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1,385 results on '"Rezaei S."'

1. Quasitopological Lifshitz dilaton black brane

Author

Bazrafshan, A., Ghanaatian, M., Rezaei, S., and Forozani, Gh.

Subjects
High Energy Physics - Theory, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract

We construct a new class of $(n+1)$-dimensional Lifshitz dilaton black brane solutions in the presence of the cubic quasitopological gravity for a flat boundary. The related action supports asymptotically Lifshitz solutions by applying some conditions which are used throughout the paper. We have to add a new boundary term and some new counterterms to the bulk action to have finite solutions. Then we define a finite stress tensor complex by which we can calculate the energy density of the quasitopological Lifshitz dilaton black brane. It is not possible to obtain analytical solutions, and so we use some expantions to probe the functions behaviors near the horizon and at the infinity. Combining the equations, we can attain a total constant along the coordinate $r$. At the horizon, this constant is proportional to the product of the temperature and the entropy and at the infinity, the total constant shows the energ density of the quasitopological Lifshitz dilaton black brane. Therefore, we can reach to a relation between the conserved quantities temperature, entropy and the energy density and get a smarr-type formula. Using the first law of thermodynamics, we can find a relation between the entropy and the temperature and then ontain the heat capacity. Our results show that the quasitopological Lifshitz dilaton black brane solutions are thermally stable for each positive values of the dynamical critiacl exponent, $z$., Comment: 14 pages and 2 figures

Published
2024

2. Correlation between Anger and Job Motivation among Psychiatric Nurses in Kashan Psychiatric Hospital

Author

Kouchaki E., Rezaei S., and Motaghi M.

Subjects
anger, job motivation, Psychiatry, Nurse, Medicine (General), R5-920
Abstract

Abstract Aims: In general, nurses who work in department of psychiatric are in fact interacting with emotional disorders of patients once providing their care services. higher levels of job motivation and satisfaction can markedly foster service improvement. The aim of this study was to evaluate the correlation between anger and job motivation in nurses of a psychiatric hospital. Instrument & Methods: In this cross-sectional descriptive research in 2014, all 50 psychiatry nurses working at Kargarnejad Hospital of Kashan City, Iran, were entirely studied. A demographical questionnaire, the Anger Multiple Scale and the Job Motivation Scale were used for data gathering. Data were analyzed by SPSS 19 software using Pearson correlation coefficient. Findings: The mean score of anger was 3.01±0.36 and of job motivation was 1.70±0.86. There was a significant relationship between job motivation and the number of family members and conditions of employment of nurses (p=0.001). There was a significant inverse relationship between scores of anger and job motivation of psychiatry nurses of the hospital (r=-0.712; p=0.001). Conclusion: There is a relationship between anger and job motivation in nurses of Kashan Psychiatric hospital.

Published
2016

3. On the source counts of VLBI-detected radio sources and the prospects of all-sky surveys with current and next generation instruments

Author

Rezaei, S., McKean, J. P., Deller, A. T., and Radcliffe, J. F.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present an analysis of the detection fraction and the number counts of radio sources imaged with Very Long Baseline Interferometry (VLBI) at 1.4 GHz as part of the mJIVE-20 survey. From a sample of 24,903 radio sources identified by FIRST, 4,965 are detected on VLBI-scales, giving an overall detection fraction of $19.9\pm2.9~$per cent. However, we find that the detection fraction falls from around 50 per cent at a peak surface brightness of $80~mJy~beam^{-1}$ in FIRST to around 8 per cent at the detection limit, which is likely dominated by the surface brightness sensitivity of the VLBI observations, with some contribution from a change in the radio source population. We also find that compactness at arcsec-scales is the dominant factor in determining whether a radio source is detected with VLBI, and that the median size of the VLBI-detected radio sources is 7.7 mas. After correcting for the survey completeness and effective sky area, we determine the slope of the differential number counts of VLBI-detected radio sources with flux densities $S_{\rm 1.4~GHz} > 1~mJy$ to be $\eta_{\rm VLBI} = -1.74\pm 0.02$, which is shallower than in the cases of the FIRST parent population ($\eta_{\rm FIRST} = -1.77\pm 0.02$) and for compact radio sources selected at higher frequencies ($\eta_{\rm JBF} = -2.06\pm 0.02$). From this, we find that all-sky ($3\pi~sr$) surveys with the EVN and the VLBA have the potential to detect $(7.2\pm0.9)\times10^{5}$ radio sources at mas-resolution, and that the density of compact radio sources is sufficient (5.3~deg$^{-2}$) for in-beam phase referencing with multiple sources (3.9 per primary beam) in the case of a hypothetical SKA-VLBI array.

Published
2023

5. A machine learning based approach to gravitational lens identification with the International LOFAR Telescope

Author

Rezaei, S., McKean, J. P., Biehl, M., de Roo1, W., and Lafontaine, A.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning
Abstract

We present a novel machine learning based approach for detecting galaxy-scale gravitational lenses from interferometric data, specifically those taken with the International LOFAR Telescope (ILT), which is observing the northern radio sky at a frequency of 150 MHz, an angular resolution of 350 mas and a sensitivity of 90 uJy beam-1 (1 sigma). We develop and test several Convolutional Neural Networks to determine the probability and uncertainty of a given sample being classified as a lensed or non-lensed event. By training and testing on a simulated interferometric imaging data set that includes realistic lensed and non-lensed radio sources, we find that it is possible to recover 95.3 per cent of the lensed samples (true positive rate), with a contamination of just 0.008 per cent from non-lensed samples (false positive rate). Taking the expected lensing probability into account results in a predicted sample purity for lensed events of 92.2 per cent. We find that the network structure is most robust when the maximum image separation between the lensed images is greater than 3 times the synthesized beam size, and the lensed images have a total flux density that is equivalent to at least a 20 sigma (point-source) detection. For the ILT, this corresponds to a lens sample with Einstein radii greater than 0.5 arcsec and a radio source population with 150 MHz flux densities more than 2 mJy. By applying these criteria and our lens detection algorithm we expect to discover the vast majority of galaxy-scale gravitational lens systems contained within the LOFAR Two Metre Sky Survey., Comment: Accepted to be published by MNRAS

Published
2022
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9. DECORAS: detection and characterization of radio-astronomical sources using deep learning

Author

Rezaei, S., McKean, J. P., Biehl, M., and Javadpour, A.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We present DECORAS, a deep learning based approach to detect both point and extended sources from Very Long Baseline Interferometry (VLBI) observations. Our approach is based on an encoder-decoder neural network architecture that uses a low number of convolutional layers to provide a scalable solution for source detection. In addition, DECORAS performs source characterization in terms of the position, effective radius and peak brightness of the detected sources. We have trained and tested the network with images that are based on realistic Very Long Baseline Array (VLBA) observations at 20 cm. Also, these images have not gone through any prior de-convolution step and are directly related to the visibility data via a Fourier transform. We find that the source catalog generated by DECORAS has a better overall completeness and purity, when compared to a traditional source detection algorithm. DECORAS is complete at the 7.5$\sigma$ level, and has an almost factor of two improvement in reliability at 5.5$\sigma$. We find that DECORAS can recover the position of the detected sources to within 0.61 $\pm$ 0.69 mas, and the effective radius and peak surface brightness are recovered to within 20 per cent for 98 and 94 per cent of the sources, respectively. Overall, we find that DECORAS provides a reliable source detection and characterization solution for future wide-field VLBI surveys., Comment: submitted to MNRAS

Published
2021
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11. New perspective on chiral exceptional points with application to discrete photonics

Author

Hashemi, A., Rezaei, S. M., Ozdemir, S. K., and El-Ganainy, R.

