes to the basal plane increased with the decreasing of the number of carbon atoms of the fatty acid chain, as determined by X-ray diffraction. In addition, the ionic character of the metal -to- oxygen bond was enhanced with the decrease of the number of carbon atoms as shown by infrared spectroscopy.
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- 1999
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31. Global Retinoblastoma Presentation and Analysis by National Income Level
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Fabian, ID, Abdallah, E, Abdullahi, SU, Abdulqader, RA, Boubacar, SA, Ademola-Popoola, DS, Adio, A, Afshar, AR, Aggarwal, P, Aghaji, AE, Ahmad, A, Akib, MNR, Al Harby, L, Al Ani, MH, Alakbarova, A, Portabella, SA, Al-Badri, SAF, Alcasabas, APA, Al-Dahmash, SA, Alejos, A, Alemany-Rubio, E, Bio, AIA, Carreras, YA, Al-Haddad, C, Al-Hussaini, HHY, Ali, AM, Alia, DB, Al-Jadiry, MF, Al-Jumaly, U, Alkatan, HM, All-Eriksson, C, Al-Mafrachi, AARM, Almeida, AA, Alsawidi, KM, Al-Shaheen, AASM, Al-Shammary, EH, Amiruddin, PO, Antonino, R, Astbury, NJ, Atalay, HT, Atchaneeyasakul, L-O, Atsiaya, R, Attaseth, T, Aung, TH, Ayala, S, Baizakova, B, Balaguer, J, Balayeva, R, Balwierz, W, Barranco, H, Bascaran, C, Popovic, MB, Benavides, R, Benmiloud, S, Guebessi, NB, Berete, RC, Berry, JL, Bhaduri, A, Bhat, S, Biddulph, SJ, Biewald, EM, Bobrova, N, Boehme, M, Boldt, HC, Bonanomi, MTBC, Bornfeld, N, Bouda, GC, Bouguila, H, Boumedane, A, Brennan, RC, Brichard, BG, Buaboonnam, J, Calderon-Sotelo, P, Calle Jara, DA, Camuglia, JE, Cano, MR, Capra, M, Cassoux, N, Castela, G, Castillo, L, Catala-Mora, J, Chantada, GL, Chaudhry, S, Chaugule, SS, Chauhan, A, Chawla, B, Chernodrinska, VS, Chiwanga, FS, Chuluunbat, T, Cieslik, K, Cockcroft, RL, Comsa, C, Correa, ZM, Correa Llano, MG, Corson, TW, Cowan-Lyn, KE, Csoka, M, Cui, X, Da Gama, I, Dangboon, W, Das, A, Das, S, Davanzo, JM, Davidson, A, De Potter, P, Delgado, KQ, Demirci, H, Desjardins, L, Diaz Coronado, RY, Dimaras, H, Dodgshun, AJ, Donaldson, C, Donato Macedo, CR, Dragomir, MD, Du, Y, Du Bruyn, M, Edison, KS, Sutyawan, IWE, El Kettani, A, Elbahi, AM, Elder, JE, Elgalaly, D, Elhaddad, AM, Elhassan, MMA, Elzembely, MM, Essuman, VA, Evina, TGA, Fadoo, Z, Fandino, AC, Faranoush, M, Fasina, O, Fernandez, DDPG, Fernandez-Teijeiro, A, Foster, A, Frenkel, S, Fu, LD, Fuentes-Alabi, SL, Gallie, BL, Gandiwa, M, Garcia, JL, Garcia Aldana, D, Gassant, PY, Geel, JA, Ghassemi, F, Giron, A, Gizachew, Z, Goenz, MA, Gold, AS, Goldberg-Lavid, M, Gole, GA, Gomel, N, Gonzalez, E, Gonzalez Perez, G, Gonzalez-Rodriguez, L, Garcia