Author: "Moniruzzaman, Md." / Publication Type: Electronic Resources - Searchworks@Jio Institute Digital Library Search Results

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35 results on '"Moniruzzaman, Md."'

1. Rural women, energy poverty and energy justice in the East Central region of Bangladesh

Author: Moniruzzaman, Md
Subjects: 333.79, GE Environmental Sciences, HQ The family. Marriage. Woman
Abstract: This research explored the gender dimension of energy poverty in rural Bangladesh. Women’s energy poverty in their everyday lives was investigated and its effects compared with men’s experience. The research also scrutinised whether energy poverty was derived from or reinforced by energy injustice, and explored whether energy poverty has any relationship with the economic situation of women. A qualitative research approach was used, consisting of in depth interviews and observation methods. The research revealed that women’s ‘energy profile’ is not the same as men living in the same household and that they are more affected than men by energy poverty. It also discovered that women’s energy poverty is reinforced due to a lack of ‘energy justice’. All three components of energy justice (distributional justice, justice as recognition and procedural justice) are deficient regarding women in this area. It also found that women’s ability to contribute to the household’s ability to purchase energy can improve their participation in energy decisions at the household level; however, the absence of modern fuel and a reliable power supply, together with patriarchal societal arrangements, restricts women’s opportunity to earn an income. Recommendations for improving the energy situation of women in rural Bangladesh are made.
Published: 2017

2. Transcriptome Profiling of a Salt Excluder Hybrid Grapevine Rootstock Ruggeri throughout Salinity.

Author: Gajjar, Pranavkumar, Gajjar, Pranavkumar, Ismail, Ahmed, Islam, Tabibul, Moniruzzaman, Md, Darwish, Ahmed, Dawood, Ahmed, Mohamed, Ahmed, Haikal, Amr, El-Saady, Abdelkareem, El-Kereamy, Ashraf, Sherif, Sherif, Abazinge, Michael, Kambiranda, Devaiah, El-Sharkawy, Islam, Gajjar, Pranavkumar, Gajjar, Pranavkumar, Ismail, Ahmed, Islam, Tabibul, Moniruzzaman, Md, Darwish, Ahmed, Dawood, Ahmed, Mohamed, Ahmed, Haikal, Amr, El-Saady, Abdelkareem, El-Kereamy, Ashraf, Sherif, Sherif, Abazinge, Michael, Kambiranda, Devaiah, and El-Sharkawy, Islam
Abstract: Salinity is one of the substantial threats to plant productivity and could be escorted by other stresses such as heat and drought. It impairs critical biological processes, such as photosynthesis, energy, and water/nutrient acquisition, ultimately leading to cell death when stress intensity becomes uncured. Therefore, plants deploy several proper processes to overcome such hostile circumstances. Grapevine is one of the most important crops worldwide that is relatively salt-tolerant and preferentially cultivated in hot and semi-arid areas. One of the most applicable strategies for sustainable viticulture is using salt-tolerant rootstock such as Ruggeri (RUG). The rootstock showed efficient capacity of photosynthesis, ROS detoxification, and carbohydrate accumulation under salinity. The current study utilized the transcriptome profiling approach to identify the molecular events of RUG throughout a regime of salt stress followed by a recovery procedure. The data showed progressive changes in the transcriptome profiling throughout salinity, underpinning the involvement of a large number of genes in transcriptional reprogramming during stress. Our results established a considerable enrichment of the biological process GO-terms related to salinity adaptation, such as signaling, hormones, photosynthesis, carbohydrates, and ROS homeostasis. Among the battery of molecular/cellular responses launched upon salinity, ROS homeostasis plays the central role of salt adaptation.
Published: 2024

3. Seedlessness Trait and Genome Editing—A Review

Author: Moniruzzaman, Md, Moniruzzaman, Md, Darwish, Ahmed G, Ismail, Ahmed, El-Kereamy, Ashraf, Tsolova, Violeta, El-Sharkawy, Islam, Moniruzzaman, Md, Moniruzzaman, Md, Darwish, Ahmed G, Ismail, Ahmed, El-Kereamy, Ashraf, Tsolova, Violeta, and El-Sharkawy, Islam
Abstract: Parthenocarpy and stenospermocarpy are the two mechanisms underlying the seedless fruit set program. Seedless fruit occurs naturally and can be produced using hormone application, crossbreeding, or ploidy breeding. However, the two types of breeding are time-consuming and sometimes ineffective due to interspecies hybridization barriers or the absence of appropriate parental genotypes to use in the breeding process. The genetic engineering approach provides a better prospect, which can be explored based on an understanding of the genetic causes underlying the seedlessness trait. For instance, CRISPR/Cas is a comprehensive and precise technology. The prerequisite for using the strategy to induce seedlessness is identifying the crucial master gene or transcription factor liable for seed formation/development. In this review, we primarily explored the seedlessness mechanisms and identified the potential candidate genes underlying seed development. We also discussed the CRISPR/Cas-mediated genome editing approaches and their improvements.
Published: 2023

4. Continuous detection of entry of cell-penetrating peptide transportan 10 into single vesicles

Author: Moghal, Md.Mizanur Rahman, Islam, Md. Zahidul, Sharmin, Sabrina, Levadnyy, Victor, Moniruzzaman, Md., Yamazaki, Masahito, Moghal, Md.Mizanur Rahman, Islam, Md. Zahidul, Sharmin, Sabrina, Levadnyy, Victor, Moniruzzaman, Md., and Yamazaki, Masahito
Published: 2023

5. Structure-aware image translation-based long future prediction for enhancement of ground robotic vehicle teleoperation

Author: Moniruzzaman, Md, Rassau, Alexander, Chai, Douglas, Islam, Syed M. S., Moniruzzaman, Md, Rassau, Alexander, Chai, Douglas, and Islam, Syed M. S.
Abstract: Predicting future frames through image-to-image translation and using these synthetically generated frames for high-speed ground vehicle teleoperation is a new concept to address latency and enhance operational performance. In the immediate previous work, the image quality of the predicted frames was low and a lot of scene detail was lost. To preserve the structural details of objects and improve overall image quality in the predicted frames, several novel ideas are proposed herein. A filter has been designed to remove noise from dense optical flow components resulting from frame rate inconsistencies. The Pix2Pix base network has been modified and a structure-aware SSIM-based perpetual loss function has been implemented. A new dataset of 20 000 training input images and 2000 test input images with a 500 ms delay between the target and input frames has been created. Without any additional video transformation steps, the proposed improved model achieved PSNR of 23.1; SSIM of 0.65; and MS-SSIM of 0.80, a substantial improvement over our previous work. A Fleiss’ kappa score of > 0.40 (0.48 for the modified network and 0.46 for the perpetual loss function) proves the reliability of the model.
Published: 2023

6. Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

Author: Wu, D, Jin, Y, Xing, Y, Abate, M, Abbasian, M, Abbasi-Kangevari, M, Abbasi-Kangevari, Z, Abd-Allah, F, Abdelmasseh, M, Abdollahifar, M, Abdulah, D, Abedi, A, Abedi, V, Abidi, H, Aboagye, R, Abolhassani, H, Abuabara, K, Abyadeh, M, Addo, I, Adeniji, K, Adepoju, A, Adesina, M, Sakilah Adnani, Q, Afarideh, M, Aghamiri, S, Agodi, A, Agrawal, A, Aguilera Arriagada, C, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadi, A, Ahmed, A, Aithala, J, Ajadi, A, Ajami, M, Akbarzadeh-Khiavi, M, Alahdab, F, Albataineh, M, Alemi, S, Saeed Al-Gheethi, A, Ali, L, Alif, S, Almazan, J, Almustanyir, S, Alqahtani, J, Alqasmi, I, Khan Altaf, I, Alvis-Guzman, N, Alvis-Zakzuk, N, Al-Worafi, Y, Aly, H, Amani, R, Amu, H, Amusa, G, Andrei, C, Ansar, A, Ansariniya, H, Anyasodor, A, Arabloo, J, Arefnezhad, R, Arulappan, J, Asghari-Jafarabadi, M, Ashraf, T, Atata, J, Athari, S, Atlaw, D, Wahbi Atout, M, Aujayeb, A, Awan, A, Ayatollahi, H, Azadnajafabad, S, Azzam, A, Badawi, A, Badiye, A, Bagherieh, S, Baig, A, Bantie, B, Barchitta, M, Bardhan, M, Barker-Collo, S, Barone-Adesi, F, Batra, K, Bayileyegn, N, Behnoush, A, Belgaumi, U, Bemanalizadeh, M, Bensenor, I, Beyene, K, Bhagavathula, A, Bhardwaj, P, Bhaskar, S, Bhat, A, Bitaraf, S, Bitra, V, Boloor, A, Bora, K, Botelho, J, Buchbinder, R, Calina, D, Cámera, L, Carvalho, A, Kai Chan, J, Chattu, V, Abebe, E, Chichagi, F, Choi, S, Chou, T, Chu, D, Coberly, K, Costa, V, Couto, R, Cruz-Martins, N, Dadras, O, Dai, X, Damiani, G, Dascalu, A, Dashti, M, Debela, S, Dellavalle, R, Demetriades, A, Demlash, A, Deng, X, Desai, H, Desai, R, Rahman Dewan, S, Dey, S, Dharmaratne, S, Diaz, D, Dibas, M, Dinis-Oliveira, R, Diress, M, Do, T, Doan, D, Dodangeh, M, Dongarwar, D, Dube, J, Dziedzic, A, Ed-Dra, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, Elemam, N, Elhadi, M, Elmehrath, A, Abdou Elmeligy, O, Emamverdi, M, Emeto, T, Esayas, H, Eshetu, H, Etaee, F, Fagbamigbe, A, Faghani, S, Fakhradiyev, I, Fatehizadeh, A, Fathi, M, Feizkhah, A, Fekadu, G, Fereidouni, M, Fereshtehnejad, S, Fernandes, J, Ferrara, P, Fetensa, G, Filip, I, Fischer, F, Foroutan, B, Foroutan, M, Fukumoto, T, Ganesan, B, Belete Gemeda, B, Ghamari, S, Ghasemi, M, Gholamalizadeh, M, Gill, T, Gillum, R, Goldust, M, Golechha, M, Goleij, P, Golinelli, D, Goudarzi, H, Guan, S, Guo, Y, Gupta, B, Gupta, V, Haddadi, R, Hadi, N, Halwani, R, Haque, S, Hasan, I, Hashempour, R, Hassan, A, Hassan, T, Hassanzadeh, S, Hassen, M, Haubold, J, Hayat, K, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Herteliu, C, Hessami, K, Hezam, K, Hiraike, Y, Holla, R, Hosseini, M, Huynh, H, Hwang, B, Ibitoye, S, Ilic, I, Ilic, M, Iranmehr, A, Iravanpour, F, Ismail, N, Iwagami, M, Iwu, C, Jacob, L, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahrami, H, Jakovljevic, M, Jamshidi, E, Jani, C, Janodia, M, Jayapal, S, Jayaram, S, Jeganathan, J, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Vaishali, K, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kaliyadan, F, Kalroozi, F, Kamal, V, Kandel, A, Kandel, H, Kanungo, S, Karami, J, Karaye, I, Karimi, H, Kasraei, H, Kazemian, S, Kebede, S, Keikavoosi-Arani, L, Keykhaei, M, Khader, Y, Khajuria, H, Khamesipour, F, Khan, E, Khan, I, Khan, M, Khatatbeh, H, Khatatbeh, M, Khateri, S, Khayat Kashani, H, Kim, M, Kisa, A, Kisa, S, Koh, H, Kolkhir, P, Korzh, O, Kotnis, A, Koul, P, Koyanagi, A, Krishan, K, Kuddus, M, Kulkarni, V, Kumar, N, Kundu, S, Kurmi, O, La Vecchia, C, Lahariya, C, Laksono, T, Lám, J, Latief, K, Lauriola, P, Lawal, B, Thu Le, T, Bich Le, T, Lee, M, Lee, S, Lee, W, Lee, Y, Lenzi, J, Levi, M, Li, W, Ligade, V, Lim, S, Liu, G, Liu, X, Llanaj, E, Lo, C, Machado, V, Maghazachi, A, Mahmoud, M, Mai, T, Majeed, A, Sanaye, P, Makram, O, Rad, E, Malhotra, K, Malik, A, Malik, I, Mallhi, T, Malta, D, Mansournia, M, Mantovani, L, Martorell, M, Masoudi, S, Masoumi, S, Mathangasinghe, Y, Mathews, E, Mathioudakis, A, Maugeri, A, Mayeli, M, Carabeo Medina, J, Meles, G, Mendes, J, Menezes, R, Mestrovic, T, Michalek, I, Micheletti Gomide Nogueira de Sá, A, Mihretie, E, Nhat Minh, L, Mirfakhraie, R, Mirrakhimov, E, Misganaw, A, Mohamadkhani, A, Mohamed, N, Mohammadi, F, Mohammadi, S, Mohammed, S, Mohan, S, Mohseni, A, Mokdad, A, Momtazmanesh, S, Monasta, L, Moni, M, Moniruzzaman, M, Moradi, Y, Morovatdar, N, Mostafavi, E, Mousavi, P, Mukoro, G, Mulita, A, Mulu, G, Murillo-Zamora, E, Musaigwa, F, Mustafa, G, Muthu, S, Nainu, F, Nangia, V, Swamy, S, Natto, Z, Navaraj, P, Nayak, B, Nazri-Panjaki, A, Negash, H, Nematollahi, M, Nguyen, D, Hien Nguyen, H, Nguyen, H, Nguyen, P, Nguyen, V, Niazi, R, Nikolouzakis, T, Nnyanzi, L, Noreen, M, Nzoputam, C, Nzoputam, O, Oancea, B, Oh, I, Okati-Aliabad, H, Okonji, O, Okwute, P, Olagunju, A, Olatubi, M, Olufadewa, I, Ordak, M, Otstavnov, N, Owolabi, M, Mahesh, P, Padubidri, J, Pak, A, Pakzad, R, Palladino, R, Pana, A, Pantazopoulos, I, Papadopoulou, P, Pardhan, S, Parthasarathi, A, Pashaei, A, Patel, J, Pathan, A, Patil, S, Paudel, U, Pawar, S, Pedersini, P, Pensato, U, Pereira, D, Pereira, J, Pereira, M, Pereira, R, Peres, M, Perianayagam, A, Perna, S, Petcu, I, Pezeshki, P, Pham, H, Philip, A, Piradov, M, Podder, I, Podder, V, Poddighe, D, Sady Prates, E, Qattea, I, Radfar, A, Raee, P, Rafiei, A, Raggi, A, Rahim, F, Rahimi, M, Rahimifard, M, Rahimi-Movaghar, V, Rahman, M, Ur Rahman, M, Rahmani, A, Rahmani, M, Rahmani, S, Rahmanian, V, Ramasubramani, P, Rancic, N, Rao, I, Rashedi, S, Rashid, A, Ravikumar, N, Rawaf, S, Mohamed Redwan, E, Rezaei, N, Rezaeian, M, Ribeiro, D, Rodrigues, M, Buendia Rodriguez, J, Roever, L, Romero-Rodríguez, E, Saad, A, Saddik, B, Sadeghian, S, Saeed, U, Safary, A, Safdarian, M, Safi, S, Saghazadeh, A, Sagoe, D, Sharif-Askari, F, Sharif-Askari, N, Sahebkar, A, Sahoo, H, Sahraian, M, Sajid, M, Sakhamuri, S, Sakshaug, J, Saleh, M, Salehi, L, Salehi, S, Farrokhi, A, Samadzadeh, S, Samargandy, S, Samieefar, N, Samy, A, Sanadgol, N, Sanjeev, R, Sawhney, M, Saya, G, Schuermans, A, Senthilkumaran, S, Sepanlou, S, Sethi, Y, Shafie, M, Shah, H, Shahid, I, Shahid, S, Shaikh, M, Sharfaei, S, Sharma, M, Shayan, M, Shehata, H, Sheikh, A, Shetty, J, Shin, J, Shirkoohi, R, Shitaye, N, Shivakumar, K, Shivarov, V, Shobeiri, P, Siabani, S, Sibhat, M, Siddig, E, Simpson, C, Sinaei, E, Singh, H, Singh, I, Singh, J, Singh, P, Singh, S, Siraj, M, Al Mamun Sohag, A, Solanki, R, Solikhah, S, Solomon, Y, Soltani-Zangbar, M, Sun, J, Szeto, M, Tabarés-Seisdedos, R, Tabatabaei, S, Tabish, M, Taheri, E, Tahvildari, A, Talaat, I, Lukenze Tamuzi, J, Tan, K, Tat, N, Oliaee, R, Tavasol, A, Temsah, M, Thangaraju, P, Tharwat, S, Tibebu, N, Vera Ticoalu, J, Tillawi, T, Tiruye, T, Tiyuri, A, Tovani-Palone, M, Tripathi, M, Tsegay, G, Tualeka, A, Ty, S, Ubah, C, Ullah, S, Umair, M, Umakanthan, S, Upadhyay, E, Vahabi, S, Vaithinathan, A, Tahbaz, S, Valizadeh, R, Varthya, S, Vasankari, T, Venketasubramanian, N, Verras, G, Villafañe, J, Vlassov, V, Vo, D, Waheed, Y, Waris, A, Welegebrial, B, Westerman, R, Wickramasinghe, D, Wickramasinghe, N, Willekens, B, Woldegeorgis, B, Woldemariam, M, Xiao, H, Yada, D, Yahya, G, Yang, L, Yazdanpanah, F, Yon, D, Yonemoto, N, You, Y, Zahir, M, Zaidi, S, Zangiabadian, M, Zare, I, Zeineddine, M, Zemedikun, D, Zeru, N, Zhang, C, Zhao, H, Zhong, C, Zielińska, M, Zoladl, M, Zumla, A, Guo, C, Tam, L, Wu, Dongze, Jin, Yingzhao, Xing, Yuhan, Abate, Melsew Dagne, Abbasian, Mohammadreza, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abd-Allah, Foad, Abdelmasseh, Michael, Abdollahifar, Mohammad-Amin, Abdulah, Deldar Morad, Abedi, Aidin, Abedi, Vida, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Abuabara, Katrina, Abyadeh, Morteza, Addo, Isaac Yeboah, Adeniji, Kayode Nelson, Adepoju, Abiola Victor, Adesina, Miracle Ayomikun, Sakilah Adnani, Qorinah Estiningtyas, Afarideh, Mohsen, Aghamiri, Shahin, Agodi, Antonella, Agrawal, Anurag, Aguilera Arriagada, Constanza Elizabeth, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Sajjad, Ahmad, Sohail, Ahmadi, Ali, Ahmed, Ali, Ahmed, Ayman, Aithala, Janardhana P., Ajadi, Abdullateef Abiodun, Ajami, Marjan, Akbarzadeh-Khiavi, Mostafa, Alahdab, Fares, AlBataineh, Mohammad T., Alemi, Sharifullah, Saeed Al-Gheethi, Adel Ali, Ali, Liaqat, Alif, Sheikh Mohammad, Almazan, Joseph Uy, Almustanyir, Sami, Alqahtani, Jaber S., Alqasmi, Ibrahim, Khan Altaf, Ihsan Ullah, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J., Al-Worafi, Yaser Mohammed, Aly, Hany, Amani, Reza, Amu, Hubert, Amusa, Ganiyu Adeniyi, Andrei, Catalina Liliana, Ansar, Adnan, Ansariniya, Hossein, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Arefnezhad, Reza, Arulappan, Judie, Asghari-Jafarabadi, Mohammad, Ashraf, Tahira, Atata, Jamila Abdulhamid, Athari, Seyyed Shamsadin, Atlaw, Daniel, Wahbi Atout, Maha Moh'd, Aujayeb, Avinash, Awan, Asma Tahir, Ayatollahi, Haleh, Azadnajafabad, Sina, Azzam, Ahmed Y., Badawi, Alaa, Badiye, Ashish D., Bagherieh, Sara, Baig, Atif Amin, Bantie, Berihun Bantie, Barchitta, Martina, Bardhan, Mainak, Barker-Collo, Suzanne Lyn, Barone-Adesi, Francesco, Batra, Kavita, Bayileyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Belgaumi, Uzma Iqbal, Bemanalizadeh, Maryam, Bensenor, Isabela M., Beyene, Kebede A., Bhagavathula, Akshaya Srikanth, Bhardwaj, Pankaj, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bitaraf, Saeid, Bitra, Veera R., Boloor, Archith, Bora, Kaustubh, Botelho, João Silva, Buchbinder, Rachelle, Calina, Daniela, Cámera, Luis Alberto, Carvalho, Andre F., Kai Chan, Jeffrey Shi, Chattu, Vijay Kumar, Abebe, Endeshaw Chekol, Chichagi, Fatemeh, Choi, Sungchul, Chou, Tzu-Chieh, Chu, Dinh-Toi, Coberly, Kaleb, Costa, Vera Marisa, Couto, Rosa A. S., Cruz-Martins, Natália, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dascalu, Ana Maria, Dashti, Mohsen, Debela, Sisay Abebe, Dellavalle, Robert Paul, Demetriades, Andreas K., Demlash, Alemayehu Anley, Deng, Xinlei, Desai, Hardik Dineshbhai, Desai, Rupak, Rahman Dewan, Syed Masudur, Dey, Sourav, Dharmaratne, Samath Dhamminda, Diaz, Daniel, Dibas, Mahmoud, Dinis-Oliveira, Ricardo Jorge, Diress, Mengistie, Do, Thanh Chi, Doan, Duy Khanh, Dodangeh, Masoud, Dodangeh, Milad, Dongarwar, Deepa, Dube, John, Dziedzic, Arkadiusz Marian, Ed-Dra, Abdelaziz, Edinur, Hisham Atan, Eissazade, Negin, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Elemam, Noha Mousaad, Elhadi, Muhammed, Elmehrath, Ahmed O., Abdou Elmeligy, Omar Abdelsadek, Emamverdi, Mehdi, Emeto, Theophilus I., Esayas, Hawi Leul, Eshetu, Habitu Birhan, Etaee, Farshid, Fagbamigbe, Adeniyi Francis, Faghani, Shahriar, Fakhradiyev, Ildar Ravisovich, Fatehizadeh, Ali, Fathi, Mobina, Feizkhah, Alireza, Fekadu, Ginenus, Fereidouni, Mohammad, Fereshtehnejad, Seyed-Mohammad, Fernandes, João C., Ferrara, Pietro, Fetensa, Getahun, Filip, Irina, Fischer, Florian, Foroutan, Behzad, Foroutan, Masoud, Fukumoto, Takeshi, Ganesan, Balasankar, Belete Gemeda, Belete Negese, Ghamari, Seyyed-Hadi, Ghasemi, MohammadReza, Gholamalizadeh, Maryam, Gill, Tiffany K., Gillum, Richard F., Goldust, Mohamad, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Goudarzi, Houman, Guan, Shi-Yang, Guo, Yang, Gupta, Bhawna, Gupta, Veer Bala, Gupta, Vivek Kumar, Haddadi, Rasool, Hadi, Najah R., Halwani, Rabih, Haque, Shafiul, Hasan, Ikramul, Hashempour, Reza, Hassan, Amr, Hassan, Treska S., Hassanzadeh, Sara, Hassen, Mohammed Bheser, Haubold, Johannes, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Heidari-Soureshjani, Reza, Herteliu, Claudiu, Hessami, Kamran, Hezam, Kamal, Hiraike, Yuta, Holla, Ramesh, Hosseini, Mohammad-Salar, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Ilic, Irena M., Ilic, Milena D., Iranmehr, Arad, Iravanpour, Farideh, Ismail, Nahlah Elkudssiah, Iwagami, Masao, Iwu, Chidozie C. D., Jacob, Louis, Jafarinia, Morteza, Jafarzadeh, Abdollah, Jahankhani, Kasra, Jahrami, Haitham, Jakovljevic, Mihajlo, Jamshidi, Elham, Jani, Chinmay T., Janodia, Manthan Dilipkumar, Jayapal, Sathish Kumar, Jayaram, Shubha, Jeganathan, Jayakumar, Jonas, Jost B., Joseph, Abel, Joseph, Nitin, Joshua, Charity Ehimwenma, Vaishali, K., Kaambwa, Billingsley, Kabir, Ali, Kabir, Zubair, Kadashetti, Vidya, Kaliyadan, Feroze, Kalroozi, Fatemeh, Kamal, Vineet Kumar, Kandel, Amit, Kandel, Himal, Kanungo, Srikanta, Karami, Jafar, Karaye, Ibraheem M., Karimi, Hanie, Kasraei, Hengameh, Kazemian, Sina, Kebede, Sewnet Adem, Keikavoosi-Arani, Leila, Keykhaei, Mohammad, Khader, Yousef Saleh, Khajuria, Himanshu, Khamesipour, Faham, Khan, Ejaz Ahmad, Khan, Imteyaz A., Khan, Maseer, Khan, Md Jobair, Khan, Moien A. B., Khan, Muhammad Arslan, Khatatbeh, Haitham, Khatatbeh, Moawiah Mohammad, Khateri, Sorour, Khayat Kashani, Hamid Reza, Kim, Min Seo, Kisa, Adnan, Kisa, Sezer, Koh, Hyun