Subjects
Physics - Optics
Abstract

Chiral exceptional points (CEPs) have been shown to emerge in traveling wave resonators via asymmetric back scattering from two or more nano-scatterers. Here, we provide a new perspective on the formation of CEPs based on the coupled oscillator model. Our approach provides an intuitive understanding for the modal coalescence that signals the emergence of CEPs, and emphasizes the role played by dissipation throughout this process. In doing so, our model also unveils an otherwise unexplored connection between CEPs and other types of exceptional points associated with parity-time symmetric photonic arrangements. In addition, our model also explains qualitative results observed in recent experimental work involving CEPs. Importantly, the tight-binding nature of our approach allows us to extend the notion of CEP to discrete photonics setups that consist coupled resonator and waveguide arrays, thus opening new avenues for exploring the exotic features of CEPs in conjunction with other interesting physical effects such as nonlinearities and topological protections., Comment: 7 pages, 2 figures

Published
2021
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12. Signature of the quantum critical point on the witness of the non-Markovianity and the entanglement in spin-1/2 chain

Author

Saghafi, Z., Rezaei, S. Samadi, Azizi, P., Lapasar, E. Hosseini, and Mahdavifar, S.

Subjects
Condensed Matter - Statistical Mechanics
Abstract

A thermodynamic limit chain of spin-1/2 particles with XX and three-spin interactions (TSI) is considered. Using the fermionization technique, the Hamiltonian of the chain with periodic boundary conditions is exactly diagonalized. In the ground-state phase diagram of the chain system, a quantum critical point separates the Luttinger liquid and chiral phases. Selecting one-spin as an open quantum system, the rest of the spins play the role of its environment. By choosing different initial states, we studied the dynamics of the entanglement between the open quantum system and its environment. In the initial state, the state of the open quantum system is a superposition of up and down states and the environment is polarized. The revival of the entanglement is observed in the whole range of interactions as an indicator of non-Markovian dynamics. Our exact results revealed that non-Markovian behavior is independent of the initial state. By tuning the initial state, the open quantum system will be completely entangled with the environment at a special time called entanglement-time, tE. The value of the mentioned entanglement-time decreased by increasing TSI. The signature of a quantum critical point is confirmed by investigating the long-time average of the entanglement and using the trace-distance as a witness of non-Markovianity., Comment: 7 pages, 4 figures. arXiv admin note: text overlap with arXiv:1910.05951

Published
2020

14. Markovian and non-Markovian dynamics from probability amplitudes perspective

Author

Saghafi, Z., Rezaei, S. Samadi, Lapasar, E. Hosseini, and Mahdavifar, S.

Subjects
Condensed Matter - Statistical Mechanics, Quantum Physics
Abstract

One-spin and two-spin in a thermodynamic limit spin-1/2 chain as open quantum systems are considered. The dynamics of system is generated by XX Heisenberg interaction and three-spin interaction (TSI) among all the nearest three spins in the chain. Two variety Hamiltonians of the three-spin interaction are considered. Using the fermionization technique and calculating the trace distance, non-Markovianity as a function of the TSI is evaluated, and the results for the two different open quantum systems are compared. In addition, the time behavior of the probability amplitudes are studied. The results show that if all probability amplitudes except one of them will almost vanish after some time, the dynamics of the open quantum system will be Markovian. In the non-Markovian dynamics, more than one of the probability amplitudes fluctuate in time and will never reach zero value., Comment: This paper requires fundamental changes

