Author: "Munzir" / Publication Year Range: Last 3 years - Searchworks@Jio Institute Digital Library Search Results

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387 results on '"Munzir"'

1. Village Community Economic Empowerment in Pidie Regency: Challenges and Opportunities in Utilizing Information Technology and Enhancing Participation

Author: Munzir AG, Endang Larasati, Hardi Warsono, and Kismartini Kismartini
Subjects: economic empowerment, information, and participation of village communities, Political institutions and public administration (General), JF20-2112
Abstract: Economic empowerment of rural communities is a global issue which has once again become an important program implemented in Indonesia, especially in the village fund program. There are many obstacles faced by villages, including villages in Pidie Regency, Aceh Province, in its implementation. This research explores the factors that influence the supporting and inhibiting factors for the economic empowerment of village communities in Pidie Regency. This research uses a qualitative method with a descriptive approach, which aims to understand the phenomena experienced by research subjects, such as behavior, perceptions, motivations, actions, completely and explicitly, using a natural approach in a natural context. The research results show that the supporting factors for information access are the use of information and communication technology and freedom of information. On the other hand, the inhibiting factor is that information from the community and the information media available in the village still need to be increased. Supporting factors for participation are the opportunities to participate provided by the government. Meanwhile, the inhibiting factors are the low ability and desire or willingness to participate in society as well as the need for more awareness from village communities regarding village community economic empowerment activities. The limitation of this research is that it only uses two factors to look at the factors that influence the economic development of village communities, so it is hoped that there will be other research that uses several other influencing factors. The village government in Pidie Regency is expected to pay attention to these influencing factors in carrying out economic empowerment of village communities.
Published: 2024
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2. Sustainability of Sharia Effects: Evidence from the Markets of Indonesia and Malaysia