Yong, Kolkhir, Pavel, Korzh, Oleksii, Kotnis, Ashwin Laxmikant, Koul, Parvaiz A., Koyanagi, Ai, Krishan, Kewal, Kuddus, Mohammed, Kulkarni, Vishnutheertha Vishnutheertha, Kumar, Narinder, Kundu, Satyajit, Kurmi, Om P., La Vecchia, Carlo, Lahariya, Chandrakant, Laksono, Tri, Lám, Judit, Latief, Kamaluddin, Lauriola, Paolo, Lawal, Basira Kankia, Thu Le, Thao Thi, Bich Le, Trang Thi, Lee, Munjae, Lee, Seung Won, Lee, Wei-Chen, Lee, Yo Han, Lenzi, Jacopo, Levi, Miriam, Li, Wei, Ligade, Virendra S., Lim, Stephen S., Liu, Gang, Liu, Xuefeng, Llanaj, Erand, Lo, Chun-Han, Machado, Vanessa Sintra, Maghazachi, Azzam A., Mahmoud, Mansour Adam, Mai, Tuan A., Majeed, Azeem, Sanaye, Pantea Majma, Makram, Omar Mohamed, Rad, Elaheh Malakan, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Martorell, Miquel, Masoudi, Sahar, Masoumi, Seyedeh Zahra, Mathangasinghe, Yasith, Mathews, Elezebeth, Mathioudakis, Alexander G., Maugeri, Andrea, Mayeli, Mahsa, Carabeo Medina, John Robert, Meles, Gebrekiros Gebremichael, Mendes, José João, Menezes, Ritesh G., Mestrovic, Tomislav, Michalek, Irmina Maria, Micheletti Gomide Nogueira de Sá, Ana Carolina, Mihretie, Ephrem Tesfaye, Nhat Minh, Le Huu, Mirfakhraie, Reza, Mirrakhimov, Erkin M., Misganaw, Awoke, Mohamadkhani, Ashraf, Mohamed, Nouh Saad, Mohammadi, Faezeh, Mohammadi, Soheil, Mohammed, Salahuddin, Mohammed, Shafiu, Mohan, Syam, Mohseni, Anita, Mokdad, Ali H., Momtazmanesh, Sara, Monasta, Lorenzo, Moni, Mohammad Ali, Moniruzzaman, Md, Moradi, Yousef, Morovatdar, Negar, Mostafavi, Ebrahim, Mousavi, Parsa, Mukoro, George Duke, Mulita, Admir, Mulu, Getaneh Baye, Murillo-Zamora, Efrén, Musaigwa, Fungai, Mustafa, Ghulam, Muthu, Sathish, Nainu, Firzan, Nangia, Vinay, Swamy, Sreenivas Narasimha, Natto, Zuhair S., Navaraj, Perumalsamy, Nayak, Biswa Prakash, Nazri-Panjaki, Athare, Negash, Hadush, Nematollahi, Mohammad Hadi, Nguyen, Dang H., Hien Nguyen, Hau Thi, Nguyen, Hien Quang, Nguyen, Phat Tuan, Nguyen, Van Thanh, Niazi, Robina Khan, Nikolouzakis, Taxiarchis Konstantinos, Nnyanzi, Lawrence Achilles, Noreen, Mamoona, Nzoputam, Chimezie Igwegbe, Nzoputam, Ogochukwu Janet, Oancea, Bogdan, Oh, In-Hwan, Okati-Aliabad, Hassan, Okonji, Osaretin Christabel, Okwute, Patrick Godwin, Olagunju, Andrew T., Olatubi, Matthew Idowu, Olufadewa, Isaac Iyinoluwa, Ordak, Michal, Otstavnov, Nikita, Owolabi, Mayowa O., Mahesh, P. A., Padubidri, Jagadish Rao, Pak, Anton, Pakzad, Reza, Palladino, Raffaele, Pana, Adrian, Pantazopoulos, Ioannis, Papadopoulou, Paraskevi, Pardhan, Shahina, Parthasarathi, Ashwaghosha, Pashaei, Ava, Patel, Jay, Pathan, Aslam Ramjan, Patil, Shankargouda, Paudel, Uttam, Pawar, Shrikant, Pedersini, Paolo, Pensato, Umberto, Pereira, David M., Pereira, Jeevan, Pereira, Maria Odete, Pereira, Renato B., Peres, Mario F. P., Perianayagam, Arokiasamy, Perna, Simone, Petcu, Ionela-Roxana, Pezeshki, Parmida Sadat, Pham, Hoang Tran, Philip, Anil K., Piradov, Michael A., Podder, Indrashis, Podder, Vivek, Poddighe, Dimitri, Sady Prates, Elton Junio, Qattea, Ibrahim, Radfar, Amir, Raee, Pourya, Rafiei, Alireza, Raggi, Alberto, Rahim, Fakher, Rahimi, Mehran, Rahimifard, Mahban, Rahimi-Movaghar, Vafa, Rahman, Md Obaidur, Ur Rahman, Mohammad Hifz, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Mohamed, Rahmani, Shayan, Rahmanian, Vahid, Ramasubramani, Premkumar, Rancic, Nemanja, Rao, Indu Ramachandra, Rashedi, Sina, Rashid, Ahmed Mustafa, Ravikumar, Nakul, Rawaf, Salman, Mohamed Redwan, Elrashdy Moustafa, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaeian, Mohsen, Ribeiro, Daniela, Rodrigues, Mónica, Buendia Rodriguez, Jefferson Antonio, Roever, Leonardo, Romero-Rodríguez, Esperanza, Saad, Aly M. A., Saddik, Basema, Sadeghian, Saeid, Saeed, Umar, Safary, Azam, Safdarian, Mahdi, Safi, Sher Zaman, Saghazadeh, Amene, Sagoe, Dominic, Sharif-Askari, Fatemeh Saheb, Sharif-Askari, Narjes Saheb, Sahebkar, Amirhossein, Sahoo, Harihar, Sahraian, Mohammad Ali, Sajid, Mirza Rizwan, Sakhamuri, Sateesh, Sakshaug, Joseph W., Saleh, Mohamed A., Salehi, Leili, Salehi, Sana, Farrokhi, Amir Salek, Samadzadeh, Sara, Samargandy, Saad, Samieefar, Noosha, Samy, Abdallah M., Sanadgol, Nima, Sanjeev, Rama Krishna, Sawhney, Monika, Saya, Ganesh Kumar, Schuermans, Art, Senthilkumaran, Subramanian, Sepanlou, Sadaf G., Sethi, Yashendra, Shafie, Mahan, Shah, Humaira, Shahid, Izza, Shahid, Samiah, Shaikh, Masood Ali, Sharfaei, Sadaf, Sharma, Manoj, Shayan, Maryam, Shehata, Hatem Samir, Sheikh, Aziz, Shetty, Jeevan K., Shin, Jae Il, Shirkoohi, Reza, Shitaye, Nebiyu Aniley, Shivakumar, K. M., Shivarov, Velizar, Shobeiri, Parnian, Siabani, Soraya, Sibhat, Migbar Mekonnen, Siddig, Emmanuel Edwar, Simpson, Colin R., Sinaei, Ehsan, Singh, Harpreet, Singh, Inderbir, Singh, Jasvinder A., Singh, Paramdeep, Singh, Surjit, Siraj, Md Shahjahan, Al Mamun Sohag, Abdullah, Solanki, Ranjan, Solikhah, Solikhah, Solomon, Yonatan, Soltani-Zangbar, Mohammad Sadegh, Sun, Jing, Szeto, Mindy D., Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabish, Mohammad, Taheri, Ensiyeh, Tahvildari, Azin, Talaat, Iman M., Lukenze Tamuzi, Jacques J. L., Tan, Ker-Kan, Tat, Nathan Y., Oliaee, Razieh Tavakoli, Tavasol, Arian, Temsah, Mohamad-Hani, Thangaraju, Pugazhenthan, Tharwat, Samar, Tibebu, Nigusie Selomon, Vera Ticoalu, Jansje Henny, Tillawi, Tala, Tiruye, Tenaw Yimer, Tiyuri, Amir, Tovani-Palone, Marcos Roberto, Tripathi, Manjari, Tsegay, Guesh Mebrahtom, Tualeka, Abdul Rohim, Ty, Sree Sudha, Ubah, Chukwudi S., Ullah, Saif, Ullah, Sana, Umair, Muhammad, Umakanthan, Srikanth, Upadhyay, Era, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Tahbaz, Sahel Valadan, Valizadeh, Rohollah, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Verras, Georgios-Ioannis, Villafañe, Jorge Hugo, Vlassov, Vasily, Vo, Danh Cao, Waheed, Yasir, Waris, Abdul, Welegebrial, Brhane Gebrehiwot, Westerman, Ronny, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Willekens, Barbara, Woldegeorgis, Beshada Zerfu, Woldemariam, Melat, Xiao, Hong, Yada, Dereje Y., Yahya, Galal, Yang, Lin, Yazdanpanah, Fereshteh, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Zahir, Mazyar, Zaidi, Syed Saoud, Zangiabadian, Moein, Zare, Iman, Zeineddine, Mohammad A., Zemedikun, Dawit T., Zeru, Naod Gebrekrstos, Zhang, Chen, Zhao, Hanqing, Zhong, Chenwen, Zielińska, Magdalena, Zoladl, Mohammad, Zumla, Alimuddin, Guo, Cui, Tam, Lai-shan, Wu, D, Jin, Y, Xing, Y, Abate, M, Abbasian, M, Abbasi-Kangevari, M, Abbasi-Kangevari, Z, Abd-Allah, F, Abdelmasseh, M, Abdollahifar, M, Abdulah, D, Abedi, A, Abedi, V, Abidi, H, Aboagye, R, Abolhassani, H, Abuabara, K, Abyadeh, M, Addo, I, Adeniji, K, Adepoju, A, Adesina, M, Sakilah Adnani, Q, Afarideh, M, Aghamiri, S, Agodi, A, Agrawal, A, Aguilera Arriagada, C, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadi, A, Ahmed, A, Aithala, J, Ajadi, A, Ajami, M, Akbarzadeh-Khiavi, M, Alahdab, F, Albataineh, M, Alemi, S, Saeed Al-Gheethi, A, Ali, L, Alif, S, Almazan, J, Almustanyir, S, Alqahtani, J, Alqasmi, I, Khan Altaf, I, Alvis-Guzman, N, Alvis-Zakzuk, N, Al-Worafi, Y, Aly, H, Amani, R, Amu, H, Amusa, G, Andrei, C, Ansar, A, Ansariniya, H, Anyasodor, A, Arabloo, J, Arefnezhad, R, Arulappan, J, Asghari-Jafarabadi, M, Ashraf, T, Atata, J, Athari, S, Atlaw, D, Wahbi Atout, M, Aujayeb, A, Awan, A, Ayatollahi, H, Azadnajafabad, S, Azzam, A, Badawi, A, Badiye, A, Bagherieh, S, Baig, A, Bantie, B, Barchitta, M, Bardhan, M, Barker-Collo, S, Barone-Adesi, F, Batra, K, Bayileyegn, N, Behnoush, A, Belgaumi, U, Bemanalizadeh, M, Bensenor, I, Beyene, K, Bhagavathula, A, Bhardwaj, P, Bhaskar, S, Bhat, A, Bitaraf, S, Bitra, V, Boloor, A, Bora, K, Botelho, J, Buchbinder, R, Calina, D, Cámera, L, Carvalho, A, Kai Chan, J, Chattu, V, Abebe, E, Chichagi, F, Choi, S, Chou, T, Chu, D, Coberly, K, Costa, V, Couto, R, Cruz-Martins, N, Dadras, O, Dai, X, Damiani, G, Dascalu, A, Dashti, M, Debela, S, Dellavalle, R, Demetriades, A, Demlash, A, Deng, X, Desai, H, Desai, R, Rahman Dewan, S, Dey, S, Dharmaratne, S, Diaz, D, Dibas, M, Dinis-Oliveira, R, Diress, M, Do, T, Doan, D, Dodangeh, M, Dongarwar, D, Dube, J, Dziedzic, A, Ed-Dra, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, Elemam, N, Elhadi, M, Elmehrath, A, Abdou Elmeligy, O, Emamverdi, M, Emeto, T, Esayas, H, Eshetu, H, Etaee, F, Fagbamigbe, A, Faghani, S, Fakhradiyev, I, Fatehizadeh, A, Fathi, M, Feizkhah, A, Fekadu, G, Fereidouni, M, Fereshtehnejad, S, Fernandes, J, Ferrara, P, Fetensa, G, Filip, I, Fischer, F, Foroutan, B, Foroutan, M, Fukumoto, T, Ganesan, B, Belete Gemeda, B, Ghamari, S, Ghasemi, M, Gholamalizadeh, M, Gill, T, Gillum, R, Goldust, M, Golechha, M, Goleij, P, Golinelli, D, Goudarzi, H, Guan, S, Guo, Y, Gupta, B, Gupta, V, Haddadi, R, Hadi, N, Halwani, R, Haque, S, Hasan, I, Hashempour, R, Hassan, A, Hassan, T, Hassanzadeh, S, Hassen, M, Haubold, J, Hayat, K, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Herteliu, C, Hessami, K, Hezam, K, Hiraike, Y, Holla, R, Hosseini, M, Huynh, H, Hwang, B, Ibitoye, S, Ilic, I, Ilic, M, Iranmehr, A, Iravanpour, F, Ismail, N, Iwagami, M, Iwu, C, Jacob, L, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahrami, H, Jakovljevic, M, Jamshidi, E, Jani, C, Janodia, M, Jayapal, S, Jayaram, S, Jeganathan, J, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Vaishali, K, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kaliyadan, F, Kalroozi, F, Kamal, V, Kandel, A, Kandel, H, Kanungo, S, Karami, J, Karaye, I, Karimi, H, Kasraei, H, Kazemian, S, Kebede, S, Keikavoosi-Arani, L, Keykhaei, M, Khader, Y, Khajuria, H, Khamesipour, F, Khan, E, Khan, I, Khan, M, Khatatbeh, H, Khatatbeh, M, Khateri, S, Khayat Kashani, H, Kim, M, Kisa, A, Kisa, S, Koh, H, Kolkhir, P, Korzh, O, Kotnis, A, Koul, P, Koyanagi, A, Krishan, K, Kuddus, M, Kulkarni, V, Kumar, N, Kundu, S, Kurmi, O, La Vecchia, C, Lahariya, C, Laksono, T, Lám, J, Latief, K, Lauriola, P, Lawal, B, Thu Le, T, Bich Le, T, Lee, M, Lee, S, Lee, W, Lee, Y, Lenzi, J, Levi, M, Li, W, Ligade, V, Lim, S, Liu, G, Liu, X, Llanaj, E, Lo, C, Machado, V, Maghazachi, A, Mahmoud, M, Mai, T, Majeed, A, Sanaye, P, Makram, O, Rad, E, Malhotra, K, Malik, A, Malik, I, Mallhi, T, Malta, D, Mansournia, M, Mantovani, L, Martorell, M, Masoudi, S, Masoumi, S, Mathangasinghe, Y, Mathews, E, Mathioudakis, A, Maugeri, A, Mayeli, M, Carabeo Medina, J, Meles, G, Mendes, J, Menezes, R, Mestrovic, T, Michalek, I, Micheletti Gomide Nogueira de Sá, A, Mihretie, E, Nhat Minh, L, Mirfakhraie, R, Mirrakhimov, E, Misganaw, A, Mohamadkhani, A, Mohamed, N, Mohammadi, F, Mohammadi, S, Mohammed, S, Mohan, S, Mohseni, A, Mokdad, A, Momtazmanesh, S, Monasta, L, Moni, M, Moniruzzaman, M, Moradi, Y, Morovatdar, N, Mostafavi, E, Mousavi, P, Mukoro, G, Mulita, A, Mulu, G, Murillo-Zamora, E, Musaigwa, F, Mustafa, G, Muthu, S, Nainu, F, Nangia, V, Swamy, S, Natto, Z, Navaraj, P, Nayak, B, Nazri-Panjaki, A, Negash, H, Nematollahi, M, Nguyen, D, Hien Nguyen, H, Nguyen, H, Nguyen, P, Nguyen, V, Niazi, R, Nikolouzakis, T, Nnyanzi, L, Noreen, M, Nzoputam, C, Nzoputam, O, Oancea, B, Oh, I, Okati-Aliabad, H, Okonji, O, Okwute, P, Olagunju, A, Olatubi, M, Olufadewa, I, Ordak, M, Otstavnov, N, Owolabi, M, Mahesh, P, Padubidri, J, Pak, A, Pakzad, R, Palladino, R, Pana, A, Pantazopoulos, I, Papadopoulou, P, Pardhan, S, Parthasarathi, A, Pashaei, A, Patel, J, Pathan, A, Patil, S, Paudel, U, Pawar, S, Pedersini, P, Pensato, U, Pereira, D, Pereira, J, Pereira, M, Pereira, R, Peres, M, Perianayagam, A, Perna, S, Petcu, I, Pezeshki, P, Pham, H, Philip, A, Piradov, M, Podder, I, Podder, V, Poddighe, D, Sady Prates, E, Qattea, I, Radfar, A, Raee, P, Rafiei, A, Raggi, A, Rahim, F, Rahimi, M, Rahimifard, M, Rahimi-Movaghar, V, Rahman, M, Ur Rahman, M, Rahmani, A, Rahmani, M, Rahmani, S, Rahmanian, V, Ramasubramani, P, Rancic, N, Rao, I, Rashedi, S, Rashid, A, Ravikumar, N, Rawaf, S, Mohamed Redwan, E, Rezaei, N, Rezaeian, M, Ribeiro, D, Rodrigues, M, Buendia Rodriguez, J, Roever, L, Romero-Rodríguez, E, Saad, A, Saddik, B, Sadeghian, S, Saeed, U, Safary, A, Safdarian, M, Safi, S, Saghazadeh, A, Sagoe, D, Sharif-Askari, F, Sharif-Askari, N, Sahebkar, A, Sahoo, H, Sahraian, M, Sajid, M, Sakhamuri, S, Sakshaug, J, Saleh, M, Salehi, L, Salehi, S, Farrokhi, A, Samadzadeh, S, Samargandy, S, Samieefar, N, Samy, A, Sanadgol, N, Sanjeev, R, Sawhney, M, Saya, G, Schuermans, A, Senthilkumaran, S, Sepanlou, S, Sethi, Y, Shafie, M, Shah, H, Shahid, I, Shahid, S, Shaikh, M, Sharfaei, S, Sharma, M, Shayan, M, Shehata, H, Sheikh, A, Shetty, J, Shin, J, Shirkoohi, R, Shitaye, N, Shivakumar, K, Shivarov, V, Shobeiri, P, Siabani, S, Sibhat, M, Siddig, E, Simpson, C, Sinaei, E, Singh, H, Singh, I, Singh, J, Singh, P, Singh, S, Siraj, M, Al Mamun