Published
2019

33. Congenital heart disease in the ESC EORP Registry of Pregnancy and Cardiac disease (ROPAC)

Author

Hall, Roger, Roos-Hesselink, Jolien, Stein, Joerg, Parsonage, William Anthony, Budts, Werner, De Backer, Julie, Grewal, Jasmin, Marelli, Ariane, Kaemmerer, Harald, Jondeau, Guillaume, Johnson, Mark, Maggioni, Aldo P., Tavazzi, Luigi, Thilen, Ulf, Elkayam, Uri, Otto, Catherine, Sliwa, Karen, Aquieri, A., Saad, A., Vega, H. Ruda, Hojman, J., Caparros, J.M., Blanco, M. Vazquez, Arstall, M., Chung, C.M., Mahadavan, G., Aldridge, E., Wittwer, M., Chow, Y.Y., Parsonage, W.A., Lust, K., Collins, N., Warner, G., Hatton, R., Gordon, A., Nyman, E., Stein, J., Donhauser, E., Gabriel, H., Bahshaliyev, A., Guliyev, F., Hasanova, I., Jahangirov, T., Gasimov, Z., Salim, A., Ahmed, C.M., Begum, F., Hoque, M.H., Mahmood, M., Islam, M.N., Haque, P.P., Banerjee, S.K., Parveen, T., Morissens, M., De Backer, J., Demulier, L., de Hosson, M., Budts, W., Beckx, M., Kozic, M., Lovric, M., Kovacevic-Preradovic, T., Chilingirova, N., Kratunkov, P., Wahab, N., McLean, S., Gordon, E., Walter, L., Marelli, A., Montesclaros, A.R., Monsalve, G., Rodriguez, C., Balthazar, F., Quintero, V., Palacio, W., Cadavid, L.A. Mejía, Ortiz, E. Munoz, Hoyos, F. Fortich, Guerrero, E. Arevalo, Ricardo, J. Gandara, Penagos, J. Velasquez, Vavera, Z., Prague, Popelova, J., Vejlstrup, N., Grønbeck, L., Johansen, M., Ersboll, A., Elrakshy, Y., Eltamawy, K., Abd-El Aziz, M. Gamal, El Nagar, A., Ebaid, H., Elenin, H. Abo, Saed, M., Farag, S., Makled, W., Sorour, K., Ashour, Z., El-Sayed, G., Meguid Mahdy, M. Abdel, Taha, N., Dardeer, A., Shabaan, M., Ali, M., Moceri, P., Duthoit, G., Gouton, M., Nizard, J., Baris, L., Cohen, S., Ladouceur, M., Khimoud, D., Iung, B., Berger, F., Olsson, A., Gembruch, U., Merz, W.M., Reinert, E., Clade, S., Kliesch, Y., Wald, C., Sinning, C., Kozlik-Feldmann, R., Blankenberg, S., Zengin-Sahm, E., Mueller, G., Hillebrand, M., Hauck, P., von Kodolitsch, Y., Zarniko, N., Baumgartner, Muenster H., Schmidt, R., Hellige, A., Tutarel, O., Kaemmerer, H., Kuschel, B., Nagdyman, N., Motz, R., Maisuradze, D., Frogoudaki, A., Iliodromitis, E., Anastasiou-Nana, M., Marousi, Triantafyllis, D., Bekiaris, G., Karvounis, H., Giannakoulas, G., Ntiloudi, D., Mouratoglou, S.A., Temesvari, A., Balint, H., Kohalmi, D., Merkely, B., Liptai, C., Nemes, A., Forster, T., Kalapos, A., Berek, K., Havasi, K., Ambrus, N., Shelke, A., Kawade, R., Patil, S., Martanto, E., Aprami, T.M., Purnomowati, A., Cool, C.J., Hasan, M., Akbar, R., Hidayat, S., Dewi, T.I., Permadi, W., Soedarsono, D.A., Ansari-Ramandi, M.M., Samiei, N., Tabib, A., Kashfi, F., Ansari-Ramandi, S., Rezaei, S., Farhan, H. Ali, Al-Hussein, A., Al-Saedi, G., Mahmood, G., Yaseen, I.F., Al-Yousuf, L., AlBayati, M., Mahmood, S., Raheem, S., AlHaidari, T., Dakhil, Z., Thornton, P., Donnelly, J., Bowen, M., Blatt, A., Elbaz-Greener, G., Shotan, A., Yalonetsky, S., Goland, S., Biener, M., Assenza, G. Egidy, Bonvicini, M., Donti, A., Bulgarelli, A., Prandstraller, D., Romeo, C., Crepaz, R., Sciatti, E., Metra, M., Orabona, R., Ali, L. Ait, Festa, P., Fesslova, V., Bonanomi, C., Calcagnino, M., Lombardi, F., Colli, A.M., Ossola, M.W., Gobbi, C., Gherbesi, E., Tondi, L., Schiavone, M., Squillace, M., Carmina, M.G., Maina, A., Macchi, C., Gollo, E., Comoglio, F.M., Montali, N., Re, P., Bordese, R., Todros, T., Donvito, V., Marra, W. Grosso, Sinagra, G., D'Agata Mottolese, B., Bobbo, M., Gesuete, V., Rakar, S., Ramani, F., Niwa, K., Mekebekova, D., Mussagaliyeva, A., Lee, T., Mirrakhimov, E., Abilova, S., Bektasheva, E., Neronova, K., Lunegova, O., Žaliūnas, R., Jonkaitienė, R., Petrauskaitė, J., Laucevicius, A., Jancauskaite, D., Lauciuviene, L., Gumbiene, L., Lankutiene, L., Glaveckaite, S., Laukyte, M., Solovjova, S., Rudiene, V., Chee, K.H., Yim, C.C.-W., Ang, H.L., Kuppusamy, R., Watson, T., Caruana, M., Estensen, M.-E., Kayani, M.G.A. Mahmood, Munir, R., Tomaszuk-Kazberuk, A., Sobkowicz, B., Przepiesc, J., Lesniak-Sobelga, A., Tomkiewicz-Pajak, L., Komar, M., Olszowska, M., Podolec, P., Wisniowska-Smialek, S., Lelonek, M., Faflik, U., Cichocka-Radwan, A., Plaskota, K., Trojnarska, O., Guerra, N., de Sousa, L., Cruz, C., Ribeiro, V., Jovanova, S., Petrescu, V., Jurcut, R., Ginghina, C., Coman, I. Mircea, Musteata, M., Osipova, O., Golivets, T., Khamnagadaev, I., Golovchenko, O., Nagibina, A., Ropatko, I., Gaisin, I.R., Shilina, L. Valeryevna, Sharashkina, N., Shlyakhto, E., Irtyuga, O., Moiseeva, O., Karelkina, E., Zazerskaya, I., Kozlenok, A., Sukhova, I., Jovovic, L., Prokšelj, K., Koželj, M., Askar, A.O., Abdilaahi, A.A., Mohamed, M.H., Dirir, A.M., Sliwa, K., Manga, P., Pijuan-Domenech, A., Galian-Gay, L., Tornos, P., Subirana, M.T., T, M., Subirana, Oliver, J.M., Garcia-Aranda Dominguez, B., Gonzalez, I. Hernandez, Jimenez, J.F. Delgado, Subias, P. Escribano, Murga, N., Elbushi, A., Suliman, A., Jazzar, K., Murtada, M., Ahamed, N., Dellborg, M., Furenas, E., Jinesjo, M., Skoglund, K., Eriksson, P., Gilljam, T., Thilen, U., Tobler, D., Wustmann, K., Schwitz, F., Schwerzmann, M., Rutz, T., Bouchardy, J., Greutmann, M., Lopes, B.M. Santos, Meier, L., Arrigo, M., de Boer, K., Konings, T., Wajon, E., Wagenaar, L.J., Polak, P., Pieper, E.P.G., Roos-Hesselink, J., van Hagen, I., Duvekot, H., Cornette, J.M.J., De Groot, C., van Oppen, C., Sarac, L., Esen, O. Batukan, Enar, S. Catirli, Mondo, C., Ingabire, P., Nalwanga, B., Semu, T., Salih, B.T., Almahmeed, W.A.R., Wani, S., Farook, F.S. Mohamed, Ain, Al, Gerges, F., Komaranchath, A.M., Al bakshi, F., Al Mulla, A., Yusufali, A.H., Al Hatou, E.I., Bazargani, N., Hussain, F., Hudsmith, L., Thompson, P., Thorne, S., Bowater, S., Money-Kyrle, A., Clifford, P., Ramrakha, P., Firoozan, S., Chaplin, J., Bowers, N., Adamson, D., Schroeder, F., Wendler, R., Hammond, S., Nihoyannopoulos, P., Norfolk, Norwich, Hall, R., Freeman, L., Veldtman, G., Kerr, J., Tellett, L., Scott, N., Bhatt, A.B., DeFaria Yeh, D., Youniss, M.A., Wood, M., Sarma, A.A., Tsiaras, S., Stefanescu, A., Duran, J.M., Stone, L., Majdalany, D.S., Chapa, J., Chintala, K., Gupta, P., Botti, J., Ting, J., Davidson, W.R., Wells, G., Sparks, D., Paruchuri, V., Marzo, K., Patel, D., Wagner, W., Ahanya, S.N., Colicchia, L., Jentink, T., Han, K., Loichinger, M., Parker, M., Longtin, C., Yetman, A., Erickson, K., Cramer, J., Tsai, S., Fletcher, B., Warta, S., Cohen, C., Lindblade, C., Puntel, R., Nagaran, K., Croft, N., Gurvitz, M., Otto, C., Talluto, C., Murphy, D., Perlroth, M.G., Ramlakhan, Karishma P., Johnson, Mark R., Lelonek, Malgorzata, Saad, Aly, Gasimov, Zaur, Sharashkina, Natalia V., Thornton, Patrick, Arstall, Margaret, and Roos-Hesselink, Jolien W.

Published
2021
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35. The Suitability of the Three-way Catalyst for Hydrogen Fuelled Engines: A study in carbon emissions reduction and NOx management.