Author: Adi Gunanto, Siti Aisyah, Mohammad Ridwan, Sofyan Syamsuddin, Munzir, and Sunarmi
Subjects: profitability, leverage, carbon emission disclosure, Islam, BP1-253
Abstract: This study is designed to assess the empirical impact of increased profitability, leverage, and carbon emission disclosure on the scale of sustainability reporting. A quantitative method was chosen as the primary approach, relying on secondary data as a source of information. Observations were conducted on manufacturing entities listed in the Sharia Securities List in Indonesia and Malaysia during the period from 2021 to 2023, using purposive sampling techniques resulting in a sample of 105 companies. Descriptive and verificative statistical methods were employed for data analysis, including panel data regression using fixed effects models. Eviews 12 software was adopted as the analytical tool. The empirical findings of this research indicate that increased profitability and carbon emission disclosure significantly contribute to the expansion of sustainability reporting disclosure. On the other hand, increased leverage does not have a significant negative impact on the scale of sustainability reporting disclosure.
Published: 2024
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3. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author: Jannik Boos, Caspar I. van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V.C. Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J. Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M. Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L. Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U. Ludwig, Valeria Rimoldi, Elvezia M. Paraboschi, Alessandra Bandera, Flora Peyvandi, Giacomo Grasselli, Francesco Blasi, Francesco Malvestiti, Serena Pelusi, Cristiana Bianco, Lorenzo Miano, Angela Lombardi, Pietro Invernizzi, Alessio Gerussi, Giuseppe Citerio, Andrea Biondi, Maria Grazia Valsecchi, Marina Elena Cazzaniga, Giuseppe Foti, Ilaria Beretta, Mariella D'Angiò, Laura Rachele Bettini, Xavier Farré, Susana Iraola-Guzmán, Manolis Kogevinas, Gemma Castaño-Vinyals, Koldo Garcia-Etxebarria, Beatriz Nafria, Mauro D'Amato, Adriana Palom, Colin Begg, Sara Clohisey, Charles Hinds, Peter Horby, Julian Knight, Lowell Ling, David Maslove, Danny McAuley, Johnny Millar, Hugh Montgomery, Alistair Nichol, Peter J.M. Openshaw, Alexandre C. Pereira, Chris P. Ponting, Kathy Rowan, Malcolm G. Semple, Manu Shankar-Hari, Charlotte Summers, Timothy Walsh, Latha Aravindan, Ruth Armstrong, Heather Biggs, Ceilia Boz, Adam Brown, Richard Clark, Audrey Coutts, Judy Coyle, Louise Cullum, Sukamal Das, Nicky Day, Lorna Donnelly, Esther Duncan, Angie Fawkes, Paul Fineran, Max Head Fourman, Anita Furlong, James Furniss, Bernadette Gallagher, Tammy Gilchrist, Ailsa Golightly, Fiona Griffiths, Katarzyna Hafezi, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Louise Macgillivray, Alan Maclean, Hanning Mal, Sarah McCafferty, Ellie Mcmaster, Jen Meikle, Shona C. Moore, Kirstie Morrice, Lee Murphy, Sheena Murphy, Mybaya Hellen, Wilna Oosthuyzen, Chenqing Zheng, Jiantao Chen, Nick Parkinson, Trevor Paterson, Katherine Schon, Andrew Stenhouse, Mihaela Das, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Lance Turtle, Tony Wackett, Mairi Ward, Jane Weaver, Nicola Wrobel, Marie Zechner, Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Christopher Whitton, Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak, Olivier Zongo, Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett, Evie Headlam, Nageswar Bandla, Minnie Gellamucho, Michelle Davies, Christopher Thompson, Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Kumar Rohit, Frater Alasdair, Malik Saleem, Carter David, Jenkins Samuel, Zoe Lamond, Wall Alanna, Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A.C. Waite, Victoria Waugh, Ingeborg D. Welters, Karen Williams, Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O'Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith, Abigail Knighton, David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias, Maie Templeton, Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei, Angela Andrew, Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie, Jean Wilson, David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Denise O'Connor, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera, Jonathan Fox, Gillian Andrew, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton, Sohphie Birch, Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose, Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams, Sophie Arnold, Petra Polgarova, Katerina Stroud, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney, Kay Elston, Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong, Aparna George, Laura Ortiz-Ruiz de Gordoa, Emily Peasgood, Claire Phillips, Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson, James Scriven, Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun, Kamal Patel, Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt, Ahmed Zaki, Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury, Clare Smedley, Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves, Rachel Bolton, Miriam Davey, David Golden, Rebecca Seaman, Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, Owen Richards, Yusuf Cheema, Hollie Brooke, Sarah Buckley, Jose Cebrian Suarez, Ruth Charlesworth, Karen Hansson, John Norris, Alice Poole, Alastair Rose, Rajdeep Sandhu, Brendan Sloan, Elizabeth Smithson, Muthu Thirumaran, Veronica Wagstaff, Alexandra Metcalfe, Mark Brunton, Jess Caterson, Holly Coles, Matthew Frise, Sabi Gurung Rai, Nicola Jacques, Liza Keating, Emma Tilney, Shauna Bartley, Parminder Bhuie, Sian Gibson, Amanda Lyle, Fiona McNeela, Jayachandran Radhakrishnan, Alistair Hughes, Bryan Yates, Jessica Reynolds, Helen Campbell, Maria Thompsom, Steve Dodds, Stacey Duffy, Sandra Greer, Karen Shuker, Ascanio Tridente, Reena Khade, Ashok Sundar, George Tsinaslanidis, Isobel Birkinshaw, Joseph Carter, Kate Howard, Joanne Ingham, Rosie Joy, Harriet Pearson, Samantha Roche, Zoe Scott, Hollie Bancroft, Mary Bellamy, Margaret Carmody, Jacqueline Daglish, Faye Moore, Joanne Rhodes, Mirriam Sangombe, Salma Kadiri, Maria Croft, Ian White, Victoria Frost, Maia Aquino, Rajeev Jha, Vinodh Krishnamurthy, Lai Lim, Li Lim, Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech, Sallyanne Trotman, Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman, Clare Whyte, Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm, Jordi Margalef, Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts, Karen Salmon, Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton, Alex McCurdy, Cecilia Ahmed, Balvinder Baines, Sarah Clamp, Julie Colley, Risna Haq, Anne Hayes, Jonathan Hulme, Samia Hussain, Sibet Joseph, Rita Kumar, Zahira Maqsood, Manjit Purewal, Leonie Benham, Zena Bradshaw, Joanna Brown, Melanie Caswell, Jason Cupitt, Sarah Melling, Stephen Preston, Nicola Slawson, Emma Stoddard, Scott Warden, Bethan Deacon, Ceri Lynch, Carla Pothecary, Lisa Roche, Gwenllian Sera Howe, Jayaprakash Singh, Keri Turner, Hannah Ellis, Natalie Stroud, Jodie Hunt, Joy Dearden, Emma Dobson, Andy Drummond, Michelle Mulcahy, Sheila Munt, Grainne O'Connor, Jennifer Philbin, Chloe Rishton, Redmond Tully, Sarah Winnard, Susanne Cathcart, Katharine Duffy, Alex Puxty, Kathryn Puxty, Lynne Turner, Jane Ireland, Gary Semple, Kate Long, Simon Whiteley, Elizabeth Wilby, Bethan Ogg, Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell, Ellen Brown, Julie Melville, Jay Naisbitt, Rosane Joseph, Maria Lazo, Olivia Walton, Alan Neal, Peter Alexander, Schvearn Allen, Joanne Bradley-Potts, Craig Brantwood, Jasmine Egan, Timothy Felton, Grace Padden, Luke Ward, Stuart Moss, Susannah Glasgow, Lynn Abel, Michael Brett, Brian Digby, Lisa Gemmell, James Hornsby, Patrick MacGoey, Pauline O'Neil, Richard Price, Natalie Rodden, Kevin Rooney, Radha Sundaram, Nicola Thomson, Bridget Hopkins, Laura Thrasyvoulou, Heather Willis, Martyn Clark, Martina Coulding, Edward Jude, Jacqueline McCormick, Oliver Mercer, Darsh Potla, Hafiz Rehman, Heather Savill, Victoria Turner, Charlotte Downes, Kathleen Holding, Katie Riches, Mary Hilton, Mel Hayman, Deepak Subramanian, Priya Daniel, Oluronke Adanini, Nikhil Bhatia, Maines Msiska, Rebecca Collins, Ian Clement, Bijal Patel, A. Gulati, Carole Hays, K. Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett, Philip Robinson, Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams, Yasmin Death, Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari, Brice Djeugam, Gillian Bell, Katy English, Amro Katary, Louise Wilcox, Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T-Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper, Joanne Rothwell, Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper, Adriana Botello, Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe, Kayleigh Spencer, Craig Brandwood, Lara Smith, Katie Birchall, Laurel Kolakaluri, Deborah Baines, Anila Sukumaran, Elena Apetri, Cathrine Basikolo, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Vicky Thomas, Danielle Walker, Angiy Michael, Matthew Collis, Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston, James Rand, Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim, Gordan McCreath, Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood, Michael Bentley, Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster, Georgia Efford, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell, Katie Stammers, Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson, Helen Wild, Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson, Jordan Jarmain, Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding, Peter Harding, Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson, Elizabeth Stones, Llucia Carbral-Ortega, Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes, Deborah Smyth, Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn, Kizzy Baines, Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke, Julie Zamikula, Bally Purewal, Vanessa Rivers, Stephanie Bell, Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith, Deanna Stephens, Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren, Sara-Beth Sutherland, Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson, Caroline Wrey Brown, Amy Collins, Waqas Khaliq, Estefania Treus Gude, Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A.L. Jones, Tara McHugh, Hamza Meghari, Lauran O'Neill, Mark J. Peters, Samiran Ray, Ana Luisa Tomas, Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt, Danielle Thornton, Jade Cole, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas, Angharad Williams, Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright, Maria Alvarez Corral, Reni Jacob, Cathy Jones, Craig Denmade, Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson, Amanda Whileman, Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton, Marius Vaida, Deborah Butcher, Susie O'Sullivan, Nicola Butterworth-Cowin, Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. Mills, Ajay Raithatha, Matthew Wiles, Jayne Willson, Helen Newell, Alison Lye, Lorenza Nwafor, Claire Jarman, Sarah Rowland-Jones, David Foote, Joby Cole, Roger Thompson, James Watson, Lisa Hesseldon, Irene Macharia, Luke Chetam, Jacqui Smith, Amber Ford, Samantha Anderson, Kathryn Birchall, Kay Housley, Sara Walker, Leanne Milner, Helena Hanratty, Helen Trower, Patrick Phillips, Simon Oxspring, Ben Donne, Catherine Jardine, Dewi Williams, Alasdair Hay, Rebecca Flanagan, Gareth Hughes, Scott Latham, Emma McKenna, Jennifer Anderson, Robert Hull, Kat Rhead, Carina Cruz, Natalie Pattison, Rob Charnock, Denise McFarland, Denise Cosgrove, Ashar Ahmed, Anna Morris, Srinivas Jakkula, Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq, Sarah Hanley, Meg Hibbert, Dariusz Tetla, Chrsitopher Woodford, Latha Durga, Gareth Kennard-Holden, Debbie Branney, Jordan Frankham, Sally Pitts, Nigel White, Shondipon Laha, Mark Verlander, Alexandra Williams, Abdelhakim Altabaibeh, Ana Alvaro, Kayleigh Gilbert, Louise Ma, Loreta Mostoles, Chetan Parmar, Kathryn Simpson, Champa Jetha, Lauren Booker, Anezka Pratley, Colene Adams, Anita Agasou, Tracie Arden, Amy Bowes, Pauline Boyle, Mandy Beekes, Heather Button, Nigel Capps, Mandy Carnahan, Anne Carter, Danielle Childs, Denise Donaldson, Kelly Hard, Fran Hurford, Yasmin Hussain, Ayesha Javaid, James Jones, Sanal Jose, Michael Leigh, Terry Martin, Helen Millward, Nichola Motherwell, Rachel Rikunenko, Jo Stickley, Julie Summers, Louise Ting, Helen Tivenan, Louise Tonks, Rebecca Wilcox, Maureen Holland, Natalie Keenan, Marc Lyons, Helen Wassall, Chris Marsh, Mervin Mahenthran, Emma Carter, Thomas Kong, Helen Blackman, Ben Creagh-Brown, Sinead Donlon, Natalia Michalak-Glinska, Sheila Mtuwa, Veronika Pristopan, Armorel Salberg, Eleanor Smith, Sarah Stone, Charles Piercy, Jerik Verula, Dorota Burda, Rugia Montaser, Lesley Harden, Irving Mayangao, Cheryl Marriott, Paul Bradley, Celia Harris, Susan Anderson, Eleanor Andrews, Janine Birch, Emma Collins, Kate Hammerton, Ryan O'Leary, Michele Clark, Sarah Purvis, Russell Barber, Claire Hewitt, Annette Hilldrith, Karen Jackson-Lawrence, Sarah Shepardson, Maryanne Wills, Susan Butler, Silvia Tavares, Amy Cunningham, Julia Hindale, Sarwat Arif, Sarah Bean, Karen Burt, Michael Spivey, Carrie Demetriou, Charlotte Eckbad, Sarah Hierons, Lucy Howie, Sarah Mitchard, Lidia Ramos, Alfredo Serrano-Ruiz, Katie White, Fiona Kelly, Daniele Cristiano, Natalie Dormand, Zohreh Farzad, Mahitha Gummadi, Kamal Liyanage, Brijesh Patel, Sara Salmi, Geraldine Sloane, Vicky Thwaites, Mathew Varghese, Anelise C. Zborowski, John Allan, Tim Geary, Gordon Houston, Alistair Meikle, Peter O'Brien, Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches, Mark Vertue, Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joannne Lewis, Stephanie Rees, Metod Oblak, Monica Popescu, Mini Thankachen, Andrew Higham, Kerry Simpson, Jayne Craig, Rosie Baruah, Sheila Morris, Susie Ferguson, Amy Shepherd, Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins, Jaime Carungcong, Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage, Matthew White, Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton, Inez Wynter, Siobhain Carmody, Valerie Joan Page, Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D'Sylva, Kathryn Norman, Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch, Dhaneesha Senaratne, Michaela Hill, Thogulava Kannan, Wild Laura, Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson, Gemma Wray, Helen Langton, Rachel Prout, Malcolm Watters, Catherine Novis, Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Kanta Mahay, Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham, Rachel Walker, Ellen Knights, Alicia Price, Alice Thomas, Chris Thorpe, Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard, Rachael Stead, Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith, Janet Imeson-Wood, Denise Skinner, Jane Gaylard, Dee Mullan, Julie Newman, Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins, Liz Nicol, Rosie Reece-Anthony, Mark Birt, Alison Ghosh, Emma Williams, Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki, Sharon Turney, Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn, Natalia Waddington, Tina Coventry, Susan Fowler, Michael MacMahon, Amanda McGregor, Anne Cowley, Judith Highgate, Jane Gregory, Susan O'Connell, Tim Smith, Luigi Barberis, Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell, Elizabeth Radford, Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White, Phil Donnison, Fiona Trim, Beena Eapen, Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams, Barbara Winter-Goodwin, Ailstair Nichol, Kathy Brickell, Michelle Smyth, Lorna Murphy, Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj, Craig Sell, Paula Hilltout, Jayne Evitts, Amanda Tyler, Joanne Waldron, Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood, Clare Buckley, Peter Barry, Neil Flint, Patel Rekha, Dawn Hales, Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall, Gayathri Subramanian, Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins, Bernadette King, Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon, Watkins Claire, Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga, Emma Virgilio, Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant, Madeleine Anderson, Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle, Bijoy Mathew, Ben Attwood, Penny Parsons, Geraldine Ward, Pamela Bremmer, West Joe, Baird Tracy, Ruddy Jim, Ellie Davies, Sonia Sathe, Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran, Anisha Sukha, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O'Hara, Laura Okeefe, Clare Bradley, Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou, Mark De Neef, Kathy Dent, Elizabeth Horsley, Muhmmad Nauman Akhtar, Sandra Pearson, Dorota Potoczna, Sue Spencer, Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Rachel Mutch, Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland, Sophie Packham, Rehana Bi, Barney Scholefield, Lydia Ashton, Linsha George, Sophie Twiss, David Wright, Manish Chablani, Amy Kirkby, Kimberley Netherton, Kim Davies, Linda O'Brien, Zohra Omar, Emma Perkins, Tracy Lewis, Isobel Sutherland, Karen Burns, Dr Ben Chandler, Kerry Elliott, Janine Mallinson, Alison Turnbull, Prisca Gondo, Bernard Hadebe, Abdul Kayani, Bridgett Masunda, Taya Anderson, Dan Hawcutt, Laura O'Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones, Rachael Dore, Matthew Halkes, Pauline Mercer, Lorraine Thornton, Joy Dawson, Sweyn Garrioch, Melanie Tolson, Jonathan Aldridge, Ritoo Kapoor, David Loader, Karen Castle, Sally Humphreys, Ruth Tampsett, Katherine Mackintosh, Amanda Ayers, Wendy Harrison, Julie North, Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley, Andrew Fagan, Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham, Benjamin Thomas, Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon, Austin Rattray, Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks, Michelle Edwards, Sheena Quaid, Ekaterina Watson, Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne Van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay, Katie Adams, Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie, Miranda Odam, Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis, Alex Lyon, Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson, Sarah Marsh, John Hardy, Henry Houlden, Eleanor Moncur, Ambreen Tariq, Arianna Tucci, Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench, Rebecca Wolf-Roberts, Val Irvine, Benjamin Shelley, Claire Gorman, Abhinav Gupta, Elizabeth Timlick, Rebecca Brady, Barry Milligan, Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter, Alex Howlett, Katy Fidler, Emma Tagliavini, and Kevin Donnelly
Subjects: SARS-CoV-2, host genetics, toll-like receptor 7, targeted sequencing, rare variants, variant collapsing analysis, Genetics, QH426-470
Abstract: Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (
Published: 2024
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4. Value of an orthopaedic admission proforma