Sohag, A, Solanki, R, Solikhah, S, Solomon, Y, Soltani-Zangbar, M, Sun, J, Szeto, M, Tabarés-Seisdedos, R, Tabatabaei, S, Tabish, M, Taheri, E, Tahvildari, A, Talaat, I, Lukenze Tamuzi, J, Tan, K, Tat, N, Oliaee, R, Tavasol, A, Temsah, M, Thangaraju, P, Tharwat, S, Tibebu, N, Vera Ticoalu, J, Tillawi, T, Tiruye, T, Tiyuri, A, Tovani-Palone, M, Tripathi, M, Tsegay, G, Tualeka, A, Ty, S, Ubah, C, Ullah, S, Umair, M, Umakanthan, S, Upadhyay, E, Vahabi, S, Vaithinathan, A, Tahbaz, S, Valizadeh, R, Varthya, S, Vasankari, T, Venketasubramanian, N, Verras, G, Villafañe, J, Vlassov, V, Vo, D, Waheed, Y, Waris, A, Welegebrial, B, Westerman, R, Wickramasinghe, D, Wickramasinghe, N, Willekens, B, Woldegeorgis, B, Woldemariam, M, Xiao, H, Yada, D, Yahya, G, Yang, L, Yazdanpanah, F, Yon, D, Yonemoto, N, You, Y, Zahir, M, Zaidi, S, Zangiabadian, M, Zare, I, Zeineddine, M, Zemedikun, D, Zeru, N, Zhang, C, Zhao, H, Zhong, C, Zielińska, M, Zoladl, M, Zumla, A, Guo, C, Tam, L, Wu, Dongze, Jin, Yingzhao, Xing, Yuhan, Abate, Melsew Dagne, Abbasian, Mohammadreza, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abd-Allah, Foad, Abdelmasseh, Michael, Abdollahifar, Mohammad-Amin, Abdulah, Deldar Morad, Abedi, Aidin, Abedi, Vida, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Abuabara, Katrina, Abyadeh, Morteza, Addo, Isaac Yeboah, Adeniji, Kayode Nelson, Adepoju, Abiola Victor, Adesina, Miracle Ayomikun, Sakilah Adnani, Qorinah Estiningtyas, Afarideh, Mohsen, Aghamiri, Shahin, Agodi, Antonella, Agrawal, Anurag, Aguilera Arriagada, Constanza Elizabeth, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Sajjad, Ahmad, Sohail, Ahmadi, Ali, Ahmed, Ali, Ahmed, Ayman, Aithala, Janardhana P., Ajadi, Abdullateef Abiodun, Ajami, Marjan, Akbarzadeh-Khiavi, Mostafa, Alahdab, Fares, AlBataineh, Mohammad T., Alemi, Sharifullah, Saeed Al-Gheethi, Adel Ali, Ali, Liaqat, Alif, Sheikh Mohammad, Almazan, Joseph Uy, Almustanyir, Sami, Alqahtani, Jaber S., Alqasmi, Ibrahim, Khan Altaf, Ihsan Ullah, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J., Al-Worafi, Yaser Mohammed, Aly, Hany, Amani, Reza, Amu, Hubert, Amusa, Ganiyu Adeniyi, Andrei, Catalina Liliana, Ansar, Adnan, Ansariniya, Hossein, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Arefnezhad, Reza, Arulappan, Judie, Asghari-Jafarabadi, Mohammad, Ashraf, Tahira, Atata, Jamila Abdulhamid, Athari, Seyyed Shamsadin, Atlaw, Daniel, Wahbi Atout, Maha Moh'd, Aujayeb, Avinash, Awan, Asma Tahir, Ayatollahi, Haleh, Azadnajafabad, Sina, Azzam, Ahmed Y., Badawi, Alaa, Badiye, Ashish D., Bagherieh, Sara, Baig, Atif Amin, Bantie, Berihun Bantie, Barchitta, Martina, Bardhan, Mainak, Barker-Collo, Suzanne Lyn, Barone-Adesi, Francesco, Batra, Kavita, Bayileyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Belgaumi, Uzma Iqbal, Bemanalizadeh, Maryam, Bensenor, Isabela M., Beyene, Kebede A., Bhagavathula, Akshaya Srikanth, Bhardwaj, Pankaj, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bitaraf, Saeid, Bitra, Veera R., Boloor, Archith, Bora, Kaustubh, Botelho, João Silva, Buchbinder, Rachelle, Calina, Daniela, Cámera, Luis Alberto, Carvalho, Andre F., Kai Chan, Jeffrey Shi, Chattu, Vijay Kumar, Abebe, Endeshaw Chekol, Chichagi, Fatemeh, Choi, Sungchul, Chou, Tzu-Chieh, Chu, Dinh-Toi, Coberly, Kaleb, Costa, Vera Marisa, Couto, Rosa A. S., Cruz-Martins, Natália, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dascalu, Ana Maria, Dashti, Mohsen, Debela, Sisay Abebe, Dellavalle, Robert Paul, Demetriades, Andreas K., Demlash, Alemayehu Anley, Deng, Xinlei, Desai, Hardik Dineshbhai, Desai, Rupak, Rahman Dewan, Syed Masudur, Dey, Sourav, Dharmaratne, Samath Dhamminda, Diaz, Daniel, Dibas, Mahmoud, Dinis-Oliveira, Ricardo Jorge, Diress, Mengistie, Do, Thanh Chi, Doan, Duy Khanh, Dodangeh, Masoud, Dodangeh, Milad, Dongarwar, Deepa, Dube, John, Dziedzic, Arkadiusz Marian, Ed-Dra, Abdelaziz, Edinur, Hisham Atan, Eissazade, Negin, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Elemam, Noha Mousaad, Elhadi, Muhammed, Elmehrath, Ahmed O., Abdou Elmeligy, Omar Abdelsadek, Emamverdi, Mehdi, Emeto, Theophilus I., Esayas, Hawi Leul, Eshetu, Habitu Birhan, Etaee, Farshid, Fagbamigbe, Adeniyi Francis, Faghani, Shahriar, Fakhradiyev, Ildar Ravisovich, Fatehizadeh, Ali, Fathi, Mobina, Feizkhah, Alireza, Fekadu, Ginenus, Fereidouni, Mohammad, Fereshtehnejad, Seyed-Mohammad, Fernandes, João C., Ferrara, Pietro, Fetensa, Getahun, Filip, Irina, Fischer, Florian, Foroutan, Behzad, Foroutan, Masoud, Fukumoto, Takeshi, Ganesan, Balasankar, Belete Gemeda, Belete Negese, Ghamari, Seyyed-Hadi, Ghasemi, MohammadReza, Gholamalizadeh, Maryam, Gill, Tiffany K., Gillum, Richard F., Goldust, Mohamad, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Goudarzi, Houman, Guan, Shi-Yang, Guo, Yang, Gupta, Bhawna, Gupta, Veer Bala, Gupta, Vivek Kumar, Haddadi, Rasool, Hadi, Najah R., Halwani, Rabih, Haque, Shafiul, Hasan, Ikramul, Hashempour, Reza, Hassan, Amr, Hassan, Treska S., Hassanzadeh, Sara, Hassen, Mohammed Bheser, Haubold, Johannes, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Heidari-Soureshjani, Reza, Herteliu, Claudiu, Hessami, Kamran, Hezam, Kamal, Hiraike, Yuta, Holla, Ramesh, Hosseini, Mohammad-Salar, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Ilic, Irena M., Ilic, Milena D., Iranmehr, Arad, Iravanpour, Farideh, Ismail, Nahlah Elkudssiah, Iwagami, Masao, Iwu, Chidozie C. D., Jacob, Louis, Jafarinia, Morteza, Jafarzadeh, Abdollah, Jahankhani, Kasra, Jahrami, Haitham, Jakovljevic, Mihajlo, Jamshidi, Elham, Jani, Chinmay T., Janodia, Manthan Dilipkumar, Jayapal, Sathish Kumar, Jayaram, Shubha, Jeganathan, Jayakumar, Jonas, Jost B., Joseph, Abel, Joseph, Nitin, Joshua, Charity Ehimwenma, Vaishali, K., Kaambwa, Billingsley, Kabir, Ali, Kabir, Zubair, Kadashetti, Vidya, Kaliyadan, Feroze, Kalroozi, Fatemeh, Kamal, Vineet Kumar, Kandel, Amit, Kandel, Himal, Kanungo, Srikanta, Karami, Jafar, Karaye, Ibraheem M., Karimi, Hanie, Kasraei, Hengameh, Kazemian, Sina, Kebede, Sewnet Adem, Keikavoosi-Arani, Leila, Keykhaei, Mohammad, Khader, Yousef Saleh, Khajuria, Himanshu, Khamesipour, Faham, Khan, Ejaz Ahmad, Khan, Imteyaz A., Khan, Maseer, Khan, Md Jobair, Khan, Moien A. B., Khan, Muhammad Arslan, Khatatbeh, Haitham, Khatatbeh, Moawiah Mohammad, Khateri, Sorour, Khayat Kashani, Hamid Reza, Kim, Min Seo, Kisa, Adnan, Kisa, Sezer, Koh, Hyun Yong, Kolkhir, Pavel, Korzh, Oleksii, Kotnis, Ashwin Laxmikant, Koul, Parvaiz A., Koyanagi, Ai, Krishan, Kewal, Kuddus, Mohammed, Kulkarni, Vishnutheertha Vishnutheertha, Kumar, Narinder, Kundu, Satyajit, Kurmi, Om P., La Vecchia, Carlo, Lahariya, Chandrakant, Laksono, Tri, Lám, Judit, Latief, Kamaluddin, Lauriola, Paolo, Lawal, Basira Kankia, Thu Le, Thao Thi, Bich Le, Trang Thi, Lee, Munjae, Lee, Seung Won, Lee, Wei-Chen, Lee, Yo Han, Lenzi, Jacopo, Levi, Miriam, Li, Wei, Ligade, Virendra S., Lim, Stephen S., Liu, Gang, Liu, Xuefeng, Llanaj, Erand, Lo, Chun-Han, Machado, Vanessa Sintra, Maghazachi, Azzam A., Mahmoud, Mansour Adam, Mai, Tuan A., Majeed, Azeem, Sanaye, Pantea Majma, Makram, Omar Mohamed, Rad, Elaheh Malakan, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Martorell, Miquel, Masoudi, Sahar, Masoumi, Seyedeh Zahra, Mathangasinghe, Yasith, Mathews, Elezebeth, Mathioudakis, Alexander G., Maugeri, Andrea, Mayeli, Mahsa, Carabeo Medina, John Robert, Meles, Gebrekiros Gebremichael, Mendes, José João, Menezes, Ritesh G., Mestrovic, Tomislav, Michalek, Irmina Maria, Micheletti Gomide Nogueira de Sá, Ana Carolina, Mihretie, Ephrem Tesfaye, Nhat Minh, Le Huu, Mirfakhraie, Reza, Mirrakhimov, Erkin M., Misganaw, Awoke, Mohamadkhani, Ashraf, Mohamed, Nouh Saad, Mohammadi, Faezeh, Mohammadi, Soheil, Mohammed, Salahuddin, Mohammed, Shafiu, Mohan, Syam, Mohseni, Anita, Mokdad, Ali H., Momtazmanesh, Sara, Monasta, Lorenzo, Moni, Mohammad Ali, Moniruzzaman, Md, Moradi, Yousef, Morovatdar, Negar, Mostafavi, Ebrahim, Mousavi, Parsa, Mukoro, George Duke, Mulita, Admir, Mulu, Getaneh Baye, Murillo-Zamora, Efrén, Musaigwa, Fungai, Mustafa, Ghulam, Muthu, Sathish, Nainu, Firzan, Nangia, Vinay, Swamy, Sreenivas Narasimha, Natto, Zuhair S., Navaraj, Perumalsamy, Nayak, Biswa Prakash, Nazri-Panjaki, Athare, Negash, Hadush, Nematollahi, Mohammad Hadi, Nguyen, Dang H., Hien Nguyen, Hau Thi, Nguyen, Hien Quang, Nguyen, Phat Tuan, Nguyen, Van Thanh, Niazi, Robina Khan, Nikolouzakis, Taxiarchis Konstantinos, Nnyanzi, Lawrence Achilles, Noreen, Mamoona, Nzoputam, Chimezie Igwegbe, Nzoputam, Ogochukwu Janet, Oancea, Bogdan, Oh, In-Hwan, Okati-Aliabad, Hassan, Okonji, Osaretin Christabel, Okwute, Patrick Godwin, Olagunju, Andrew T., Olatubi, Matthew Idowu, Olufadewa, Isaac Iyinoluwa, Ordak, Michal, Otstavnov, Nikita, Owolabi, Mayowa O., Mahesh, P. A., Padubidri, Jagadish Rao, Pak, Anton, Pakzad, Reza, Palladino, Raffaele, Pana, Adrian, Pantazopoulos, Ioannis, Papadopoulou, Paraskevi, Pardhan, Shahina, Parthasarathi, Ashwaghosha, Pashaei, Ava, Patel, Jay, Pathan, Aslam Ramjan, Patil, Shankargouda, Paudel, Uttam, Pawar, Shrikant, Pedersini, Paolo, Pensato, Umberto, Pereira, David M., Pereira, Jeevan, Pereira, Maria Odete, Pereira, Renato B., Peres, Mario F. P., Perianayagam, Arokiasamy, Perna, Simone, Petcu, Ionela-Roxana, Pezeshki, Parmida Sadat, Pham, Hoang Tran, Philip, Anil K., Piradov, Michael A., Podder, Indrashis, Podder, Vivek, Poddighe, Dimitri, Sady Prates, Elton Junio, Qattea, Ibrahim, Radfar, Amir, Raee, Pourya, Rafiei, Alireza, Raggi, Alberto, Rahim, Fakher, Rahimi, Mehran, Rahimifard, Mahban, Rahimi-Movaghar, Vafa, Rahman, Md Obaidur, Ur Rahman, Mohammad Hifz, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Mohamed, Rahmani, Shayan, Rahmanian, Vahid, Ramasubramani, Premkumar, Rancic, Nemanja, Rao, Indu Ramachandra, Rashedi, Sina, Rashid, Ahmed Mustafa, Ravikumar, Nakul, Rawaf, Salman, Mohamed Redwan, Elrashdy Moustafa, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaeian, Mohsen, Ribeiro, Daniela, Rodrigues, Mónica, Buendia Rodriguez, Jefferson Antonio, Roever, Leonardo, Romero-Rodríguez, Esperanza, Saad, Aly M. A., Saddik, Basema, Sadeghian, Saeid, Saeed, Umar, Safary, Azam, Safdarian, Mahdi, Safi, Sher Zaman, Saghazadeh, Amene, Sagoe, Dominic, Sharif-Askari, Fatemeh Saheb, Sharif-Askari, Narjes Saheb, Sahebkar, Amirhossein, Sahoo, Harihar, Sahraian, Mohammad Ali, Sajid, Mirza Rizwan, Sakhamuri, Sateesh, Sakshaug, Joseph W., Saleh, Mohamed A., Salehi, Leili, Salehi, Sana, Farrokhi, Amir Salek, Samadzadeh, Sara, Samargandy, Saad, Samieefar, Noosha, Samy, Abdallah M., Sanadgol, Nima, Sanjeev, Rama Krishna, Sawhney, Monika, Saya, Ganesh Kumar, Schuermans, Art, Senthilkumaran, Subramanian, Sepanlou, Sadaf G., Sethi, Yashendra, Shafie, Mahan, Shah, Humaira, Shahid, Izza, Shahid, Samiah, Shaikh, Masood Ali, Sharfaei, Sadaf, Sharma, Manoj, Shayan, Maryam, Shehata, Hatem Samir, Sheikh, Aziz, Shetty, Jeevan K., Shin, Jae Il, Shirkoohi, Reza, Shitaye, Nebiyu Aniley, Shivakumar, K. M., Shivarov, Velizar, Shobeiri, Parnian, Siabani, Soraya, Sibhat, Migbar Mekonnen, Siddig, Emmanuel Edwar, Simpson, Colin R., Sinaei, Ehsan, Singh, Harpreet, Singh, Inderbir, Singh, Jasvinder A., Singh, Paramdeep, Singh, Surjit, Siraj, Md Shahjahan, Al Mamun Sohag, Abdullah, Solanki, Ranjan, Solikhah, Solikhah, Solomon, Yonatan, Soltani-Zangbar, Mohammad Sadegh, Sun, Jing, Szeto, Mindy D., Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabish, Mohammad, Taheri, Ensiyeh, Tahvildari, Azin, Talaat, Iman M., Lukenze Tamuzi, Jacques J. L., Tan, Ker-Kan, Tat, Nathan Y., Oliaee, Razieh Tavakoli, Tavasol, Arian, Temsah, Mohamad-Hani, Thangaraju, Pugazhenthan, Tharwat, Samar, Tibebu, Nigusie Selomon, Vera Ticoalu, Jansje Henny, Tillawi, Tala, Tiruye, Tenaw Yimer, Tiyuri, Amir, Tovani-Palone, Marcos Roberto, Tripathi, Manjari, Tsegay, Guesh Mebrahtom, Tualeka, Abdul Rohim, Ty, Sree Sudha, Ubah, Chukwudi S., Ullah, Saif, Ullah, Sana, Umair, Muhammad, Umakanthan, Srikanth, Upadhyay, Era, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Tahbaz, Sahel Valadan, Valizadeh, Rohollah, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Verras, Georgios-Ioannis, Villafañe, Jorge Hugo, Vlassov, Vasily, Vo, Danh Cao, Waheed, Yasir, Waris, Abdul, Welegebrial, Brhane Gebrehiwot, Westerman, Ronny, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Willekens, Barbara, Woldegeorgis, Beshada Zerfu, Woldemariam, Melat, Xiao, Hong, Yada, Dereje Y., Yahya, Galal, Yang, Lin, Yazdanpanah, Fereshteh, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Zahir, Mazyar, Zaidi, Syed Saoud, Zangiabadian, Moein, Zare, Iman, Zeineddine, Mohammad A., Zemedikun, Dawit T., Zeru, Naod Gebrekrstos, Zhang, Chen, Zhao, Hanqing, Zhong, Chenwen, Zielińska, Magdalena, Zoladl, Mohammad, Zumla, Alimuddin, Guo, Cui, and Tam, Lai-shan
Abstract: Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rh
Published: 2023