Pacheco, HN, Graells, J, Green, L, Gregersen, PA, Grigorovski, NDAK, Guedenon, KM, Gunasekera, DS, Gunduz, AK, Gupta, H, Gupta, S, Hadjistilianou, T, Hamel, P, Hamid, SA, Hamzah, N, Hansen, ED, Harbour, JW, Hartnett, ME, Hasanreisoglu, M, Hassan, S, Hederova, S, Hernandez, J, Carcamo Hernandez, LM, Hessissen, L, Hordofa, DF, Huang, LC, Hubbard, GB, Hummlen, M, Husakova, K, Al-Janabi, ANH, Ida, R, Ilic, VR, Jairaj, V, Jeeva, I, Jenkinson, H, Ji, X, Jo, DH, Johnson, KP, Johnson, WJ, Jones, MM, Kabesha, TBA, Kabore, RL, Kaliki, S, Kalinaki, A, Kantar, M, Kao, L-Y, Kardava, T, Kebudi, R, Kepak, T, Keren-Froim, N, Khan, ZJ, Khaqan, HA, Khauv, P, Kheir, WJ, Khetan, V, Khodabande, A, Khotenashvili, Z, Kim, JW, Kim, JH, Kiratli, H, Kivela, TT, Klett, A, Palet, JEKK, Krivaitiene, D, Kruger, M, Kulvichit, K, Kuntorini, MW, Kyara, A, Lachmann, ES, Lam, CPS, Lam, GC, Larson, SA, Latinovic, S, Laurenti, KD, Le, BHA, Lecuona, K, Leverant, AA, Li, C, Limbu, B, Quah, BL, Lopez, JP, Lukamba, RM, Lumbroso, L, Luna-Fineman, S, Lutfi, D, Lysytsia, L, Magrath, GN, Mahajan, A, Majeed, AR, Maka, E, Makan, M, Makimbetov, EK, Manda, C, Martin Begue, N, Mason, L, Mason, JO, Matende, IO, Materin, M, Mattosinho, CCDS, Matua, M, Mayet, I, Mbumba, FB, McKenzie, JD, Medina-Sanson, A, Mehrvar, A, Mengesha, AA, Menon, V, Mercado, GJVD, Mets, MB, Midena, E, Mishra, DKC, Mndeme, FG, Mohamedani, AA, Mohammad, MT, Moll, AC, Montero, MM, Morales, RA, Moreira, C, Mruthyunjaya, P, Msina, MS, Msukwa, G, Mudaliar, SS, Muma, K, Munier, FL, Murgoi, G, Murray, TG, Musa, KO, Mushtaq, A, Mustak, H, Muyen, OM, Naidu, G, Nair, AG, Naumenko, L, Roth, PAN, Nency, YM, Neroev, V, Ngo, H, Nieves, RM, Nikitovic, M, Nkanga, ED, Nkumbe, H, Nuruddin, M, Nyaywa, M, Obono-Obiang, G, Oguego, NC, Olechowski, A, Oliver, SCN, Osei-Bonsu, P, Ossandon, D, Paez-Escamilla, MA, Pagarra, H, Painter, SL, Paintsil, V, Paiva, L, Pal, BP, Palanivelu, MS, Papyan, R, Parrozzani, R, Parulekar, M, Morales, CRP, Paton, KE, Pawinska-Wasikowska, K, Pe'er, J, Pena, A, Peric, S, Pham, CTM, Philbert, R, Plager, DA, Pochop, P, Polania, RA, Polyakov, VG, Pompe, MT, Pons, JJ, Prat, D, Prom, V, Purwanto, I, Qadir, AO, Qayyum, S, Qian, J, Rahman, A, Rahman, S, Rahmat, J, Rajkarnikar, P, Ramanjulu, R, Ramasubramanian, A, Ramirez-Ortiz, MA, Raobela, L, Rashid, R, Reddy, MA, Reich, E, Renner, LA, Reynders, D, Ribadu, D, Riheia, MM, Ritter-Sovinz, P, Rojanaporn, D, Romero, L, Roy, SR, Saab, RH, Saakyan, S, Sabhan, AH, Sagoo, MS, Said, AMA, Saiju, R, Salas, B, San Roman Pacheco, S, Sanchez, GL, Sayalith, P, Scanlan, TA, Schefler, AC, Schoeman, J, Sedaghat, A, Seregard, S, Seth, R, Shah, AS, Shakoor, SA, Sharma, MK, Sherief, ST, Shetye, NG, Shields, CL, Siddiqui, SN, Cheikh, SS, Silva, S, Singh, AD, Singh, N, Singh, U, Singha, P, Sitorus, RS, Skalet, AH, Soebagjo, HD, Sorochynska, T, Ssali, G, Stacey, AW, Staffieri, SE, Stahl, ED, Stathopoulos, C, Kranjc, BS, Stones, DK, Strahlendorf, C, Suarez, MEC, Sultana, S, Sun, X, Sundy, M, Superstein, R, Supriyadi, E, Surukrattanaskul, S, Suzuki, S, Svojgr, K, Sylla, F, Tamamyan, G, Tan, D, Tandili, A, Tarrillo