Author: Munzir Akasha, Oliver Boughton, and May Cleary
Subjects: Medicine (General), R5-920
Abstract: Background Admission notes are an important aspect of clinical practice and a vital means of communication among healthcare professionals. Incomplete or poor clinical documentation on admission can lead to delayed surgery.Patients and methods A retrospective analysis of 20 consecutive admission notes to our department was compared against the Royal College of Surgeons standards (GSP 2014). A new admission proforma was designed, and after the introductory period, two further retrospective cycles were performed.Results In total, 60 admission notes were analysed. Following the introduction of the proforma, there was an overall improvement in the documentation of the quality and quantity of notes studied.Conclusion Our study demonstrated that a well-structured admission protocol can improve the overall quality of admission notes.
Published: 2024
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5. Dermaptera Community Structure on Oil Palm Ecosystem in Dharmasraya District, Indonesia

Author: Munzir Busnia, Irwin Mirza Umami, and Marina
Subjects: chelisoches, diversity, evenness, natural enemies, Plant culture, SB1-1110, Agriculture (General), S1-972
Abstract: The oil palm ecosystem is one of the suitable habitats for the order Dermaptera. Several physical factors, especially humidity in the oil palm ecosystem, support these insects' existence. In the oil palm ecosystem, Dermaptera has several functions, including as a predator of oil palm pests, but on the other hand, these insects also prey on Elaeidobius kamerunicus Faust, the primary pollinator of oil palm plants. For that reason, research was conducted to study the structure of the Dermaptera community in the ecosystem of oil palm plantations in the Sitiung sub-district. This research was a survey conducted at three locations- Sitiung, Gunung Medan, and Sungai Duo Villages—the collection of insect samples by hand collection. Identification of insect samples was carried out at the species level according to Burr (1910) and Borror et al. (1996). In this study, 214 individuals of the order Dermaptera were found to consist of three species: Cheslisoches mario, Forficula auricularia, and Vostox brunneipennis. C. mario was the dominant Dermaptera species found with an Importance Value Index (IVI) was 1.27. Based on this research, it is known that the community structure of the order Dermaptera was simple because it has low diversity values.
Published: 2024
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6. Promoting Post-Restraint Patient Debriefing in an Acute Psychiatric Inpatient setting