7. Physiological Comparison of Two Salt-Excluder Hybrid Grapevine Rootstocks under Salinity Reveals Different Adaptation Qualities

Author: Gajjar, Pranavkumar, Ismail, Ahmed, Islam, Tabibul, Darwish, Ahmed G., Moniruzzaman, Md, Abuslima, Eman, Dawood, Ahmed S., El-Saady, Abdelkareem M., Tsolova, Violeta, El-Kereamy, Ashraf, Nick, Peter, Sherif, Sherif M., Abazinge, Michael D., El-Sharkawy, Islam, Gajjar, Pranavkumar, Ismail, Ahmed, Islam, Tabibul, Darwish, Ahmed G., Moniruzzaman, Md, Abuslima, Eman, Dawood, Ahmed S., El-Saady, Abdelkareem M., Tsolova, Violeta, El-Kereamy, Ashraf, Nick, Peter, Sherif, Sherif M., Abazinge, Michael D., and El-Sharkawy, Islam
Abstract: Like other plant stresses, salinity is a central agricultural problem, mainly in arid or semi-arid regions. Therefore, salt-adapted plants have evolved several adaptation strategies to counteract salt-related events, such as photosynthesis inhibition, metabolic toxicity, and reactive oxygen species (ROS) formation. European grapes are usually grafted onto salt-tolerant rootstocks as a cultivation practice to alleviate salinity-dependent damage. In the current study, two grape rootstocks, 140 Ruggeri (RUG) and Millardet et de Grasset 420A (MGT), were utilized to evaluate the diversity of their salinity adaptation strategies. The results showed that RUG is able to maintain higher levels of the photosynthetic pigments (Chl-T, Chl-a, and Chl-b) under salt stress, and hence accumulates higher levels of total soluble sugars (TSS), monosaccharides, and disaccharides compared with the MGT rootstock. Moreover, it was revealed that the RUG rootstock maintains and/or increases the enzymatic activities of catalase, GPX, and SOD under salinity, giving it a more efficient ROS detoxification machinery under stress.
Published: 2023