Leiva, FF, Tashvighi, M, Tateshi, B, Tehuteru, ES, Teixeira, LF, Teh, KH, Theophile, T, Toledano, H, Trang, DL, Traore, F, Trichaiyaporn, S, Tuncer, S, Tyau-Tyau, H, Umar, AB, Unal, E, Uner, OE, Urbak, SF, Ushakova, TL, Usmanov, RH, Valeina, S, Wijsard, MVH, Varadisai, A, Vasquez, L, Vaughan, LO, Veleva-Krasteva, NV, Verma, N, Victor, AA, Viksnins, M, Villacos Chafla, EG, Vishnevskia-Dai, V, Vora, T, Wachtel, AE, Wackernagel, W, Waddell, K, Wade, PD, Wali, AH, Wang, Y-Z, Weiss, A, Wilson, MW, Wime, ADC, Wiwatwongwana, A, Wiwatwongwana, D, Dod, CW, Wongwai, P, Xiang, D, Xiao, Y, Yam, JC, Yang, H, Yanga, JM, Yaqub, MA, Yarovaya, VA, Yarovoy, AA, Ye, H, Yousef, YA, Yuliawati, P, Zapata Lopez, AM, Zein, E, Zhang, C, Zhang, Y, Zhao, J, Zheng, X, Zhilyaeva, K, Zia, N, Ziko, OAO, Zondervan, M, Bowman, R, Fabian, ID, Abdallah, E, Abdullahi, SU, Abdulqader, RA, Boubacar, SA, Ademola-Popoola, DS, Adio, A, Afshar, AR, Aggarwal, P, Aghaji, AE, Ahmad, A, Akib, MNR, Al Harby, L, Al Ani, MH, Alakbarova, A, Portabella, SA, Al-Badri, SAF, Alcasabas, APA, Al-Dahmash, SA, Alejos, A, Alemany-Rubio, E, Bio, AIA, Carreras, YA, Al-Haddad, C, Al-Hussaini, HHY, Ali, AM, Alia, DB, Al-Jadiry, MF, Al-Jumaly, U, Alkatan, HM, All-Eriksson, C, Al-Mafrachi, AARM, Almeida, AA, Alsawidi, KM, Al-Shaheen, AASM, Al-Shammary, EH, Amiruddin, PO, Antonino, R, Astbury, NJ, Atalay, HT, Atchaneeyasakul, L-O, Atsiaya, R, Attaseth, T, Aung, TH, Ayala, S, Baizakova, B, Balaguer, J, Balayeva, R, Balwierz, W, Barranco, H, Bascaran, C, Popovic, MB, Benavides, R, Benmiloud, S, Guebessi, NB, Berete, RC, Berry, JL, Bhaduri, A, Bhat, S, Biddulph, SJ, Biewald, EM, Bobrova, N, Boehme, M, Boldt, HC, Bonanomi, MTBC, Bornfeld, N, Bouda, GC, Bouguila, H, Boumedane, A, Brennan, RC, Brichard, BG, Buaboonnam, J, Calderon-Sotelo, P, Calle Jara, DA, Camuglia, JE, Cano, MR, Capra, M, Cassoux, N, Castela, G, Castillo, L, Catala-Mora, J, Chantada, GL, Chaudhry, S, Chaugule, SS, Chauhan, A, Chawla, B, Chernodrinska, VS, Chiwanga, FS, Chuluunbat, T, Cieslik, K, Cockcroft, RL, Comsa, C, Correa, ZM, Correa Llano, MG, Corson, TW, Cowan-Lyn, KE, Csoka, M, Cui, X, Da Gama, I, Dangboon, W, Das, A, Das, S, Davanzo, JM, Davidson, A, De Potter, P, Delgado, KQ, Demirci, H, Desjardins, L, Diaz Coronado, RY, Dimaras, H, Dodgshun, AJ, Donaldson, C, Donato Macedo, CR, Dragomir, MD, Du, Y, Du Bruyn, M, Edison, KS, Sutyawan, IWE, El