Author: Harry Jackson, Munzir Quraishy, Maya Mendoza, and Alex Berry
Subjects: Psychiatry, RC435-571
Abstract: Aims Controlled physical restraint is a commonly used, but controversial practice in inpatient psychiatric settings, at times bringing psychiatric practice into potential conflict with accepted medical ethical standards for preserving autonomy and bodily-integrity. However, physical restraint can produce high levels of patient distress, re-traumatise those who have experienced physical or sexual abuse, and may lead to inadvertent bodily injury, and even death on rare occasions. There is an international consensus to attempt to reduce restrictive practices, including physical restraint, as demonstrated in the World Health Organization's Quality Rights Initiative. Post-restraint patient debriefing can promote recovery, prevent future restraint, and promote a more ethical and humanising care environment. We aimed to audit the frequency of restraint events, and post-restraint debriefs offered to patients in a single, London-based, male acute psychiatric ward. Methods In the pre-intervention sample, data was extracted from the records of patients admitted over a six-month period (n = 75), to identify the number of patients who had undergone restraint and the number who had been debriefed. The search terms “restrain”, “PMVA”, “response team” and “debrief” were used. After each restraint event, the notes for the following two weeks were reviewed to see if a debrief was delivered. The intervention consisted of a single description and dissemination of the results in a ward business meeting, with instruction that all staff members within the ward multidisciplinary team can help provide debrief if appropriate to do so. Where a patient was known to have been restrained, debriefs were offered during subsequent ward round reviews as appropriate. In the post-intervention sample, we collected data from patients admitted over a 10-month period (n = 89). We used Chi-Squared testing to compare categorical variables pre- and post-intervention. Results Pre-intervention, 15 patients underwent restraint and of these, 8 patients (53.33%) were debriefed. Post-intervention, 21 patients underwent restraint and of these, 10 patients (47.62%) were debriefed. There was no statistical difference in the proportion of patients offered a psychological debrief (p = 0.735). Conclusion Following a single intervention there was not a sustained difference in the proportion of post-restraint debriefs offered. It is likely more sustained interventions would bring about more substantive practice change. Incorporating the need for post-restraint debriefs in daily ward safety-huddles, or in structured “ward round proformas”, may increase the proportion of patients offered post-restraint debriefing. It is possible that the note review strategy did not capture all debriefs delivered.
Published: 2024
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7. SOSIALISASI PEMBIBITAN KAKAO BAGI GENERASI MUDA DI SALINGKA KAMPUS UNIVERSITAS ANDALAS

Author: Obel Obel, Nugraha Ramadhan, Rachmad Hersi Martinsyah, Meisilva Erona Sitepu, and Munzir Busniah
Subjects: kakao, pembibitan, generasi muda, sosialisasi, Social Sciences
Abstract: Kakao termasuk salah satu komoditi andalan Indonesia yang mempunyai sumbangsih besar terhadap perekonomian bangsa. Namun, akhir-akhir ini ketenaran kakao mulai menurun akibat banyaknya terjadi permasalahan mulai dari hulu sampai hilir pengusahaannya. Salah satunya penggunaan bibit yang kurang berkualitas sehingga mempengaruhi produksi dalam jangka panjang. Kondisi ini, mempengaruhi gairah masyarakat dalam melakukan budidaya kakao yang berefek kepada semakin merosotnya produksi kakao secara nasional. Untuk itu, perlu adanya dilakukan antisipasi sedini mungkin dengan cara mensosialisasikan pembibitan kakao kepada para generasi muda khususnya yang berada di sekitar kampus Universitas Andalas Padang. Tujuan kegiatan ini adalah untuk memberikan pengetahuan tentang tanaman kakao dan proses pembibitan kakao kepada generasi muda disalingka kampus Universitas Andalas dalam mendukung pertanian kakao yang berkelanjutan. Kegiatan ini dilaksanakan di Sungai Balang Kecamatan Pauh Kota Padang. Metode yang digunakan berupa sosialisasi terstruktur kepada generasi muda di Salingka Kampus Universitas Andalas. Untuk mengevaluasi hasil kegiatan diberikan berupa kuisioner. Hasil yang diperoleh yaitu terjadinya tingginya antusias peserta bahwa dari hasil kuisioner terlihat 87% peserta yang mengikuti sosialisasi merasa sangat puas terhadap kegiatan yang dilakukan dan 93% berharap kegiatan ini dapat berkelanjutan. Hal ini menunjukkan bahwa adanya peningkatan pemahaman generasi muda di salingka Universitas Andalas terhadap tanaman kakao dan pembibitan kakao serta semangat berwirausaha yang berbasiskan pembibitan kakao. Diharapkan kegiatan ini dapat berkelanjutan dan perlu adannya pendampingan dan pembinaan.
Published: 2023
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8. Sosialisasi Pengelolaan Teaching Farm Pembibitan Kakao Unggul pada Kelompok Tani Kakao se-Kota Padang

Author: Obel Obel, Rachmad Hersi Martinsyah, Armansyah Armansyah, Meisilva Erona Sitepu, Munzir Busniah, Yulmira Yanti, Eka Candra Lina, and Nugraha Ramadhan
Subjects: biofertilizer, cocoa, induction, teaching farm, Social sciences (General), H1-99
Abstract: Cocoa is a plantation commodity that is essential to the Indonesian economy. There are still many problems in cocoa cultivation found in the field, such as using poor-quality seedlings. One of the ways to do this is by taking preventive action by providing immunity induction from the seedling stage. Immunity induction can be done by utilizing Rhizobacteria, arbuscular mycorrhizal fungi, Entomopathogenic fungi, and vegetable pesticides. The Faculty of Agriculture of Universitas Andalas collaborated with the entrepreneurs through a Ministry of Education and Culture program, Matching Fund 2022, to make an innovation, namely the Teaching Farm for superior cocoa nurseries. This activity aims to socialize the cocoa nursery teaching farm in the hope of helping farmers prepare high-quality and sustainable cocoa seeds. This community service activity has been carried out at the Padang City Agriculture Office. The conclusions of this activity include: a) The community service program made by the Teaching Farm Team of Universitas Andalas is by the needs of the farmer group; the farmer group is satisfied and feels this service activity was helpful for the development of the Cocoa farmer group in the future, b) enrichment of understanding of farmer group members regarding biofertilizers and vegetable pesticides.
Published: 2023
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9. The Environmentally IPM Package for Controlling Fall Armyworm (Spodoptera frugiperda) in Maize Field