8. Bacterial and viral etiology of acute respiratory infection among the Forcibly Displaced Myanmar Nationals (FDMNs) in fragile settings in Cox’s Bazar-a prospective case-control study

Author: Siddik, Abu Bakar, Tanvir, Nabid Anjum, Bhuyan, Golam Sarower, Alam, Md Shahariar, Islam, Zahirul, Bulbul, Md Rakibul Hassan, Moniruzzaman, Md, Halder, Charls Erik, Rahman, Tayabur, Endtz, Hubert, Ahmed, Shakeel, Qadri, Firdausi, Picot, Valentina Sanchez, Siddik, Abu Bakar, Tanvir, Nabid Anjum, Bhuyan, Golam Sarower, Alam, Md Shahariar, Islam, Zahirul, Bulbul, Md Rakibul Hassan, Moniruzzaman, Md, Halder, Charls Erik, Rahman, Tayabur, Endtz, Hubert, Ahmed, Shakeel, Qadri, Firdausi, and Picot, Valentina Sanchez
Abstract: The leading infectious cause of death in children worldwide is lower acute respiratory infection (LARI), particularly pneumonia. We enrolled a total of 538 acute respiratory infection (ARI) cases according to WHO criteria and age-sex matched 514 controls in the Forcibly Displaced Myanmar National (FDMN) refugee camps in Cox’s Bazar, Bangladesh, between June 2018 and March 2020 to investigate the role of bacteria, viruses, and their co-infection patterns and observe Streptococcus pneumoniae (S. pneumoniae) serotype distribution. According to the etiological findings, children ≤5 years of age have a higher bacterial positivity (90%) and viral positivity (34%) in nasopharyngeal samples (NPS) compared to those >5 years of age, in both ARI cases as well as for the control group. Among the bacteria, S. pneumoniae was predominant in both cases and controls (85% and 88%). Adenovirus (ADV)(34), influenza virus A and B (IFV-A, B)(32,23), and respiratory syncytial virus (RSV) (26) were detected as the highest number among the viruses tested for the ARI cases. The total number of viruses was also found higher in ≤5 years of age group. Within this group, positive correlation was observed between bacteria and viruses but negative correlation was observed between bacteria. Both single and co-infection for viruses were found higher in the case group than the control group. However, co-infection was significantly high for Streptococcus aureus (S. aureus) and Haemophilus influenzae b (H. influenza b) (p<0.05). Additionally, semi-quantitative bacterial and viral load was found higher for the ARI cases over control considering Cycle threshold (Ct)≤30. Pathogen identification from blood specimens was higher by qRT-PCR than blood culture (16% vs 5%, p<0.05). In the S. pneumoniae serotype distribution, the predominant serotypes in ARI cases were 23F, 19A, 16F, 35B, 15A, 20 and 10F, while 11A, 10A, 34, 35A and 13 serotypes were predominant in the control group. Pathogen correla
Published: 2023

9. Teleoperation enhancement for improved control of unmanned ground vehicles through video transformation and deep learning based future frame prediction

Author: Moniruzzaman, Md and Moniruzzaman, Md
Abstract: In this era of the fourth industrial revolution, the advancement of computer systems, artificial intelligence, computer vision, and automation are playing increasingly significant roles. The rapid levels of advancement in these technologies are making robotics an integral part of many aspects of human venture. More specifically, for applications such as item delivery, telesurgery, industrial production, search and rescue, mining, underwater, aerial and space exploration, and defence, robotic systems are becoming increasingly capable. Although the expectation is that such robotic systems will become increasingly autonomous, building autonomous systems that are capable of performing such complex tasks without supervision will require significant further research. Until this is achieved, robotic teleoperation will be an important component of these applications. Effective teleoperation of remote systems is, however, highly challenging with considerable opportunity for development and improvement. In response to this need, the aim of this research was to explore novel methods for the enhancement of robotic teleportation of unmanned ground robotic vehicles operating in complex and unstructured environments. Ground vehicle teleoperators face a number of challenges including limitedsituational awareness, deficiencies in the communication medium, and, latency or delay in the communication loop. Latency in particular can significantly impactteleoperator performance through overcorrection-induced oscillations, giving riseto increased task completion time, increased cognitive load, and risk of damage to robotic vehicles and the remote environments they operate in. To identify solutions to these problems, this thesis (a) explores existing teleoperation methods and enhancement techniques, (b) identifies both conventional and artificial intelligence (AI) based techniques that have the potential to enhance teleoperation through latency compensation, and (c) explores new methods an
Published: 2023

10. Advancements in Repetitive Action Counting: Joint-Based PoseRAC Model With Improved Performance

Author: Chen, Haodong, Leu, Ming C., Moniruzzaman, Md, Yin, Zhaozheng, Hajmohammadi, Solmaz, Chen, Haodong, Leu, Ming C., Moniruzzaman, Md, Yin, Zhaozheng, and Hajmohammadi, Solmaz
Abstract: Repetitive counting (RepCount) is critical in various applications, such as fitness tracking and rehabilitation. Previous methods have relied on the estimation of red-green-and-blue (RGB) frames and body pose landmarks to identify the number of action repetitions, but these methods suffer from a number of issues, including the inability to stably handle changes in camera viewpoints, over-counting, under-counting, difficulty in distinguishing between sub-actions, inaccuracy in recognizing salient poses, etc. In this paper, based on the work done by [1], we integrate joint angles with body pose landmarks to address these challenges and achieve better results than the state-of-the-art RepCount methods, with a Mean Absolute Error (MAE) of 0.211 and an Off-By-One (OBO) counting accuracy of 0.599 on the RepCount data set [2]. Comprehensive experimental results demonstrate the effectiveness and robustness of our method., Comment: 7 pages, 9 figures
Published: 2023

11. High latency unmanned ground vehicle teleoperation enhancement by presentation of estimated future through video transformation

Author: Moniruzzaman, Md, Rassau, Alexander, Chai, Douglas, Islam, Syed Mohammed Shamsul, Moniruzzaman, Md, Rassau, Alexander, Chai, Douglas, and Islam, Syed Mohammed Shamsul
Abstract: Long-distance, high latency teleoperation tasks are difficult, highly stressful for teleoperators, and prone to over-corrections, which can lead to loss of control. At higher latencies, or when teleoperating at higher vehicle speed, the situation becomes progressively worse. To explore potential solutions, this research work investigates two 2D visual feedback-based assistive interfaces (sliding-only and sliding-and-zooming windows) that apply simple but effective video transformations to enhance teleoperation. A teleoperation simulator that can replicate teleoperation scenarios affected by high and adjustable latency has been developed to explore the effectiveness of the proposed assistive interfaces. Three image comparison metrics have been used to fine-tune and optimise the proposed interfaces. An operator survey was conducted to evaluate and compare performance with and without the assistance. The survey has shown that a 900ms latency increases task completion time by up to 205% for an on-road and 147 % for an off-road driving track. Further, the overcorrection-induced oscillations increase by up to 718 % with this level of latency. The survey has shown the sliding-only video transformation reduces the task completion time by up to 25.53 %, and the sliding-and-zooming transformation reduces the task completion time by up to 21.82 %. The sliding-only interface reduces the oscillation count by up to 66.28 %, and the sliding-and-zooming interface reduces it by up to 75.58 %. The qualitative feedback from the participants also shows that both types of assistive interfaces offer better visual situational awareness, comfort, and controllability, and significantly reduce the impact of latency and intermittency on the teleoperation task.
Published: 2022

12. Mapping of Agricultural Drought in Bangladesh using Geographic Information System (GIS)

Author: Aziz, Md Abdullah, Hossain, A. B.M. Zahid, Moniruzzaman, Md, Ahmed, Rokib, Zahan, Taslima, Azim, Saiful, Qayum, Md Abdul, Al Mamun, Md Abdulllah, Kader, Md Abdul, Rahman, Niaz Md Farhat, Aziz, Md Abdullah, Hossain, A. B.M. Zahid, Moniruzzaman, Md, Ahmed, Rokib, Zahan, Taslima, Azim, Saiful, Qayum, Md Abdul, Al Mamun, Md Abdulllah, Kader, Md Abdul, and Rahman, Niaz Md Farhat
Abstract: Bangladesh is an agriculture-dependent country and very often this sector struggles a lot due to various natural hazards including drought and flood. Almost every year in kharif crop season, Bangladesh undergoes through drought which causes a lot of yield loss. So, this has become important to identify the drought-prone areas to reduce the risk of crops yield loss and for policymaking to suggest alternative drought-tolerant crops. The agricultural drought is related to soil properties because of having spatially dynamic in nature. In the present study, agricultural drought has been assessed comprising meteorological drought of kharif season and water holding capacity (WHC) in Geographic Information System (GIS) platform, as GIS is a widely used as a powerful tool to manage and model the spatial data. The metrological drought map has prepared by rainfall data with the calculation of Standardized Precipitation Index (SPI) using GIS and WHC of soil map has converted from soil texture map. Finally, the agricultural drought map has been derived by overlying metrological drought map and WHC of soil map. The study has found that the north-west and south-west region along with Barisal division of Bangladesh are more prone to agricultural drought area than the other parts. Some districts of the middle part of the country (Dhaka, Manikganj and Faridpur: 492 km2) also suffered in extreme agricultural drought during kharif season.
Published: 2022

13. Attention-Based Sensor Fusion for Human Activity Recognition Using IMU Signals

Author: Tao, Wenjin, Chen, Haodong, Moniruzzaman, Md, Leu, Ming C., Yi, Zhaozheng, Qin, Ruwen, Tao, Wenjin, Chen, Haodong, Moniruzzaman, Md, Leu, Ming C., Yi, Zhaozheng, and Qin, Ruwen
Abstract: Human Activity Recognition (HAR) using wearable devices such as smart watches embedded with Inertial Measurement Unit (IMU) sensors has various applications relevant to our daily life, such as workout tracking and health monitoring. In this paper, we propose a novel attention-based approach to human activity recognition using multiple IMU sensors worn at different body locations. Firstly, a sensor-wise feature extraction module is designed to extract the most discriminative features from individual sensors with Convolutional Neural Networks (CNNs). Secondly, an attention-based fusion mechanism is developed to learn the importance of sensors at different body locations and to generate an attentive feature representation. Finally, an inter-sensor feature extraction module is applied to learn the inter-sensor correlations, which are connected to a classifier to output the predicted classes of activities. The proposed approach is evaluated using five public datasets and it outperforms state-of-the-art methods on a wide variety of activity categories.
Published: 2021

14. A Single Case Study On The Ayurvedic Management Of Subclinical Hypothyroidism

Author: Akbar, Waquar, Moniruzzaman, Md, Mahapatra, P B Kar, Akbar, Waquar, Moniruzzaman, Md, and Mahapatra, P B Kar
Abstract: The number of cases of hypothyroidism is increasing day by day resulting in discomforts, sign and symptoms such as weight gain, dry skin, bradycardia , hair loss , irregular menstruation in females, etc. In Ayurveda we did not find any vyadhi having direct correlation with hypothyroidism , so as per acharya Charaka it may be treated as a anukta vyadhi , on the basis of prakriti, hetu, rupa and others. As per the symptoms of hypothyroidism it can be predicted that there are involvement of kapha and vata dosa, so it should be managed as a kapha vataja vyadhi. The present study deals with a female patient, aged 35 years , suffering from sub clinical hypothyroidism since last two years , with complaints such as weight gain, weakness, palpitation, hair fall , breathlessness, etc. The patient was put under ayurvedic treatment with drugs kaishore guggulu and dashamoola kwath, while maintaining pathya and apathya for three consecutive months. Monthly observation were done , after the complete duration of treatment the blood TSH level was successfully dropped from 8.5 to 4.3 milli international units / liter , with consecutive relief from aforesaid symptoms.
Published: 2021