Kettani, A, Elbahi, AM, Elder, JE, Elgalaly, D, Elhaddad, AM, Elhassan, MMA, Elzembely, MM, Essuman, VA, Evina, TGA, Fadoo, Z, Fandino, AC, Faranoush, M, Fasina, O, Fernandez, DDPG, Fernandez-Teijeiro, A, Foster, A, Frenkel, S, Fu, LD, Fuentes-Alabi, SL, Gallie, BL, Gandiwa, M, Garcia, JL, Garcia Aldana, D, Gassant, PY, Geel, JA, Ghassemi, F, Giron, A, Gizachew, Z, Goenz, MA, Gold, AS, Goldberg-Lavid, M, Gole, GA, Gomel, N, Gonzalez, E, Gonzalez Perez, G, Gonzalez-Rodriguez, L, Garcia Pacheco, HN, Graells, J, Green, L, Gregersen, PA, Grigorovski, NDAK, Guedenon, KM, Gunasekera, DS, Gunduz, AK, Gupta, H, Gupta, S, Hadjistilianou, T, Hamel, P, Hamid, SA, Hamzah, N, Hansen, ED, Harbour, JW, Hartnett, ME, Hasanreisoglu, M, Hassan, S, Hederova, S, Hernandez, J, Carcamo Hernandez, LM, Hessissen, L, Hordofa, DF, Huang, LC, Hubbard, GB, Hummlen, M, Husakova, K, Al-Janabi, ANH, Ida, R, Ilic, VR, Jairaj, V, Jeeva, I, Jenkinson, H, Ji, X, Jo, DH, Johnson, KP, Johnson, WJ, Jones, MM, Kabesha, TBA, Kabore, RL, Kaliki, S, Kalinaki, A, Kantar, M, Kao, L-Y, Kardava, T, Kebudi, R, Kepak, T, Keren-Froim, N, Khan, ZJ, Khaqan, HA, Khauv, P, Kheir, WJ, Khetan, V, Khodabande, A, Khotenashvili, Z, Kim, JW, Kim, JH, Kiratli, H, Kivela, TT, Klett, A, Palet, JEKK, Krivaitiene, D, Kruger, M, Kulvichit, K, Kuntorini, MW, Kyara, A, Lachmann, ES, Lam, CPS, Lam, GC, Larson, SA, Latinovic, S, Laurenti, KD, Le, BHA, Lecuona, K, Leverant, AA, Li, C, Limbu, B, Quah, BL, Lopez, JP, Lukamba, RM, Lumbroso, L, Luna-Fineman, S, Lutfi, D, Lysytsia, L, Magrath, GN, Mahajan, A, Majeed, AR, Maka, E, Makan, M, Makimbetov, EK, Manda, C, Martin Begue, N, Mason, L, Mason, JO, Matende, IO, Materin, M, Mattosinho, CCDS, Matua, M, Mayet, I, Mbumba, FB, McKenzie, JD, Medina-Sanson, A, Mehrvar, A, Mengesha, AA, Menon, V, Mercado, GJVD, Mets, MB, Midena, E, Mishra, DKC, Mndeme, FG, Mohamedani, AA, Mohammad, MT, Moll, AC, Montero, MM, Morales, RA, Moreira, C, Mruthyunjaya, P, Msina, MS, Msukwa, G, Mudaliar, SS, Muma, K, Munier, FL, Murgoi, G, Murray, TG, Musa, KO, Mushtaq, A, Mustak, H, Muyen, OM, Naidu, G, Nair, AG, Naumenko, L, Roth, PAN, Nency, YM, Neroev, V, Ngo, H, Nieves, RM, Nikitovic, M, Nkanga, ED, Nkumbe, H, Nuruddin, M, Nyaywa, M, Obono-Obiang, G, Oguego, NC, Olechowski, A, Oliver, SCN, Osei-Bonsu, P, Ossandon, D, Paez-Escamilla, MA, Pagarra, H, Painter, SL, Paintsil, V, Paiva, L, Pal, BP, Palanivelu, MS, Papyan, R, Parrozzani, R, Parulekar, M, Morales, CRP, Paton, KE, Pawinska-Wasikowska, K, Pe'er, J, Pena, A, Peric, S, Pham, CTM, Philbert, R, Plager, DA, Pochop, P, Polania, RA, Polyakov, VG, Pompe, MT, Pons, JJ, Prat, D, Prom, V, Purwanto, I, Qadir, AO, Qayyum, S, Qian, J, Rahman, A, Rahman, S, Rahmat, J, Rajkarnikar, P, Ramanjulu, R, Ramasubramanian, A, Ramirez-Ortiz, MA, Raobela, L, Rashid, R, Reddy, MA, Reich, E, Renner, LA, Reynders, D, Ribadu, D, Riheia, MM, Ritter-Sovinz, P, Rojanaporn, D, Romero, L, Roy, SR, Saab, RH, Saakyan, S, Sabhan, AH, Sagoo, MS, Said, AMA, Saiju, R, Salas, B, San