Author

Yavuz, M., Brinklow, G., Bonillo, A. Cova, Herreros, J. M., Wu, D., Doustdar, O., Zeraati-Rezaei, S., Tsolakis, A., Millington, P., and Clave, S. Alcove

Subjects
CARBON emissions, HYDROGEN as fuel, GREENHOUSE gas mitigation, CATALYTIC converters for automobiles, THERMAL efficiency, LEAN combustion, ENGINES
Abstract

This experimental study investigates the palladium/rhodium based three-way catalyst (TWC) in a hydrogen-gasoline dual-fuel spark ignition (SI) engine under stoichiometric and lean conditions. The work focused on lean-burn engine operating conditions with the aim of reducing nitrogen oxides (NOx) emissions during the combustion process, where the TWC is not effective, while improving the thermal efficiency of the engine. Under these leanburn engine conditions, the combustion promoting properties of hydrogen allowed for maintained engine combustion stability as determined by the cycle-to-cycle variation (COVimep) values even up to ultra lean conditions (λ= 2.0). It was found that by reducing the combustion temperature through the application of lean conditions, engine-out NOx emissions could be reduced or even eliminated, while under these conditions the TWC was effective in reducing engine-out carbon-based gaseous emissions. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Incidence and Intensity of Catastrophic Health-care Expenditure for Type 2 Diabetes Mellitus Care in Iran: Determinants and Inequality

Author

Piroozi B, Mohamadi-Bolbanabad A, Moradi G, Safari H, Ghafoori S, Zarezade Y, Bidarpour F, and Rezaei S

Subjects
catastrophic cost, diabetes, inequalities, socioeconomic status, Specialties of internal medicine, RC581-951
Abstract

Bakhtiar Piroozi,1 Amjad Mohamadi-Bolbanabad,1 Ghobad Moradi,1 Hossein Safari,2 Shahnaz Ghafoori,1 Yadolah Zarezade,1 Farzam Bidarpour,1 Satar Rezaei3 1Social Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran; 2Health Promotion Research Center, Iran University of Medical Science, Tehran, Iran; 3Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, IranCorrespondence: Satar RezaeiResearch Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, IranEmail satarrezaei@gmail.comBackground: The present study aimed to assess the prevalence and intensity of catastrophic health-care expenditures (CHE) relating to type 2 diabetes mellitus care and inequality in facing such expenditures in Iran.Methods: A total of 1065 type 2 diabetes patients were included in this cross-sectional study. A multistage sampling method was used to select the samples. Data on sociodemographic characteristics, economic status, health and diabetic costs were collected using a self-constructed questionnaire. We used capacity to pay (CTP) of households to calculate the incidence of CHE due to diabetic care at four different thresholds. The mean positive overshoot (MPO) and overshoot were used to assess the intensity of CHE. The relative concentration index and slope index of inequality (SII) were used to measure socioeconomic-related inequalities in incidences of CHE. In addition, decomposition methods were used to identify the main factors affecting observed inequality in CHE.Results: The incidence of CHE at the 10, 20, 30, and 40% of CTP thresholds for type 2 diabetes mellitus care was 57.5, 28.9, 16.5, and 11.4%, respectively. The results of CI and SII indices for CHE due to diabetic care indicated that the incidence of CHE was more prevalent among patients with lower socioeconomic groups. The decomposition analysis showed that the socioeconomic status, marital status and gender of patients were the main factors contributing to socioeconomic inequality in incidence of CHE among the poor.Conclusion: Our study demonstrated that the incidence and intensity of CHE due to diabetic care were relatively high, particularly among socioeconomically disadvantaged patients. Modification to the present health care financing strategies is recommended in order to protect lower socioeconomic groups against the financial burden of diabetic care.Keywords: catastrophic cost, diabetes, inequalities, socioeconomic status

Published
2020

38. Global, regional, and national burden of allergic disorders and their risk factors in 204 countries and territories, from 1990 to 2019: A systematic analysis for the Global Burden of Disease Study 2019