15. Effects of fresh and saline water irrigation for maize in coastal areas of Bangladesh

Author: Sarker, K.K., Kamar, SK.S.A., Hossain, Md.A., Mainuddin, M., Bell, R., Barrett-Lennard, E.G., Gaydon, D., Glover, M., Rashid, Md.H., Khan, Md.S.I., Moniruzzaman, Md., Hossain, Md.B., Sarker, B.C., Sarker, K.K., Kamar, SK.S.A., Hossain, Md.A., Mainuddin, M., Bell, R., Barrett-Lennard, E.G., Gaydon, D., Glover, M., Rashid, Md.H., Khan, Md.S.I., Moniruzzaman, Md., Hossain, Md.B., and Sarker, B.C.
Abstract: Farmers are being encouraged to represent the conjunctive use of fresh water (FW) and saline water (SW) irrigation for the future agriculture in the coastal saline prone areas of Bangladesh where the scarcity of FW. Therefore, the effects of fresh and saline water irrigation for maize was performed on the crop performances, water use, water productivity (WP), soil salinity and scope for maize cultivation in coastal areas. The experiment was carried out at farmers’ field at two locations with six irrigation treatments and replicated thrice during 2016–2017 and 2017–2018. Results showed that the effect of FW (0.5 ≤ salinity ≤ 1.5 dS/m) at early growth stages and SW (1.5 ≤ salinity ≤ 5 dS/m) at later growth stages had insignificant difference compared to the treatment of FW irrigation. Yield slightly increased with increased number of irrigations but there was no significant differences among the treatment. WP significantly affected by irrigation frequency in both locations, decreasing greatly with increasing amount. The more changes in soil water occurred at upper layer than lower depth of soil profiles. The highest changes soil salinity (ECe) occurred at mid-February of the crop growing season compared to the beginning and later growth stages of maize in 60 cm soil profiles. The technique of fresh and saline water irrigation at different growth stages of maize in coastal regions could be an alternative irrigation scheduled and method for increasing yield and WP through establishment of maize compared to no crops at fallow lands during rabi (dry) season in the salt affected areas of Bangladesh.
Published: 2020

16. The 2000–2017 drought risk assessment of the western and southwestern basins in Iran

Author: Rousta, Iman, Olafsson, Haraldur, Moniruzzaman, Md, Ardö, Jonas, Zhang, Hao, Mushore, Terence Darlington, Shahin, Shifa, Azim, Saiful, Rousta, Iman, Olafsson, Haraldur, Moniruzzaman, Md, Ardö, Jonas, Zhang, Hao, Mushore, Terence Darlington, Shahin, Shifa, and Azim, Saiful
Published: 2020

17. Seagrass detection using deep learning

Author: Moniruzzaman, Md and Moniruzzaman, Md
Abstract: Seagrasses play an essential role in the marine ecosystem by providing foods, nutrients, and habitat to the marine lives. They work as marine bioindicators by reflecting the health condition of aquatic environments. Seagrasses also act as a significant atmospheric carbon sink that mitigates global warming and rapid climate changes. Considering the importance, it is critical to monitor seagrasses across the coastlines which includes detection, mapping, percentage cover calculation, and health estimation. Remote sensing-based aerial and spectral images, acoustic images, underwater two-dimensional and three-dimensional digital images have so far been used to monitor seagrasses. For close monitoring, different machine learning classifiers such as the support vector machine (SVM), the maximum likelihood classifier (MLC), the logistic model tree (LMT) and the multilayer perceptron (MP) have been used for seagrass classification from two-dimensional digital images. All of these approaches used handcrafted feature extraction methods, which are semi-automatic. In recent years, deep learning-based automatic object detection and image classification have achieved tremendous success, especially in the computer vision area. However, to the best of our knowledge, no attempts have been made for using deep learning for seagrass detection from underwater digital images. Possible reasons include unavailability of enough image data to train a deep neural network. In this work, we have proposed a Faster R-CNN architecture based deep learning detector that automatically detects Halophila ovalis (a common seagrass species) from underwater digital images. To train the object detector, we have collected a total of 2,699 underwater images both from real-life shorelines, and from an experimental facility. The selected seagrass (Halophila ovalis) are labelled using LabelImg software, commonly used by the research community. An expert in seagrass reviewed the extracted labels. We have used VGG
Published: 2019

18. Imaging and Classification Techniques for Seagrass Mapping and Monitoring: A Comprehensive Survey

Author: Moniruzzaman, Md, Islam, S. M. Shamsul, Lavery, Paul, Bennamoun, Mohammed, Lam, C. Peng, Moniruzzaman, Md, Islam, S. M. Shamsul, Lavery, Paul, Bennamoun, Mohammed, and Lam, C. Peng
Abstract: Monitoring underwater habitats is a vital part of observing the condition of the environment. The detection and mapping of underwater vegetation, especially seagrass has drawn the attention of the research community as early as the nineteen eighties. Initially, this monitoring relied on in situ observation by experts. Later, advances in remote-sensing technology, satellite-monitoring techniques and, digital photo- and video-based techniques opened a window to quicker, cheaper, and, potentially, more accurate seagrass-monitoring methods. So far, for seagrass detection and mapping, digital images from airborne cameras, spectral images from satellites, acoustic image data using underwater sonar technology, and digital underwater photo and video images have been used to map the seagrass meadows or monitor their condition. In this article, we have reviewed the recent approaches to seagrass detection and mapping to understand the gaps of the present approaches and determine further research scope to monitor the ocean health more easily. We have identified four classes of approach to seagrass mapping and assessment: still image-, video data-, acoustic image-, and spectral image data-based techniques. We have critically analysed the surveyed approaches and found the research gaps including the need for quick, cheap and effective imaging techniques robust to depth, turbidity, location and weather conditions, fully automated seagrass detectors that can work in real-time, accurate techniques for estimating the seagrass density, and the availability of high computation facilities for processing large scale data. For addressing these gaps, future research should focus on developing cheaper image and video data collection techniques, deep learning based automatic annotation and classification, and real-time percentage-cover calculation., Comment: 36 pages, 14 figures, 8tables
Published: 2019

19. Continuous detection of entry of cell-penetrating peptide transportan 10 into single vesicles

Author: Moghal Md.Mizanur Rahman, Islam Md. Zahidul, Sharmin Sabrina, Levadnyy Victor, Moniruzzaman Md., Yamazaki Masahito, Moghal Md.Mizanur Rahman, Islam Md. Zahidul, Sharmin Sabrina, Levadnyy Victor, Moniruzzaman Md., and Yamazaki Masahito
Published: 2018

20. Adherence to recommendations on lipid-based nutrient supplement and iron and folic acid tablet consumption among pregnant and lactating women participating in a community health programme in northwest Bangladesh.

Author: Harding, Kassandra L, Harding, Kassandra L, Matias, Susana L, Mridha, Malay K, Moniruzzaman, Md, Vosti, Stephen A, Hussain, Sohrab, Dewey, Kathryn G, Stewart, Christine P, Harding, Kassandra L, Harding, Kassandra L, Matias, Susana L, Mridha, Malay K, Moniruzzaman, Md, Vosti, Stephen A, Hussain, Sohrab, Dewey, Kathryn G, and Stewart, Christine P
Abstract: Limited knowledge exists on sustained adherence to small-quantity lipid-based nutrient supplements for pregnant and lactating women (LNS-PL) and how this compares with that of other prenatal supplements. To address these gaps, a random subsample of women (n = 360) during pregnancy, early (6- to 12-week post-partum) and late (12- to 24-week post-partum) lactation, from an ongoing effectiveness trial in Bangladesh, was selected for in-home interviews about LNS-PL or iron/folic acid (IFA) use and preferences. Prevalence of high adherence (≥70% of the recommendation) based on self-reported supplement consumption was 67%, 68% and 81% among LNS-PL recipients during pregnancy, early and late lactation, and was 87% and 71% among IFA recipients during pregnancy and early lactation, respectively (P = 0.044). Programmatic factors (e.g. distribution and visits by programme staff) were consistently statistically significantly associated with reported high adherence. Among LNS-PL recipients, high overall supplement acceptability score [odds ratio (OR): 8.62; 95% confidence interval (CI) 3.53, 20.83] and use of reminder techniques (OR: 4.41; 95%CI 1.65, 11.76) were positively associated, and reported vomiting at enrollment was negatively associated (OR: 0.34; 95%CI 0.14, 0.80), with reported high adherence. Selected women (n = 16) and key informants (n = 18) participated in in-depth interviews about perceptions and acceptability of LNS-PL. Women perceived benefits of taking LNS-PL, but some faced barriers to consumption including aversion to odour and taste during pregnancy, forgetfulness and disruptions in supply. To achieve high adherence, results from this study suggest that maternal supplementation programmes should focus on programmatic barriers and consider incorporating reminder techniques. Organoleptic acceptability of LNS-PL, particularly during pregnancy, may also need to be addressed.
Published: 2017

21. Automatic ear detection using deep learning

Author: Moniruzzaman, Md, Islam, Syed M. S., Moniruzzaman, Md, and Islam, Syed M. S.
Abstract: Ear based biometric identification can be the solution for instance such as surveillance where other biometric traits are simply very hard to access. Although many semi-automatic approaches have been made to detect ear and use it for human recognition purpose, most of them are based on feature extraction or shallow machine learning approaches. Very few approaches those used deep neural network architectures are either having less hidden layers, or a combination of deep neural network and feature extraction classifiers or already trained complex deep convolutional network. In this research approach, a deep but simple raw convolutional neural network have been used to detect ear from an ear and non-ear environment which is the initial part of ear based biometric implication. Data-Augmentation have also used and a comparative analysis have been done for original data set and Augmented dataset. Using this deep but from scratch architecture trained by 792 original images we achieved promising output which show larger data could achieve higher accuracy.
Published: 2017

22. Deep learning on underwater marine object detection: A survey

Author: Moniruzzaman, Md, Islam, Syed M. S., Bennamoun, Mohammed, Lavery, Paul, Moniruzzaman, Md, Islam, Syed M. S., Bennamoun, Mohammed, and Lavery, Paul
Abstract: Deep learning, also known as deep machine learning or deep structured learning based techniques, have recently achieved tremendous success in digital image processing for object detection and classification. As a result, they are rapidly gaining popularity and attention from the computer vision research community. There has been a massive increase in the collection of digital imagery for the monitoring of underwater ecosystems, including seagrass meadows. This growth in image data has driven the need for automatic detection and classification using deep neural network based classifiers. This paper systematically describes the use of deep learning for underwater imagery analysis within the recent past. The analysis approaches are categorized according to the object of detection, and the features and deep learning architectures used are highlighted. It is concluded that there is a great scope for automation in the analysis of digital seabed imagery using deep neural networks, especially for the detection and monitoring of seagrass.
Published: 2017

23. Low-pH-Induced Lamellar to Bicontinuous Primitive Cubic Phase Transition in Dioleoylphosphatidylserine/Monoolein Membranes

Author: Oka Toshihiko, Hasan Moynul, Islam Md. Zahidul, Moniruzzaman Md., Yamazaki Masahito, Oka Toshihiko, Hasan Moynul, Islam Md. Zahidul, Moniruzzaman Md., and Yamazaki Masahito
Abstract: publisher
Published: 2017

24. Energy security in Bangladesh perspective—an assessment and implication

Author: Islam, Md Aminul, Chan, Eng Seng, Yap, Taufiq Yun Hin, Mondal, Md. Alam Hossain, Moniruzzaman, Md., Mridha, Moniruzzaman, Islam, Md Aminul, Chan, Eng Seng, Yap, Taufiq Yun Hin, Mondal, Md. Alam Hossain, Moniruzzaman, Md., and Mridha, Moniruzzaman
Abstract: Energy is a key indicator of the nation's overall economic as well as social development. Looking at the present energy demand scenario in Bangladesh, electricity demand has significantly increased over the past years. Most of the Bangladesh's power plants are heavily dependent on expensive imported fossil fuel energy resources. Thus, the power failure has become an acute problem for the country and adversely affects the socio-economic development of the country. Consequently, the shortage and constraint in availability of fossil fuels appeal to boost up the renewable energy sector in Bangladesh in order to bring down the gap between demand and supply. Hence, decisive steps to reform the power sector with a mandate to oversee these sectors urgently need to overcome current energy crisis facing in the country. In this paper, efforts have been made to summarize the availability, current status, strategies, perspectives, promotion policies, major achievements and future potential of energy options in Bangladesh.
Published: 2014

25. Advances in solid-catalytic and non-catalytic technologies for biodiesel production

Author: Islam, Md Aminul, Yap, Taufiq Yun Hin, Chan, Eng Seng, Moniruzzaman, Md., Islam, Md. Saiful, Nabi, Md. Nurun, Islam, Md Aminul, Yap, Taufiq Yun Hin, Chan, Eng Seng, Moniruzzaman, Md., Islam, Md. Saiful, and Nabi, Md. Nurun
Abstract: The insecure supply of fossil fuel coerces the scientific society to keep a vision to boost investments in the renewable energy sector. Among the many renewable fuels currently available around the world, biodiesel offers an immediate impact in our energy. In fact, a huge interest in related research indicates a promising future for the biodiesel technology. Heterogeneous catalyzed production of biodiesel has emerged as a preferred route as it is environmentally benign needs no water washing and product separation is much easier. The number of well-defined catalyst complexes that are able to catalyze transesterification reactions efficiently has been significantly expanded in recent years. The activity of catalysts, specifically in application to solid acid/base catalyst in transesterification reaction depends on their structure, strength of basicity/acidity, surface area as well as the stability of catalyst. There are various process intensification technologies based on the use of alternate energy sources such as ultrasound and microwave. The latest advances in research and development related to biodiesel production is represented by non-catalytic supercritical method and focussed exclusively on these processes as forthcoming transesterification processes. The latest developments in this field featuring highly active catalyst complexes are outlined in this review. The knowledge of more extensive research on advances in biofuels will allow a deeper insight into the mechanism of these technologies toward meeting the critical energy challenges in future.
Published: 2014