Roman Pacheco, S, Sanchez, GL, Sayalith, P, Scanlan, TA, Schefler, AC, Schoeman, J, Sedaghat, A, Seregard, S, Seth, R, Shah, AS, Shakoor, SA, Sharma, MK, Sherief, ST, Shetye, NG, Shields, CL, Siddiqui, SN, Cheikh, SS, Silva, S, Singh, AD, Singh, N, Singh, U, Singha, P, Sitorus, RS, Skalet, AH, Soebagjo, HD, Sorochynska, T, Ssali, G, Stacey, AW, Staffieri, SE, Stahl, ED, Stathopoulos, C, Kranjc, BS, Stones, DK, Strahlendorf, C, Suarez, MEC, Sultana, S, Sun, X, Sundy, M, Superstein, R, Supriyadi, E, Surukrattanaskul, S, Suzuki, S, Svojgr, K, Sylla, F, Tamamyan, G, Tan, D, Tandili, A, Tarrillo Leiva, FF, Tashvighi, M, Tateshi, B, Tehuteru, ES, Teixeira, LF, Teh, KH, Theophile, T, Toledano, H, Trang, DL, Traore, F, Trichaiyaporn, S, Tuncer, S, Tyau-Tyau, H, Umar, AB, Unal, E, Uner, OE, Urbak, SF, Ushakova, TL, Usmanov, RH, Valeina, S, Wijsard, MVH, Varadisai, A, Vasquez, L, Vaughan, LO, Veleva-Krasteva, NV, Verma, N, Victor, AA, Viksnins, M, Villacos Chafla, EG, Vishnevskia-Dai, V, Vora, T, Wachtel, AE, Wackernagel, W, Waddell, K, Wade, PD, Wali, AH, Wang, Y-Z, Weiss, A, Wilson, MW, Wime, ADC, Wiwatwongwana, A, Wiwatwongwana, D, Dod, CW, Wongwai, P, Xiang, D, Xiao, Y, Yam, JC, Yang, H, Yanga, JM, Yaqub, MA, Yarovaya, VA, Yarovoy, AA, Ye, H, Yousef, YA, Yuliawati, P, Zapata Lopez, AM, Zein, E, Zhang, C, Zhang, Y, Zhao, J, Zheng, X, Zhilyaeva, K, Zia, N, Ziko, OAO, Zondervan, M, and Bowman, R
- Abstract
IMPORTANCE: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. OBJECTIVES: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. DESIGN, SETTING, AND PARTICIPANTS: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. MAIN OUTCOMES AND MEASURES: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. RESULTS: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis
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- 2020
32. Standardizing the Evaluation of Treatment Outcomes After Skin Rejuvenation: The Qualitative Scoring System
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Obagi, Zein E., Alaiti, Samer, Obagi, Suzan, Stevens, Michael B., and Delune, Michel E.
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- 2000
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33. Magnetic Data Interpretation Using a New R-Parameter Imaging Method with Application to Mineral Exploration
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Mehanee, Salah, primary, Essa, Khalid S., additional, and Diab, Zein E., additional
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- 2020
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34. Self-potential Data Interpretation for Two Co-axial Structures Utilizing the RMS Parameter