Author

Shin, Y, Hwang, J, Kwon, R, Lee, S, Kim, M, Abate, Y, Abbasi-Kangevari, M, Abbasi-Kangevari, Z, Abdelmasseh, M, Abdulah, D, Aboagye, R, Abolhassani, H, Abrams, E, Abtew, Y, Abu-Gharbieh, E, Adane, D, Adane, T, Addo, I, Adha, R, Adibi, A, Adnani, Q, Agrawal, A, Ahmad, S, Ahmadi, A, Ahmed, A, Al-Azzam, S, Alhalaiqa, F, Alif, S, Alipour, V, Altaany, Z, Altirkawi, K, Alvis-Guzman, N, Aly, H, Ansar, A, Arulappan, J, Asghari-Jafarabadi, M, Ashraf, T, Athari, S, Atlaw, D, Aujayeb, A, Azadnajafabad, S, Babaei, M, Babamohamadi, H, Badawi, A, Baghcheghi, N, Bagherieh, S, Bajbouj, K, Banach, M, Bardhan, M, Barone-Adesi, F, Barrow, A, Bashiri, A, Bayileyegn, N, Bensenor, I, Berhie, A, Beyene, K, Bhagavathula, A, Bhardwaj, P, Bhat, A, Bhojaraja, V, Bijani, A, Bikov, A, Cai, J, Camargos, P, Car, J, Carr, S, Carugno, A, Chakraborty, P, Chan, J, Charalampous, P, Chashmyazdan, M, Chattu, V, Chowdhury, M, Chu, D, Corso, B, Cruz-Martins, N, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Demeke, D, Demisse, B, Diaz, D, Diress, M, Dongarwar, D, Ekholuenetale, M, Ekundayo, T, Elhadi, M, Elmeligy, O, Esubalew, H, Etaee, F, Etemadimanesh, A, Fagbamigbe, A, Fakhradiyev, I, Fatehizadeh, A, Fatima, S, Feng, X, Fereidouni, M, Ferreira, N, Fetensa, G, Fischer, F, Foroutan, M, Fukumoto, T, Gaipov, A, Gela, Y, Obsa, A, Ghadirian, F, Ghamari, S, Ghozy, S, Gillum, R, Gizaw, A, Goldust, M, Golechha, M, Goleij, P, Gupta, S, Gupta, V, Haj-Mirzaian, A, Halwani, R, Hamidi, S, Hannan, M, Hasaballah, A, Hasani, H, Hashi, A, Hassen, M, Heibati, B, Heidari, G, Heidari, M, Heidari-Foroozan, M, Holla, R, Horita, N, Hossain, M, Hussain, S, Hwang, B, Ilic, I, Ilic, M, Irilouzadian, R, Ismail, N, Ispayeva, Z, Iwu, C, Linda Merin, J, Jajarmi, M, Jamshidi, E, Janodia, M, Jayaram, S, Jebai, R, Jonas, J, Joseph, N, Kaambwa, B, Kabir, Z, Kaliyadan, F, Kandel, H, Kantar, R, Karaye, I, Karimi, H, Kaur, H, Keikavoosi-Arani, L, Keykhaei, M, Khader, Y, Khajuria, H, Khan, I, Khan, M, Khanal, S, Khatatbeh, M, Khubchandani, J, Kibret, B, Kisa, A, Kisa, S, Kolkhir, P, Kompani, F, Koohestani, H, Korzh, O, Koul, P, Koyanagi, A, Krishan, K, Kuehni, C, Kumar, G, Kurmi, O, Kutikuppala, L, Kuttikkattu, A, Lam, J, Larijani, B, Latief, K, Lauriola, P, Le, T, Lee, Y, Lenzi, J, Li, M, Li, S, Ligade, V, Lim, S, Liu, W, Liu, X, Lo, C, Lopes, G, Mahalingam, S, Maharaj, S, Mahmoud, M, Majeed, A, Malekpour, M, Malik, A, Mallhi, T, Malta, D, Mamun, A, Masoumi, S, Maugeri, A, Medina, J, Menezes, R, Mensah, G, Mentis, A, Mestrovic, T, Michalek, I, Minh, L, Mirrakhimov, E, Misganaw, A, Mishra, M, Mohammed, S, Mokdad, A, Momtazmanesh, S, Monasta, L, Moniruzzaman, M, Mulugeta, T, Munblit, D, Murillo-Zamora, E, Mustafa, G, Nair, T, Nangia, V, Swamy, S, Nassereldine, H, Natto, Z, Nayak, B, Nazari, J, Ng, T, Nguyen, D, Nguyen, V, Niazi, R, Nouraei, H, Nzoputam, O, Oancea, B, Obaidur, R, Okati-Aliabad, H, Okonji, O, Okwute, P, Olagunju, A, Olufadewa, I, Orru, H, Mahesh, P, Padubidri, J, Pandey, A, Pardhan, S, Park, E, Patel, J, Patil, S, Patthipati, V, Paudel, U, Pereira, M, Pereira, R, Petcu, I, Podder, I, Podder, V, Mohammad, A, Qattea, I, Rabiee, N, Rahimi, M, Rahman, M, Rahmani, A, Rahmani, S, Rahmanian, V, Rajput, P, Ram, P, Ramasubramani, P, Rao, I, Rashid, A, Ratan, Z, Ravikumar, N, Rawaf, S, Rawal, L, Redwan, E, Regmi, A, Rezaei, N, Rezaei, S, Rezaeian, M, Rodriguez, J, Roever, L, Romero-Rodriguez, E, Ronfani, L, Saad, A, Saddik, B, Saeed, U, Sagoe, D, Sharif-Askari, F, Sahebkar, A, Sahoo, H, Sajid, M, Sakshaug, J, Salahi, S, Salehi, S, Samy, A, Santric-Milicevic, M, Sarasmita, M, Sarkhosh, M, Saya, G, Senthilkumaran, S, Shah, H, Shaikh, M, Shanawaz, M, Sheikh, A, Shekhar, S, Shigematsu, M, Shobeiri, P, Shorofi, S, Sibhat, M, Simpson, C, Singh, J, Singh, P, Singh, S, Singh, V, Siraj, M, Skryabina, A, Solomon, Y, Song, S, Soshnikov, S, Soyiri, I, Steiropoulos, P, Szeto, M, Talaat, I, Tamuzi, J, Tan, K, Tat, N, Temsah, M, Terefa, D, Tesler, R, Thangaraju, P, Ticoalu, J, Tillawi, T, Tran, M, Tusa, B, Ullah, I, Ullah, S, Upadhyay, E, Vahabi, S, van Boven, J, Vasankari, T, Verras, G, Vieira, R, Violante, F, Vos, T, Westerman, R, Wickramasinghe, N, Williams, H, Yada, D, Yismaw, Y, Yonemoto, N, Yu, C, Yunusa, I, Zahir, M, Zar, H, Zare, I, Zastrozhin, M, Zeineddine, M, Zenebe, G, Zhang, Z, Zhao, H, Zoladl, M, Shin, J, Yon, D, Shin Y. H., Hwang J., Kwon R., Lee S. W., Kim M. S., Abate Y. H., Abbasi-Kangevari M., Abbasi-Kangevari Z., Abdelmasseh M., Abdulah D. M., Aboagye R. G., Abolhassani H., Abrams E. M., Abtew Y. D., Abu-Gharbieh E., Adane D. E. A., Adane T. D., Addo I. Y., Adha R., Adibi A., Adnani Q. E. S., Agrawal A., Ahmad S., Ahmadi A., Ahmed A., Al-Azzam S., Alhalaiqa F. A. N., Alif S. M., Alipour V., Altaany Z., Altirkawi K. A., Alvis-Guzman N., Aly H., Ansar A., Arulappan J., Asghari-Jafarabadi M., Ashraf T., Athari S. S., Atlaw D., Aujayeb A., Azadnajafabad S., Babaei M., Babamohamadi H., Badawi A., Baghcheghi N., Bagherieh S., Bajbouj K., Banach M., Bardhan M., Barone-Adesi F., Barrow A., Bashiri A., Bayileyegn N. S., Bensenor I. M., Berhie A. Y., Beyene K. A., Bhagavathula A. S., Bhardwaj P., Bhat A. N., Bhojaraja V. S., Bijani A., Bikov A., Cai J., Camargos P., Car J., Carr S., Carugno A., Chakraborty P. A., Chan J. S. K., Charalampous P., Chashmyazdan M., Chattu V. K., Chowdhury M. A. K., Chu D. -T., Corso B., Cruz-Martins N., Dadras O., Dai X., Damiani G., Dandona L., Dandona R., Demeke D., Demisse B., Diaz D., Diress M., Dongarwar D., Ekholuenetale M., Ekundayo T. C., Elhadi M., Elmeligy O. A. A., Esubalew H., Etaee F., Etemadimanesh A., Fagbamigbe A. F., Fakhradiyev I. R., Fatehizadeh A., Fatima S. A. F., Feng X., Fereidouni M., Ferreira N., Fetensa G., Fischer F., Foroutan M., Fukumoto T., Gaipov A., Gela Y. Y., Obsa A. G., Ghadirian F., Ghamari S. -H., Ghozy S., Gillum R. F., Gizaw A. T., Gizaw A. B. A. B., Goldust M., Golechha M., Goleij P., Gupta S., Gupta V. K., Haj-Mirzaian A., Halwani R., Hamidi S., Hannan M. A., Hasaballah A. I., Hasani H., Hashi A., Hassen M. B., Heibati B., Heidari G., Heidari M., Heidari-Foroozan M., Holla R., Horita N., Hossain M. S., Hussain S., Hwang B. -F., Ilic I. M., Ilic