Author: Nova Yurina, My Syahrawati, Arneti Arneti, and Munzir Busniah
Subjects: Agriculture (General), S1-972
Abstract: Integrated Pest Management (IPM) is a pest control method that combines several control techniques by considering ecological, economic, and sociological consequences. Management efforts with IPM principles can be conducted by cultivating healthy plants and entomopathogen application. This study examined the IPM package's success for controlling fall armyworm (Spodoptera frugiperda) in maize field. This research was conducted in a farmer's maize plantation in the West Pasaman District from August to December 2021. The study used a Randomized Block Design (RBD) which consisted of three treatments and five replications. The treatments were different cultivation techniques using IPM, Non-IPM, and control. The variables observed were the population of S. frugiperda (individual/plant), attack rate (%), attack intensity (%), cob weight (g/cob), and farming cost (IDR). The results showed that the IPM and Non-IPM maize cultivation techniques had no different effect on S. frugiperda, especially survival stage, attack rate, intensity, and yield. However, this effect was higher than the control. In addition, the economic benefits of cultivation with IPM were higher than non-IPM. Therefore, this IPM package can be recommended for controlling S. frugiperda because it is also economically profitable and environmentally friendly.
Published: 2023
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10. Synergism of Tephrosia vogelii and Piper aduncum Based Nanoemulation Against Spodoptera frugiperda

Author: Sang Phước Nguyễn, Eka Candra Lina, Hidrayani Hidrayani, and Munzir Busniah
Subjects: Agriculture
Abstract: The botanical insecticide nanoemulsion is a pesticide having an oil phase and aqueous phase that spontaneously emulsify and range in size from 20 to 200 nm. Bio-combi extracts frequently contain intricate combinations of active ingredients that may work in concert to increase bioactivity. The goal of the study was to develop the optimal nanoformulation and investigate the physiological effects of a synergistic nanoemulsion made from Tephrosia vogelii leaves and Piper aduncum fruit extracts as a substitute pesticide for Spodoptera frugiperda larvae. Low-energy spontaneous emulsification with a magnetic stirrer was used to create nanoemulsions, which were then subjected to a toxicity and food absorption test. Malvern's Zetasizer Nano (ZN), which was used to analyze the insecticidal nano formulae for PSA, revealed that the particle sizes for the 1:1, 3:1, and 1:5 ratios were 204 nm, 4724 nm, and 97 nm, respectively. Only the 1:5 formula, which is classified as a nanoparticle, met the standards for a nanoemulsion and produced S. frugiperda mortality of 82.34% at a concentration of 0.56%, and the LC25, LC50, and LC95 values were 0.1, 0.22, and 1.59%, respectively. The analyzable results demonstrated that the mixed nanoemulsion was additive at the LC50 value was 0.95 while the LC95 value was 0.70%, meaning only marginally synergistic
Published: 2023
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11. Deep Transfer Learning Based Parkinson’s Disease Detection Using Optimized Feature Selection

Author: Sura Mahmood Abdullah, Thekra Abbas, Munzir Hubiba Bashir, Ishfaq Ahmad Khaja, Musheer Ahmad, Naglaa F. Soliman, and Walid El-Shafai
Subjects: Parkinson’s disease, neurological disorder, handwritten records, transfer learning, deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: Parkinson’s disease (PD) is one of the chronic neurological diseases whose progression is slow and symptoms have similarities with other diseases. Early detection and diagnosis of PD is crucial to prescribe proper treatment for patient’s productive and healthy lives. The disease’s symptoms are characterized by tremors, muscle rigidity, slowness in movements, balancing along with other psychiatric symptoms. The dynamics of handwritten records served as one of the dominant mechanisms which support PD detection and assessment. Several machine learning methods have been investigated for the early detection of this disease. But most of these handcrafted feature extraction techniques predominantly suffer from low performance accuracy issues. This cannot be tolerable for dealing with detection of such a chronic ailment. To this end, an efficient deep learning model is proposed which can assist to have early detection of Parkinson’s disease. The significant contribution of the proposed model is to select the most optimum features which have the effect of getting the high-performance accuracies. The feature optimization is done through genetic algorithm wherein $K$ -Nearest Neighbour technique. The proposed novel model results into detection accuracy higher than 95%, precision of 98%, area under curve of 0.90 with a loss of 0.12 only. The performance of proposed model is compared with some state-of-the-art machine learning and deep learning-based PD detection approaches to demonstrate the better detection ability of our model.
Published: 2023
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12. ACADEMIC STRESS AND GRATITUDE TO PROMOTE STUDENT WELL-BEING