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Essa, Khalid S., primary, Diab, Zein E., additional, and Elhussein, Mahmoud, additional
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- 2020
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35. Cognitive function assessment in adolescent patients on hemodiaylsis
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Zein E. Omar, Reem Elsayed Hashem, and Amr S Shalaby
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Pediatrics ,medicine.medical_specialty ,business.industry ,medicine.medical_treatment ,030232 urology & nephrology ,Cognitive flexibility ,Cognition ,030204 cardiovascular system & hematology ,medicine.disease ,03 medical and health sciences ,Psychiatry and Mental health ,0302 clinical medicine ,Raven's Progressive Matrices ,medicine ,Hemodialysis ,business ,Psychosocial ,Neurocognitive ,Dialysis ,Kidney disease - Abstract
Background Studying the impact of chronic kidney disease on neurocognitive functions is a critical element for providing optimal care to these children who might suffer from its detrimental consequence on their psychosocial life. Aim The aim of the study was to assess the cognitive functions in adolescents with end-stage renal disease (ESRD) under regular hemodialysis compared with healthy controls. Patients and methods We studied 40 adolescents – 20 patients with ESRD on regular dialysis and 20 controls closely matched with the patient in terms of their age, sex, and educational level. Patients were recruited from the pediatric dialysis unit, Menoufia University hospitals, with dialysis durations ranging from 0.5 to 8.5 years with mean 3.25±2.28 years. They were assessed using Raven’s Progressive Matrices tests (for fluid intelligence), and a computerized battery composed of Spatial Span (visual–spatial working memory task), Tower of London task (measuring planning and problem-solving ability), and the Go/No Go task (a task assessing response inhibition, set shifting, and attention). We, furthermore, assessed disease-related variables impacting the cognitive functions of the patients. Results The average age of the patients was 14.4±3.315 years, and that of the controls was 13.7±1.46 years. The fluid IQ for the patients was significantly lower than the controls (P Conclusion Our findings provide evidence that the fluid intelligence and cognitive function of adolescents with ESRD on dialysis fall within the low average on most tasks. Furthermore, hypertension and anemia potentially place children with ESRD at an increased risk for neurocognitive deficits, which consequently places them at risk for poor long-term educational and occupational outcomes.