M. D., Irilouzadian R., Ismail N. E., Ispayeva Z. B. I. Z. B., Iwu C. C. D., Linda Merin J., Jajarmi M., Jamshidi E., Janodia M. D., Jayaram S., Jebai R., Jonas J. B., Joseph N., Kaambwa B., Kabir Z., Kaliyadan F., Kandel H., Kantar R. S., Karaye I. M., Karimi H., Kaur H., Keikavoosi-Arani L., Keykhaei M., Khader Y. S., Khajuria H., Khan I. A., Khan M., Khan M. A. B., Khanal S., Khatatbeh M. M., Khubchandani J., Kibret B. G., Kisa A., Kisa S., Kolkhir P., Kompani F., Koohestani H. R., Korzh O., Koul P. A., Koyanagi A., Krishan K., Kuehni C. E., Kumar G. A., Kurmi O. P., Kutikuppala L. V. S., Kuttikkattu A., Lam J., Larijani B., Latief K., Lauriola P., Le T. T. T., Lee Y. H., Lenzi J., Li M. -C., Li S., Ligade V. S., Lim S. S., Liu W., Liu X., Lo C. -H., Lopes G., Mahalingam S., Maharaj S. B., Mahmoud M. A., Majeed A., Malekpour M. -R., Malik A. A., Mallhi T. H., Malta D. C., Mamun A. A., Masoumi S. Z., Maugeri A., Medina J. R. C., Menezes R. G., Mensah G. A., Mentis A. -F. A., Mestrovic T., Michalek I. M., Minh L. H. N., Mirrakhimov E. M., Misganaw A., Mishra M., Mohammed S., Mokdad A. H., Momtazmanesh S., Monasta L., Moniruzzaman M., Mulugeta T., Munblit D., Murillo-Zamora E., Mustafa G., Nair T. S., Nangia V., Swamy S. N., Nassereldine H., Natto Z. S., Nayak B. P., Nazari J., Ng T. P., Nguyen D. H., Nguyen V. T., Niazi R. K., Nouraei H., Nzoputam O. J., Oancea B., Obaidur R. M., Okati-Aliabad H., Okonji O. C., Okwute P. G., Olagunju A. T., Olufadewa I. I., Orru H., Mahesh P. A., Padubidri J. R., Pandey A., Pardhan S., Park E. -K., Patel J., Patil S., Patthipati V. S., Paudel U., Pereira M., Pereira R. B., Petcu I. -R., Podder I., Podder V., Mohammad A. P., Qattea I., Rabiee N., Rahimi M., Rahman M., Rahman M. A., Rahmani A. M., Rahmani S., Rahmanian V., Rajput P., Ram P., Ramasubramani P., Rao I. R., Rashid A. M., Ratan Z. A., Ravikumar N., Rawaf S., Rawal L., Redwan E. M. M., Regmi A. R., Rezaei N., Rezaei S., Rezaeian M., Rodriguez J. A. B., Roever L., Romero-Rodriguez E., Ronfani L., Saad A. M. A., Saddik B., Saeed U., Sagoe D., Sharif-Askari F. S., Sahebkar A., Sahoo H., Sajid M. R., Sakshaug J. W., Salahi S., Salehi S., Samy A. M., Santric-Milicevic M. M., Sarasmita M. A., Sarkhosh M., Saya G. K., Senthilkumaran S., Shah H., Shaikh M. A., Shanawaz M., Sheikh A., Shekhar S., Shigematsu M., Shobeiri P., Shorofi S. A., Sibhat M. M., Simpson C. R., Singh J. A., Singh P., Singh S., Singh V., Siraj M. S., Skryabina A. A., Solomon Y., Song S., Soshnikov S., Soyiri I. N., Steiropoulos P., Szeto M. D., Talaat I. M., Tamuzi J. J. L. L., Tan K. -K., Tat N. Y., Temsah M. -H., Terefa D. R., Tesler R., Thangaraju P., Ticoalu J. H. V., Tillawi T., Tran M. T. N., Tusa B. S., Ullah I., Ullah S., Upadhyay E., Vahabi S. M., van Boven J. F. M., Vasankari T. J., Verras G. -I., Vieira R. J., Violante F. S., Vos T., Westerman R., Wickramasinghe N. D., Williams H. C., Yada D. Y., Yismaw Y., Yonemoto N., Yu C., Yunusa I., Zahir M., Zar H. J., Zare I., Zastrozhin M. S., Zeineddine M. A., Zenebe G. A., Zhang Z. -J., Zhao H., Zoladl M., Shin J. I., Yon D. K., Shin, Y, Hwang, J, Kwon, R, Lee, S, Kim, M, Abate, Y, Abbasi-Kangevari, M, Abbasi-Kangevari, Z, Abdelmasseh, M, Abdulah, D, Aboagye, R, Abolhassani, H, Abrams, E, Abtew, Y, Abu-Gharbieh, E, Adane, D, Adane, T, Addo, I, Adha, R, Adibi, A, Adnani, Q, Agrawal, A, Ahmad, S, Ahmadi, A, Ahmed, A, Al-Azzam, S, Alhalaiqa, F, Alif, S, Alipour, V, Altaany, Z, Altirkawi, K, Alvis-Guzman, N, Aly, H, Ansar, A, Arulappan, J, Asghari-Jafarabadi, M, Ashraf, T, Athari, S, Atlaw, D, Aujayeb, A, Azadnajafabad, S, Babaei, M, Babamohamadi, H, Badawi, A, Baghcheghi, N, Bagherieh, S, Bajbouj, K, Banach, M, Bardhan, M, Barone-Adesi, F, Barrow, A, Bashiri, A, Bayileyegn, N, Bensenor, I, Berhie, A, Beyene, K, Bhagavathula, A, Bhardwaj, P, Bhat, A, Bhojaraja, V, Bijani, A, Bikov, A, Cai, J, Camargos, P, Car, J, Carr, S, Carugno, A, Chakraborty, P, Chan, J, Charalampous, P, Chashmyazdan, M, Chattu, V, Chowdhury, M, Chu, D, Corso, B, Cruz-Martins, N, Dadras, O, Dai, X, Damiani, G, Dandona, L, Dandona, R, Demeke, D, Demisse, B, Diaz, D, Diress, M, Dongarwar, D, Ekholuenetale, M, Ekundayo, T, Elhadi, M, Elmeligy, O, Esubalew, H, Etaee, F, Etemadimanesh, A, Fagbamigbe, A, Fakhradiyev, I, Fatehizadeh, A, Fatima, S, Feng, X, Fereidouni, M, Ferreira, N, Fetensa, G, Fischer, F, Foroutan, M, Fukumoto, T, Gaipov, A, Gela, Y, Obsa, A, Ghadirian, F, Ghamari, S, Ghozy, S, Gillum, R, Gizaw, A, Goldust, M, Golechha, M, Goleij, P, Gupta, S, Gupta, V, Haj-Mirzaian, A, Halwani, R, Hamidi, S, Hannan, M, Hasaballah, A, Hasani, H, Hashi, A, Hassen, M, Heibati, B, Heidari, G, Heidari, M, Heidari-Foroozan, M, Holla, R, Horita, N, Hossain, M, Hussain, S, Hwang, B, Ilic, I, Ilic, M, Irilouzadian, R, Ismail, N, Ispayeva, Z, Iwu, C, Linda Merin, J, Jajarmi, M, Jamshidi, E, Janodia, M, Jayaram, S, Jebai, R, Jonas, J, Joseph, N, Kaambwa, B, Kabir, Z, Kaliyadan, F, Kandel, H, Kantar, R, Karaye, I, Karimi, H, Kaur, H, Keikavoosi-Arani, L, Keykhaei, M, Khader, Y, Khajuria, H, Khan, I, Khan, M, Khanal, S, Khatatbeh, M, Khubchandani, J, Kibret, B, Kisa, A, Kisa, S, Kolkhir, P, Kompani, F, Koohestani, H, Korzh, O, Koul, P, Koyanagi, A, Krishan, K, Kuehni, C, Kumar, G, Kurmi, O, Kutikuppala, L, Kuttikkattu, A, Lam, J, Larijani, B, Latief, K, Lauriola, P, Le, T, Lee, Y, Lenzi, J, Li, M, Li, S, Ligade, V, Lim, S, Liu, W, Liu, X, Lo, C, Lopes, G, Mahalingam, S, Maharaj, S, Mahmoud, M, Majeed, A, Malekpour, M, Malik, A, Mallhi, T, Malta, D, Mamun, A, Masoumi, S, Maugeri, A, Medina, J, Menezes, R, Mensah, G, Mentis, A, Mestrovic, T, Michalek, I, Minh, L, Mirrakhimov, E, Misganaw, A, Mishra, M, Mohammed, S, Mokdad, A, Momtazmanesh, S, Monasta, L, Moniruzzaman, M, Mulugeta, T, Munblit, D, Murillo-Zamora, E, Mustafa, G, Nair, T, Nangia, V, Swamy, S, Nassereldine, H, Natto, Z, Nayak, B, Nazari, J, Ng, T, Nguyen, D, Nguyen, V, Niazi, R, Nouraei, H, Nzoputam, O, Oancea, B, Obaidur, R, Okati-Aliabad, H, Okonji, O, Okwute, P, Olagunju, A, Olufadewa, I, Orru, H, Mahesh, P, Padubidri, J, Pandey, A, Pardhan, S, Park, E, Patel, J, Patil, S, Patthipati, V, Paudel, U, Pereira, M, Pereira, R, Petcu, I, Podder, I, Podder, V, Mohammad, A, Qattea, I, Rabiee, N, Rahimi, M, Rahman, M, Rahmani, A, Rahmani, S, Rahmanian, V, Rajput, P, Ram, P, Ramasubramani, P, Rao, I, Rashid, A, Ratan, Z, Ravikumar, N, Rawaf, S, Rawal, L, Redwan, E, Regmi, A, Rezaei, N, Rezaei, S, Rezaeian, M, Rodriguez, J, Roever, L, Romero-Rodriguez, E, Ronfani, L, Saad, A, Saddik, B, Saeed, U, Sagoe, D, Sharif-Askari, F, Sahebkar, A, Sahoo, H, Sajid, M, Sakshaug, J, Salahi, S, Salehi, S, Samy, A, Santric-Milicevic, M, Sarasmita, M, Sarkhosh, M, Saya, G, Senthilkumaran, S, Shah, H, Shaikh, M, Shanawaz, M, Sheikh, A, Shekhar, S, Shigematsu, M, Shobeiri, P, Shorofi, S, Sibhat, M, Simpson, C, Singh, J, Singh, P, Singh, S, Singh, V, Siraj, M, Skryabina, A, Solomon, Y, Song, S, Soshnikov, S, Soyiri, I, Steiropoulos, P, Szeto, M, Talaat, I, Tamuzi, J, Tan, K, Tat, N, Temsah, M, Terefa, D, Tesler, R, Thangaraju, P, Ticoalu, J, Tillawi, T, Tran, M, Tusa, B, Ullah, I, Ullah, S, Upadhyay, E, Vahabi, S, van Boven, J, Vasankari, T, Verras, G, Vieira, R, Violante, F, Vos, T, Westerman, R, Wickramasinghe, N, Williams, H, Yada, D, Yismaw, Y, Yonemoto, N, Yu, C, Yunusa, I, Zahir, M, Zar, H, Zare, I, Zastrozhin, M, Zeineddine, M, Zenebe, G, Zhang, Z, Zhao, H, Zoladl, M, Shin, J, Yon, D, Shin Y. H., Hwang J., Kwon R., Lee S. W., Kim M. S., Abate Y. H., Abbasi-Kangevari M., Abbasi-Kangevari Z., Abdelmasseh M., Abdulah D. M., Aboagye R. G., Abolhassani H., Abrams E. M., Abtew Y. D., Abu-Gharbieh E., Adane D. E. A., Adane T. D., Addo I. Y., Adha R., Adibi A., Adnani Q. E. S., Agrawal A., Ahmad S., Ahmadi A., Ahmed A., Al-Azzam S., Alhalaiqa F. A. N., Alif S. M., Alipour V., Altaany Z., Altirkawi K. A., Alvis-Guzman N., Aly H., Ansar A., Arulappan J., Asghari-Jafarabadi M., Ashraf T., Athari S. S., Atlaw D., Aujayeb A., Azadnajafabad S., Babaei M., Babamohamadi H., Badawi A., Baghcheghi N., Bagherieh S., Bajbouj K., Banach M., Bardhan M., Barone-Adesi F., Barrow A., Bashiri A., Bayileyegn N. S., Bensenor I. M., Berhie A. Y., Beyene K. A., Bhagavathula A. S., Bhardwaj P., Bhat A. N., Bhojaraja V. S., Bijani A., Bikov A., Cai J., Camargos P., Car J., Carr S., Carugno A., Chakraborty P. A., Chan J. S. K., Charalampous P., Chashmyazdan M., Chattu V. K., Chowdhury M. A. K., Chu D. -T., Corso B., Cruz-Martins N., Dadras O., Dai X., Damiani G., Dandona L., Dandona R., Demeke D., Demisse B., Diaz D., Diress M., Dongarwar D., Ekholuenetale M., Ekundayo T. C., Elhadi M., Elmeligy O. A. A., Esubalew H., Etaee F., Etemadimanesh A., Fagbamigbe A. F., Fakhradiyev I. R., Fatehizadeh A., Fatima S. A. F., Feng X., Fereidouni M., Ferreira N., Fetensa G., Fischer F., Foroutan M., Fukumoto T., Gaipov A., Gela Y. Y., Obsa A. G., Ghadirian F., Ghamari S. -H., Ghozy S., Gillum R. F., Gizaw A. T., Gizaw A. B. A. B., Goldust M., Golechha M., Goleij P., Gupta S., Gupta V. K., Haj-Mirzaian A., Halwani R., Hamidi S., Hannan M. A., Hasaballah A. I., Hasani H., Hashi A., Hassen M. B., Heibati B., Heidari G., Heidari M., Heidari-Foroozan M., Holla R., Horita N., Hossain M. S., Hussain S., Hwang B. -F., Ilic I. M., Ilic M. D., Irilouzadian R., Ismail N. E., Ispayeva Z. B. I. Z. B., Iwu C. C. D., Linda Merin J., Jajarmi M., Jamshidi E., Janodia M. D., Jayaram S., Jebai R., Jonas J. B., Joseph N., Kaambwa B., Kabir Z., Kaliyadan F., Kandel H., Kantar R. S., Karaye I. M., Karimi H., Kaur H., Keikavoosi-Arani L., Keykhaei M., Khader Y. S., Khajuria H., Khan I. A., Khan M., Khan M. A. B., Khanal S., Khatatbeh M. M., Khubchandani J., Kibret B. G., Kisa A., Kisa S., Kolkhir P., Kompani F., Koohestani H. R., Korzh O., Koul P. A., Koyanagi A., Krishan K., Kuehni C. E., Kumar G. A., Kurmi O. P., Kutikuppala L. V. S., Kuttikkattu A., Lam J., Larijani B., Latief K., Lauriola P., Le T. T. T., Lee Y. H., Lenzi J., Li M. -C., Li S., Ligade V. S., Lim S. S., Liu W., Liu X., Lo C. -H., Lopes G., Mahalingam S., Maharaj S. B., Mahmoud M. A., Majeed A., Malekpour M. -R., Malik A. A., Mallhi T. H., Malta D. C., Mamun A. A., Masoumi S. Z., Maugeri A., Medina J. R. C., Menezes R. G., Mensah G. A., Mentis A. -F. A., Mestrovic T., Michalek I. M., Minh L. H. N., Mirrakhimov E. M., Misganaw A., Mishra M., Mohammed S., Mokdad A. H., Momtazmanesh S., Monasta L., Moniruzzaman M., Mulugeta T., Munblit D., Murillo-Zamora E., Mustafa G., Nair T. S., Nangia V., Swamy S. N., Nassereldine H., Natto Z. S., Nayak B. P., Nazari J., Ng T. P., Nguyen D. H., Nguyen V. T., Niazi R. K., Nouraei H., Nzoputam O. J., Oancea B., Obaidur R. M., Okati-Aliabad H., Okonji O. C., Okwute P. G., Olagunju A. T., Olufadewa I. I., Orru H., Mahesh P. A., Padubidri J. R., Pandey A., Pardhan S., Park E. -K., Patel J., Patil S., Patthipati V. S., Paudel U., Pereira M., Pereira R. B., Petcu I. -R., Podder I., Podder V., Mohammad A. P., Qattea I., Rabiee N., Rahimi M., Rahman M., Rahman M. A., Rahmani A. M., Rahmani S., Rahmanian V., Rajput P., Ram P., Ramasubramani P., Rao I. R., Rashid A. M., Ratan Z. A., Ravikumar N., Rawaf S., Rawal L., Redwan E. M. M., Regmi A. R., Rezaei N., Rezaei S., Rezaeian M., Rodriguez J. A. B., Roever L., Romero-Rodriguez E., Ronfani L., Saad A. M. A., Saddik B., Saeed U., Sagoe D., Sharif-Askari F. S., Sahebkar A., Sahoo H., Sajid M. R., Sakshaug J. W., Salahi S., Salehi S., Samy A. M., Santric-Milicevic M. M., Sarasmita M. A., Sarkhosh M., Saya G. K., Senthilkumaran S., Shah H., Shaikh M. A., Shanawaz M., Sheikh A., Shekhar S., Shigematsu M., Shobeiri P., Shorofi S. A., Sibhat M. M., Simpson C. R., Singh J. A., Singh P., Singh S., Singh V., Siraj M. S., Skryabina A. A., Solomon Y., Song S., Soshnikov S., Soyiri I. N., Steiropoulos P., Szeto M. D., Talaat I. M., Tamuzi J. J. L. L., Tan K. -K., Tat N. Y., Temsah M. -H., Terefa D. R., Tesler R., Thangaraju P., Ticoalu J. H. V., Tillawi T., Tran M. T. N., Tusa B. S., Ullah I., Ullah S., Upadhyay E., Vahabi S. M., van Boven J. F. M., Vasankari T. J., Verras G. -I., Vieira R. J., Violante F. S., Vos T., Westerman R., Wickramasinghe N. D., Williams H. C., Yada D. Y., Yismaw Y., Yonemoto N., Yu C., Yunusa I., Zahir M., Zar H. J., Zare I., Zastrozhin M. S., Zeineddine M. A., Zenebe G. A., Zhang Z. -J., Zhao H., Zoladl M., Shin J. I., and Yon D. K.