Author: Sri Wahyuni, Munzir Hitami, Muslim Afandi, and Hellya Agustina
Subjects: student well-being, academic stress, gratitude, Islam, BP1-253, Psychology, BF1-990
Abstract: Research in education is developing very rapidly and widely, not only examining the cognitive domain but also starting to develop into the affective domain, such as research on student well-being. This study aimed to examine the correlation between academic stress and gratitude with student well-being. The approach used in this research is correlational quantitative. The research scale is given offline and online using a google form. Respondents in this study were 602 students of Madrasah Aliyah Pekanbaru, Riau, Indonesia. The instruments used are the academic stress, gratitude and student well-being scale. The results of data analysis with multiple regression analysis showed that there was a significant relationship between academic stress and gratitude with student well-being (p-value < 0.001; r 0.655), meaning that the hypothesis is accepted, with the effective contribution of academic stress and gratitude simultaneously on student well-being by 42.9%. Academic stress were negatively and significantly associated with student well-being when the gratitude variable was controlled (p < 0.001; Beta -0.521), and gratitude were positively and significantly associated with student well-being when the academic stress variable was controlled (p < 0.001; Beta 0.302). Furthermore, in qualitative data, the researcher found that some students felt stressed with the workload from school because they did not understand the subject matter, communication with teachers was not fluent, anxious and sad, afraid to disappoint parents, and dizzy and frustrated in thinking about the subject matter. The researcher recommends that schools organize training that can reduce academic stress and increase student gratitude, so that student well-being can increase.
Published: 2022
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13. NOCTURNAL BEETLE POPULATION (COLEOPTERA: SCARABAEIDAE) AND PERCENTAGE OF AFFECTED CROPS IN THE MAIN NURSERY OF OIL PALM (Elaeis guineensis Jacq.)

Author: Purnama Devi, Munzir Busniah, and Zahlul Ikhsan
Subjects: apogonia expeditionis, adoretus compressus, nocturnal beetle, oil palm nursery, Plant culture, SB1-1110, Agriculture (General), S1-972
Abstract: Rapid development of oil palm plantations in Indonesia, cause seeds requirement also increase. Nurseries are a phase that is very vulnerable to pests and diseases because the morphological sensitivity of the seedlings which are very responsive. The main pests that attack oil palm in nursery are nocturnal beetles. The objective of this study was to determine the species, population and percentage of crops attacked by the nocturnal beetles in the main nursery phase oil palm (Elaeis guineensis Jacq.). This research was conducted at the CV. Agro Unggul Sejati located in Sungai Kambut Village, Pulau Punjung District, Dharmasraya Regency. The method on this study was a survey. The sample plants were determined systematically, there were 10% of the total number of seeds in each observation block. The trapping of nocturnal beetles was carried out by light traps were installed two traps in each observation block. Observation of the percentage of affected crops was carried out by counting the sample plants that were attacked and vice versa. Two types of nocturnal beetles were found in oil palm main nursery in CV. Agro Unggul Sejati, namely Apogonia expeditionis Ritsema and Adoretus compressus Webb. Morphological characteristics of A. expeditionis are shiny black and sized 8,5-11 mm while A. compressus is reddish brown, with a body length ranging from 1-1,5 cm. The attack of nocturnal beetle cause large tears in the leaves of oil palm seedlings. The population of A. compressus was more abundant than A. expeditionis. There were 45 species of A. compressus, while 29 species of A. expeditionis. The percentage of affected crops caused by the nocturnal beetles in oil palm in the main nursery ranged from 11,12-37,03%.
Published: 2022
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14. Chemotherapy Toxicity in Older Adults Optimized by Geriatric Assessment and Intervention: A Non-Comparative Analysis

Author: Munzir Hamid, Michelle Hannan, Nay Myo Oo, Paula Lynch, Darren J. Walsh, Tara Matthews, Stephen Madden, Miriam O’Connor, Paula Calvert, and Anne M. Horgan
Subjects: chemotherapy, toxicity, geriatric assessment, healthcare utilization, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: The Comprehensive Geriatric Assessment (CGA) is recommended to guide treatment choices in older patients with cancer. Patients ≥ 70 years referred to our oncology service with a new cancer diagnosis are screened using the G-8. Patients with a score of ≤14 are eligible to attend the Geriatric Oncology and Liaison (GOAL) Clinic in our institution, with referral based on physician discretion. Referred patients undergo multidimensional assessments at baseline. CGA domains assessed include mobility, nutritional, cognitive, and psychological status. Chemotherapy toxicity risk is estimated using the Cancer Aging and Research Group (CARG) calculator. We undertook a retrospective analysis of patients attending the GOAL clinic over a 30-month period to April 2021. The objective was to determine rates of treatment dose modifications, delays, discontinuation, and unscheduled hospitalizations as surrogates for cytotoxic therapy toxicity in these patients. These data were collected retrospectively. Ninety-four patients received chemotherapy; the median age was 76 (70–87) and 45 were female (48%). Seventy-five (80%) had an ECOG PS of 0–1. Seventy-two (77%) had gastrointestinal cancer, and most had stage III (47%) or IV (40%) disease. Chemotherapy with curative intent was received by 51% (n = 48) and 51% received monotherapy. From the CGA, the median Timed Up and Go was 11 s (7.79–31.6), and 90% reported no falls in the prior 6 months. The median BMI was 26.93 (15.43–39.25), with 70% at risk or frankly malnourished by the Mini Nutritional Assessment. Twenty-seven (29%) patients had impaired cognitive function. Forty-three (46%) had a high risk of toxicity based on the baseline CARG toxicity calculator. Twenty-six (28%) required dose reduction, 55% (n = 52) required a dose delay, and 36% (n = 34) had a hospitalization due to toxicity. Thirty-nine patients (42%) discontinued treatment due to toxicity. Despite intensive assessment, clinical optimization and personalized treatment decisions, older adults with cancer remain at high risk of chemotherapy toxicity.
Published: 2022
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15. Menyingkap Makna Objek Pendidikan dalam Istilah al-Ahl, al-‘Asyirah, dan al-Aqrab