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- 2017
36. Managing the Difficult Soft Tissue Envelope in Facial and Rhinoplasty Surgery
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Zein E Obagi and Aaron M. Kosins
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Adult ,Male ,medicine.medical_specialty ,Nasolabial Fold ,Esthetics ,medicine.medical_treatment ,Nose ,030230 surgery ,Decision Support Techniques ,Rhinoplasty ,Young Adult ,03 medical and health sciences ,Subcutaneous Tissue ,0302 clinical medicine ,Dermis ,Predictive Value of Tests ,Photography ,medicine ,Humans ,Local anesthesia ,Muscle, Skeletal ,030223 otorhinolaryngology ,Physical Examination ,Skin ,Ultrasonography ,business.industry ,Racial Groups ,Ultrasound ,Reproducibility of Results ,Soft tissue ,General Medicine ,Middle Aged ,Nasolabial fold ,Surgery ,Treatment Outcome ,medicine.anatomical_structure ,Visual Perception ,Female ,Anatomic Landmarks ,business ,Algorithms ,Envelope (motion) - Abstract
Background The nasal soft tissue envelope affects the final rhinoplasty result, and can limit the expected improvement. Currently, no dependable and objective test exists to measure the thickness of the nasal skin and underlying soft tissue. Objectives This paper presents a simple, yet reliable method to determine the thickness of the soft tissue envelope. An algorithm is presented for treatment of the dermis and/or soft tissue apart from surgery of the underlying osseocartilaginous structures. Methods Seventy-five patients presenting for primary rhinoplasty underwent visual and ultrasound assessment of their nasal soft tissue envelope. At preoperative evaluation, the Obagi "skin pinch test" was used to assess the thickness of the nasolabial fold and whether or not the skin was oily. Patients were classified based on the pinch thickness. At time of surgery prior to injection of local anesthesia, ultrasonic assessment was done at the nasolabial fold, keystone junction, supratip, and tip to measure the thickness of the nasal dermis and underlying soft tissue. Results Patients determined to have thin, normal, and thick skin by the "skin pinch test" were found to have a nasolabial fold dermal thickness with an average of 0.7 mm (0.4-1.2 mm), 1.1 mm (0.8-1.8 mm), and 1.4 mm (0.7-2.0 mm). Patients determined to have thin, normal, and thick skin were found to have a dermal thickness at the keystone junction with an average of 0.3 mm (0.2-0.4 mm), 0.5 mm (0.3-1.1 mm), and 0.9 mm (0.6-1.2 mm), respectively. This difference in thickness also translated to the supratip and tip areas measured. However, all areas were also affected by the oiliness of the skin. Soft tissue thickness (SMAS and muscle) underlying the dermis was variable. Patients of non-Caucasian background were more likely to have a thicker soft tissue layer. Conclusions The "skin pinch test" is an easy and reliable way for the surgeon to evaluate the thickness of the nasal soft tissue envelope. The rhinoplasty surgeon can make decisions pre- and postoperatively to treat patients with difficult soft tissue envelopes. LEVEL OF EVIDENCE 4.