Abstract

Background: Asthma and atopic dermatitis (AD) are chronic allergic conditions, along with allergic rhinitis and food allergy and cause high morbidity and mortality both in children and adults. This study aims to evaluate the global, regional, national, and temporal trends of the burden of asthma and AD from 1990 to 2019 and analyze their associations with geographic, demographic, social, and clinical factors. Methods: Using data from the Global Burden of Diseases (GBD), Injuries, and Risk Factors Study 2019, we assessed the age-standardized prevalence, incidence, mortality, and disability-adjusted life years (DALYs) of both asthma and AD from 1990 to 2019, stratified by geographic region, age, sex, and socio-demographic index (SDI). DALYs were calculated as the sum of years lived with disability and years of life lost to premature mortality. Additionally, the disease burden of asthma attributable to high body mass index, occupational asthmagens, and smoking was described. Results: In 2019, there were a total of 262 million [95% uncertainty interval (UI): 224–309 million] cases of asthma and 171 million [95% UI: 165–178 million] total cases of AD globally; age-standardized prevalence rates were 3416 [95% UI: 2899–4066] and 2277 [95% UI: 2192–2369] per 100,000 population for asthma and AD, respectively, a 24.1% [95% UI: −27.2 to −20.8] decrease for asthma and a 4.3% [95% UI: 3.8–4.8] decrease for AD compared to baseline in 1990. Both asthma and AD had similar trends according to age, with age-specific prevalence rates peaking at age 5–9 years and rising again in adulthood. The prevalence and incidence of asthma and AD were both higher for individuals with higher SDI; however, mortality and DALYs rates of individuals with asthma had a reverse trend, with higher mortality and DALYs rates in those in the lower SDI quintiles. Of the three risk factors, high body mass index contributed to the highest DALYs and deaths due to asthma, accounting for a total of 3.65 million [9

Published
2023

39. Substitution effects of Ag/Cu and Al/Cu on Y123 samples: Hall anomaly and transport properties

Author

Nazarzadehmoafi, M., Daadmehr, V., Rezakhani, A. T., Falahati, S., Saeb, F., and Rezaei, S. Barekat

Subjects
Condensed Matter - Superconductivity
Abstract

The Hall effect and its associated anomalies offer an important means for describing superconducting property in cuprate compounds. Here, we investigate the electron- and hole-doping effects (implemented through Al- and Ag-doping, respectively) on the Hall effect and transport properties of Y123 superconducting materials (YBa2Cu3-xXxO7-d; X= Ag, Al). The Hall anomaly, in both normal and vortex states, generally depends on multiple factors, such as temperature, magnetic field, and amount/type of doping. Specifically, for our samples, we observed that hole doping first enhances the critical temperature TC, whereas its excess beyond a threshold value (here x=0.15) decreases TC; electron doping, however, decreases TC. We also show how doping changes the critical current density JC at temperature 77K with magnetic field 9kOe. More importantly, all of our samples exhibited one Hall sign reversal. Interestingly, behavior of the Hall coefficient vs. temperature reveals that the Hall dip vs. magnetic field for Ag - doped samples shows a behavior opposite to that for Al-doped samples., Comment: 19 pages, 9 figures, and 3 tables

Published
2011

40. Joint production-planning and distribution optimization of perishable products under a combined shipment structure: A new hybrid policy-based approach.

Author

Rezaei, S. and Kheirkhah, A.

Subjects
PRODUCTION planning, SUPPLY chains, BATCH processing, HEURISTIC, CONSUMERS
Abstract

Following the pioneering challenge for joint optimization of decisions in supply chains, this paper newly provides an integrated framework to efficiently fulfill a productionplanning and distribution problem in effect. In such an integrated scheme, a set of perishable family products is manufactured on a single batch-processing machine. These products are dispatched to the customers by a third-party logistics service provider with only two types of licensed eco-friendly transportation facilities. In order to efficiently deliver the manufactured products before they become unusable, we propose a combined shipment structure. To accomplish this, the problem is formulated in the context of a mixedinteger linear programming model. In particular, we aim to establish two manufacturing policies based on both increasing and decreasing rates of production and also two delivery policies expressing distinct preferences in fulfilling the customers' demands. The cost structures obtained from the established integrated planning and the resulting distribution configurations are investigated as well. Further, four heuristic algorithms are developed for solving the problem for each hybrid production/distribution scheme derived from the former policies. A numerical study is conducted to compare the mentioned procedures, illustrating the preferable efficiency of the plan obtained through the hybridization of the increasing-production-rate and decreasing-delivery-distance policies. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
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50. Preferences of Medical Sciences Students for Work Contracts in Deprived Areas of Iran: A Discrete Choice Experiment Analysis [Erratum]

Author

Kazemi Karyani A, Karami Matin B, Malekian P, Moradi Rotvandi D, Amini S, Delavari S, Soltani S, and Rezaei S

Subjects
preferences, contracts, medical students, deprived areas, Public aspects of medicine, RA1-1270
Abstract

Kazemi Karyani A, Karami Matin B, Malekian P, et al. Risk Manag Healthc Policy. 2020;13:927–939. The authors have advised that there is an error in Table 3 of the published paper which was introduced by the Editorial staff during the publication process. Page 935, Table 3, Major, Medicine, aOR column, Workload (base: low), Moderate row the value “41.15” should read “1.15”. Read the original article

Published
2021

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