26. Compliance potential mapping: a tool to assess potential contributions of walking towards physical activity guidelines

Author: Moniruzzaman, Md, Páez, Antonio, Morency, Catherine, Moniruzzaman, Md, Páez, Antonio, and Morency, Catherine
Abstract: Background: Walking for transport is increasingly considered an important component for meeting physical activity guidelines. This is true for individuals of all ages, and particularly important for seniors, for whom other physical activities may not be recommended. In order to evaluate the potential contributions of walking to physical activity, in this paper the concept of Compliance Potential Mapping is introduced. The concept is illustrated using seniors as a case study.Methods: Based on estimates of walking trip distance and frequency, estimates of expected total daily walking distance are obtained. These estimates are converted to weekly walking minutes, which are in turn compared to recommended physical activity guidelines for seniors. Once estimates of travel behavior are available, the approach is straightforward and based on relatively simple map algebra operations.Results: Compliance Potential Mapping as a tool to assess the potential contributions of walking towards physical activity is demonstrated using data from Montreal's 2008 travel survey. The results indicate that the central parts of Montreal Island display higher potential for compliance with physical activity guidelines, but with variations according to age, income, occupation, possession of driver's license and vehicle, and neighborhood and accessibility parameters.Conclusions: Compliance Potential Maps offer valuable information for public health and transportation planning and policy analysis.
Published: 2014

27. Development of a procedure for spherical alginate–boehmite particle preparation

Author: Islam, Md Aminul, Yap, Taufiq Yun Hin, Ravindra, Pogaku, Moniruzzaman, Md., Chan, Eng Seng, Islam, Md Aminul, Yap, Taufiq Yun Hin, Ravindra, Pogaku, Moniruzzaman, Md., and Chan, Eng Seng
Abstract: Herein we describe a versatile new strategy for producing spherical solid particles with 2 mm in size using integrated gelling process. The method involves the formation of spherical droplets by using a peristatic pump device and shaping the droplets in a liquid calcium chloride solution. The shape and size of these calcium alginate macroparticles depend strongly on the calcium solution concentration. The shaping mechanism of the macroparticles and the impact of the experimental conditions on particle shape and size are investigated. This method has the following features: (1) A new level of control over the shapes of the particles is offered. (2) The procedure can be scaled up to produce large numbers of particles. (3) The final porous structure of the developed particle can be designed for a specific application (adsorption, catalysis).
Published: 2013

28. Developing a web-based accessibility calculator prototype for the Greater Montreal Area

Author: Páez, Antonio, Moniruzzaman, Md, Bourbonnais, Pierre-Léo, Morency, Catherine, Páez, Antonio, Moniruzzaman, Md, Bourbonnais, Pierre-Léo, and Morency, Catherine
Abstract: A mixture of modes is considered a key element towards sustainable transportation. New technologies that provide information about various modes and environments can help to inform choices regarding travel and accessibility. In this paper we describe the development of a web-based accessibility calculator prototype for the Greater Montreal Area in Canada. The core of this tool is a statistical model of trip length developed using the spatial expansion method. The model is used to obtain estimates of trip length for a desired profile, based on attributes such as age, gender, family structure, and mode of travel, as well as geographical location. These estimates are used to calculate a cumulative opportunities accessibility measure to different types of essential destinations. Travel behavior information is drawn from Montreal's 2008 Household Travel Surveys. Geocoded information about trip origins and destinations is used to calculate trip length. A broad array of covariates related to individual and household attributes, and urban form are used. A geocoded business point database is used for the calculation of cumulative opportunities. To simplify the use of the accessibility calculator, the model is implemented in a user-friendly way using Google Maps API v3 and a convenient interface. Different possible uses of the accessibility calculator are illustrated in the paper. The accessibility calculator can be used by members of the public or planners/policy makers to measure the level of accessibility for a specific address and personal profile by various modes of transportation.
Published: 2013

29. ACCESSIBILITY AND BUILT ENVIRONMENT EFFECTS ON TRANSIT USE

Author: Moniruzzaman, Md, Paez, Antonio, Darren Scott, Pavlos Kanaroglou, Geography, Moniruzzaman, Md, Paez, Antonio, Darren Scott, Pavlos Kanaroglou, and Geography
Abstract: A critical factor in transit mode share analysis is the level of accessibility to transit services. The objective of this study is to investigate the relationships between accessibility and the built environment, and the use of transit. To do so, the proportion of transit users is modeled as a function of socio-economic characteristics, transit level of service, and built environment characteristics. While accessibility to transit has been the object of previous research, accessibility by transit is a factor that has received only limited attention in prior transit modal share research. The case study is the city of Hamilton, and the geographic unit of analysis is the Dissemination Area. A logistic model for proportions with a spatial filter (for spatial autocorrelation) and an over-dispersion parameter is found to provide the best fit and statistical properties. The results of analysis at the meso-scale show that accessibility by transit contributes positively to usage of transit. The possibility that factors at the micro-scale may also influence use of transit, suggests the development of a methodology, based on the use of spatial filtering, to systematically select walkability audit sites. The proposed methodology is demonstrated by means of a case study of neighborhoods in Hamilton. Statistical analysis of walkability audit information shows that the proposed selection strategy can be used to better target limited resources for field-based work, and produce valuable insights into the micro-level factors that may affect transit use., Master of Arts (MA)
Published: 2011

30. Faster R-CNN based deep learning for seagrass detection from underwater digital images

Author: Moniruzzaman, Md, Islam, Syed, Lavery, Paul, Bennamoun, Mohammed, Moniruzzaman, Md, Islam, Syed, Lavery, Paul, and Bennamoun, Mohammed
Abstract: Moniruzzaman, M., Islam, S., Lavery, P., & Bennamoun, M. (2019). Faster R-CNN based deep learning for seagrass detection from underwater digital images. In Proceedings of The International Conference on Digital Image Computing: Techniques and Applications, DICTA 2019 (S1.6). Perth, Australia. Available here

31. Evaluation of different features and machine learning classifiers for classification of rays from underwater digital images

Author: Moniruzzaman, MD, Islam, S., Moniruzzaman, MD, and Islam, S.
Abstract: Moniruzzaman, M. D., & Islam, S. S. (2018, December). Evaluation of Different Features and Classifiers for Classification of Rays from Underwater Digital Images. In 2018 International Conference on Machine Learning and Data Engineering (iCMLDE) (pp. 83-90). IEEE. Available here

32. Automatic seagrass detection: A survey

Author: Islam, Syed M. S., Raza, Syed K., Moniruzzaman, Md, Janjua, Naeem, Lavery, Paul, Al-Jumaily, Adel, Islam, Syed M. S., Raza, Syed K., Moniruzzaman, Md, Janjua, Naeem, Lavery, Paul, and Al-Jumaily, Adel
Abstract: Islam, S.M.S., Raza, S.K., Moniruzzamn, M., Janjua, N., Lavery, P., & Al-Jumaily. (2017). Automatic seagrass detection: A survey. In Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA). Ras Al Khaimah, United Arab Emirates. here

33. Deep learning on underwater marine object detection: A survey

Author: Moniruzzaman, Md, Islam, Syed M. S., Bennamoun, Mohammed, Lavery, Paul, Moniruzzaman, Md, Islam, Syed M. S., Bennamoun, Mohammed, and Lavery, Paul
Abstract: Moniruzzaman M., Islam S.M.S., Bennamoun M., Lavery P. (2017) Deep Learning on Underwater Marine Object Detection: A Survey. In: Blanc-Talon J., Penne R., Philips W., Popescu D., Scheunders P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2017. Lecture Notes in Computer Science, vol 10617. Springer, Cham Available here

34. Automatic ear detection using deep learning

Author: Moniruzzaman, Md, Islam, Syed M. S., Moniruzzaman, Md, and Islam, Syed M. S.
Abstract: Moniruzzaman, M, & Islam, S.M.S. (2017). Automatic ear detection using deep learning. In the proceedings of the International Conference on Machine Learning and Data Engineering (iCMLDE2017). (pp. 108 - 114). Sydney, Australia. Available here

35. Nutritive Value of BJRI Mesta-2 (Hibiscus sabdariﬀa L.) Leaves

Author: Tareq, Md. Zablul, Mollah, Md. Abul Fazal, Sarker, Md. Saiful Alam, Bashar, Kazi Khayrul, Sarker, Md. Delwar Hossain, Moniruzzaman, Md., Islam, Syed Nazrul, Rafiq, Md. Zahid Al, Sadat, Md. Abu, Tareq, Md. Zablul, Mollah, Md. Abul Fazal, Sarker, Md. Saiful Alam, Bashar, Kazi Khayrul, Sarker, Md. Delwar Hossain, Moniruzzaman, Md., Islam, Syed Nazrul, Rafiq, Md. Zahid Al, and Sadat, Md. Abu
Abstract: The genus Hibiscus has more than 300 globally distributed species. This plant is well known for its bast fiber biogenesis, while its nutritional and medicinal values are largely ignored. Consequently, the nutritional properties of the Roselle variety, BJRI mesta-2, are unknown. Therefore, this study was carried out to analyze the nutritional composition of our selected Roselle tissues to support the nutritional requirements for humans in early summer in Bangladesh. Leaves were found to be a good source of calcium (2.7%), magnesium (1.6%), ash (7.34%), vitamin A (165.9%), and vitamin C (94.88%), whereas calyx was the potential source of potassium (1.9%), iron (422%), manganese (126%), and moisture (87.45%). Roselle seeds also have edible oil-producing capabilities, along with their nutritional properties. Our results indicate that BJRI mesta-2 can be an additional source of leafy vegetables, along with its herbal tea and edible oil contents.

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35 results on '"Moniruzzaman, Md."'

1. Rural women, energy poverty and energy justice in the East Central region of Bangladesh

2. Transcriptome Profiling of a Salt Excluder Hybrid Grapevine Rootstock Ruggeri throughout Salinity.

3. Seedlessness Trait and Genome Editing—A Review

4. Continuous detection of entry of cell-penetrating peptide transportan 10 into single vesicles

5. Structure-aware image translation-based long future prediction for enhancement of ground robotic vehicle teleoperation

6. Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

7. Physiological Comparison of Two Salt-Excluder Hybrid Grapevine Rootstocks under Salinity Reveals Different Adaptation Qualities

8. Bacterial and viral etiology of acute respiratory infection among the Forcibly Displaced Myanmar Nationals (FDMNs) in fragile settings in Cox’s Bazar-a prospective case-control study

9. Teleoperation enhancement for improved control of unmanned ground vehicles through video transformation and deep learning based future frame prediction

10. Advancements in Repetitive Action Counting: Joint-Based PoseRAC Model With Improved Performance

11. High latency unmanned ground vehicle teleoperation enhancement by presentation of estimated future through video transformation

12. Mapping of Agricultural Drought in Bangladesh using Geographic Information System (GIS)

13. Attention-Based Sensor Fusion for Human Activity Recognition Using IMU Signals

14. A Single Case Study On The Ayurvedic Management Of Subclinical Hypothyroidism

15. Effects of fresh and saline water irrigation for maize in coastal areas of Bangladesh

16. The 2000–2017 drought risk assessment of the western and southwestern basins in Iran

17. Seagrass detection using deep learning

18. Imaging and Classification Techniques for Seagrass Mapping and Monitoring: A Comprehensive Survey

19. Continuous detection of entry of cell-penetrating peptide transportan 10 into single vesicles

20. Adherence to recommendations on lipid-based nutrient supplement and iron and folic acid tablet consumption among pregnant and lactating women participating in a community health programme in northwest Bangladesh.

21. Automatic ear detection using deep learning

22. Deep learning on underwater marine object detection: A survey

23. Low-pH-Induced Lamellar to Bicontinuous Primitive Cubic Phase Transition in Dioleoylphosphatidylserine/Monoolein Membranes

24. Energy security in Bangladesh perspective—an assessment and implication

25. Advances in solid-catalytic and non-catalytic technologies for biodiesel production

26. Compliance potential mapping: a tool to assess potential contributions of walking towards physical activity guidelines

27. Development of a procedure for spherical alginate–boehmite particle preparation

28. Developing a web-based accessibility calculator prototype for the Greater Montreal Area

29. ACCESSIBILITY AND BUILT ENVIRONMENT EFFECTS ON TRANSIT USE

30. Faster R-CNN based deep learning for seagrass detection from underwater digital images

31. Evaluation of different features and machine learning classifiers for classification of rays from underwater digital images

32. Automatic seagrass detection: A survey

33. Deep learning on underwater marine object detection: A survey

34. Automatic ear detection using deep learning

35. Nutritive Value of BJRI Mesta-2 (Hibiscus sabdariﬀa L.) Leaves

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