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- 2016
37. Skin Health Restoration and Skin Conditioning: Agents Used
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Obagi, Zein E., primary
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- 2000
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38. Obagi Skin Health Restoration and Rejuvenation
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Obagi, Zein E., primary
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- 2000
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39. Part Two Skin Anatomy and Physiology: A Personal View
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Obagi, Zein E., primary
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- 2000
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40. The Blue Peel
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Obagi, Zein E., primary
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- 2000
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41. Skin Health: The Concepts
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Obagi, Zein E., primary
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- 2000
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42. The Obagi Controlled Medium-Depth Peel
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Obagi, Zein E., primary
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- 2000
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43. Skin Health Restoration and Skin Conditioning: Correction and Stimulation
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Obagi, Zein E., primary
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- 2000
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44. Identifying and Treating Anticipated Reactions and Complications after Chemical Peels and Other Resurfacing Procedures
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Obagi, Zein E., primary
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- 2000
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45. The Treatment Plan for Rejuvenation
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Obagi, Zein E., primary
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- 2000
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46. Part One Skin Anatomy and Physiology
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Obagi, Zein E., primary
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- 2000
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47. Skin Classification
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Obagi, Zein E., primary
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- 2000
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48. Overview of TCA and Other Chemical Peels
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Obagi, Zein E., primary
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- 2000
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49. Effect of posture and prolonged pneumoperitoneum on intraoperative and postoperative outcomes during gynecological laparoscopic surgery: an observational clinical study
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Zein E. A. Zareh Hassan, Fatma N A. Mohamed, Umm K A. Gad, Esam Abdalla, and Sayed Kaoud Abd Elshafy
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Laparoscopic surgery ,business.industry ,medicine.medical_treatment ,Trendelenburg position ,Hemodynamics ,medicine.disease ,Mean blood pressure ,Blood pressure ,Pneumoperitoneum ,Anesthesia ,medicine ,Respiratory function ,business ,Gynecological surgery - Abstract
Introduction Laparoscopic surgery is a common daily performed procedure. It has the advantages of small incision, better cosmetic aspects, less postoperative pain, and rapid recovery to daily activities. Pneumoperitoneum and increased intraabdominal pressure can induce many pathophysiologic disturbances, requiring the anesthesiologist to be well alert during the operation for necessary management. Patients and methods This is a prospective, observational clinical study. A total of 60 consecutive patients scheduled for gynecological laparoscopic surgery were recruited from the Gynecological and Obstetrics Department. Selected patients were divided into two groups according to the duration in Trendelenburg positioning: group I ( 1 h). A preoperative anesthetic assessment was carried out, and a standardized general anesthesia technique and monitoring were followed for all patients of the two groups. Pneumoperitoneum was generated by the insufflation of gas (CO2) into the peritoneal cavity. Results On the evaluation of the effect of prolonged pneumoperitoneum and position of patents on intraoperative hemodynamics, mean arterial blood pressure was significantly decreased (in group II) at time M3 (average mean blood pressure during Trendelenburg position till recovery). Heart rate also significantly decreased (in group II) at time heart rate 3 (average heart rate during Trendelenburg position till recovery). Intraabdominal pressure significantly decreased in group II at time intraabdominal pressure 4 (average time during positioning), and pulmonary function test parameters were significantly decreased after recovery. Conclusion Prolonged laparoscopic gynecological surgery can markedly affect intraoperative hemodynamics and postoperative respiratory function.
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- 2021
50. Gravity profile interpretation using the R-parameter imaging technique with application to ore exploration
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Zein E. Diab, Khalid S. Essa, Salah Mehanee, and Khaled S. Soliman
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Gravity (chemistry) ,Correlation coefficient ,Noise (signal processing) ,020209 energy ,Mathematical analysis ,Statistical parameter ,Geochemistry ,Geology ,02 engineering and technology ,010502 geochemistry & geophysics ,01 natural sciences ,Amplitude ,Interference (communication) ,Gravitational field ,Geochemistry and Petrology ,0202 electrical engineering, electronic engineering, information engineering ,Economic Geology ,Analytic signal ,0105 earth and related environmental sciences - Abstract
This paper describes a fast imaging technique, the so-called here the “R-parameter imaging technique”, for the interpretation of gravity data measured along profile. The technique calculates the R-parameter (a statistical parameter called the correlation coefficient) between the analytic signal of the measured gravity field and that of the synthetic response of an assumed interpretive model in the restricted class of spheres and cylinders. The characteristic source parameters (depth, shape, origin point of the gravity profile, and amplitude factor) of the model correspond to the maximum R-parameter value. The method has been verified on noise free numerical examples. Following that, the accuracy of the method has been carefully assessed on both noisy numerical examples and numerical examples with interference effects. Finally, the technique has been successfully applied to five field data examples from Canada, Sweden and Cuba for mineral exploration, and it is found that the obtained results are in good agreement with those reported in the published literature.
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- 2020
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