Author: Musaddad Harahap, Munzir Hitami, and Abu Anwar
Subjects: objek, ahl, ‘asyirah, aqrab, pendidikan islam, Special aspects of education, LC8-6691
Abstract: The problem in this study is the importance of understanding the nature of the object of education from the perspective of Islamic education. In general, the object of education is often understood as just a human who needs learning. But in Islamic education, the object of education is not just individual humans, but more than that. Humans as objects of education have very broad dimensions. Islamic education has indicated this in its main source, namely the Qur'an and the Sunnah of the Prophet Muhammad. To answer this research problem, the approach used is library research. The results of this study are the object of education in Islam refers to several words. First, the word ahl means family, wife, relatives, or people who live in the same place. the word ahl can also refer to various groups that are formed and formed in the reality of human life. Second, the word 'asyirah has varied meanings. The emphasis on the meaning of the most dominant is the family in a larger scope when compared to the family in terms of ahl. So that the term 'asyirah is not only limited to a relationship because of kinship, but also a relationship because of similarities both geographically or in terms of place of residence, ethnicity, tribe, or because of the intense interactive communication between existing community groups. Third, the term al-qurbu refers more to a family bound by brotherhood, perhaps the brotherhood is the result of a lineage or brotherhood which is only limited to common perception. Thus, in Islamic education, education does not only focus on how to teach humans as individuals, but humans in various communities also receive serious attention in order to realize the goals of Islamic education, namely the actualization of faith and piety to Allah SWT in human’s soul.
Published: 2022
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16. Effectivity of Mangkokan Leaf Extract (Nothopanax scutellarium Merr) with Different Treatments to Control Golden Snail (Pomacea canaliculata Lamarck)

Author: Rusdi Rusli, Imelda Sari, and Munzir Busniah
Subjects: Agriculture (General), S1-972
Abstract: Mangkokan leaves (Nothopanax scutellarium Merr) have been used to control golden snail (Pomacea canaliculata Lamarck) in several preparations. This research aimed to study the most effective preparation of the mangkokan leaf extract to control the golden snail. The research was conducted in the Insect Bioecology Laboratory and agriculture field in Batu Busuak Village, Pauh District, Padang City, from March to April 2021. This study used a Completely Randomized Design (CRD) consisting of five treatments and five replications. The treatments were several preparations of mangkokan leaves with a concentration of 5 g/l: control, fresh, boiled, sun-dried, and oven-dried. The observed variables were mortality of the golden snail, the weight of feed consumed, and the decrease in the eating activity of the golden snail. The result showed that botanical molluscicide from mangkokan leaves preparation by oven-dried and fresh were the two most effective in controlling the golden snail because they caused 100 % mortality of the golden snail, reduced the feed number consumed, with decreasing in feeding activity of 54.91% and 52.94%.
Published: 2022
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17. Implementation of the TERPADU Learning Concept during the Covid-19 Pandemic at Integrated Islamic Junior High School

Author: Elbina Mamla Sa'idah, Munzir Hitami, and Abu Anwar
Subjects: terpadu, jsit, pandemic, Education (General), L7-991
Abstract: Integrated Islamic Schools under the auspices of JSIT have an integrated curriculum by combining the national curriculum and JSIT's own curriculum. However, during the Covid-19 Pandemic, limited learning activities caused problems in the process of implementing the TERPADU approach (study, explore, formulate, present, apply, mundane, ukhrowi). This study aims to analyze the implementation of the TERPADU concept at SMPS IT Mutiara Duri. The research method uses a case study at SMPIT Mutiara Duri with data collection techniques involving interviews, documentation and observations. The results of the study revealed that the learning plan and implementation of learning with the TERPADU approach could be implemented well and the teacher had no difficulty in meeting the indicators of success in the subjects being taught.
Published: 2022
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18. Pengaruh Latihan Beban Dumbell terhadap Kecepatan Pukulan Straight pada Atlet UKM Muay Thai Unsyiah Banda Aceh

Author: Zikrur Rahmat, Irfandi, and Munzir
Subjects: dumbbell weight training, straight blow, muaythai, Sports, GV557-1198.995
Abstract: Hasil pengamatan peneliti di UKM Unsyiah, tidak semua atlet UKM Muay Thai Unsyiah dapat melakukan pukulan straight dengan baik dan cepat. Masih banyak yang melakukan pukulan yang kadang kala tidak terarah dan lemah serta tidak tepat mengenai sasaran. Keadaan ini disebabkan karena kurangnya dukungan kemampuan fisik dari atlet serta kurang menguasai teknik pukulan dengan baik. Disamping itu, ditemukan sekitar 80% pemain pemula mengalami kelemahan ketika memukul straight, terutama ketika melakukan teknik pukulan straight, yang diakibatkan karena lemahnya latihan beban dumbell. Penelitian ini bertujuan untuk mengetahui pengaruh latihan beban dumbell terhadap kecepatan pukulan straight pada atlet UKM Muay Thai Unsyiah. Pendekatan Penelitian menggunakan kuantitatif dengan menggunakan desain korelasional. Sampel dalam penelitian ini adalah atlet UKM Muay Thai Unsyiah yang berjumlah 8 orang yang terdiri dari 4 orang atlet putra dan 4 orang atlet putri. Instrumen dalam penelitian ini adalah pretest dan postest. Hasil Penelitian menunjukkan bahwa latihan beban dumbell berpengaruh terhadap kecepatan pukulan straight pada atlet UKM Muay Thai Unsyiah. Kemudian dari perhitungan koefisien korelasi data, diperoleh nilai pengaruh antara latihan beban dumbbel terhadap kecepatan pukulan straight sebesar 0,92 dimana interpretasi koefisien korelasi nya terletak pada tingkat pengaruh yang tinggi (ada pengaruh). Persentase koefisien korelasi nya 84,64%. dimana berarti latihan beban dumbbel (X) memberikan kontribusi terhadap kecepatan pukulan straight (Y) sebesar 84,64% dan sisa nya 15,36% dipengaruhi oleh faktor-faktor lain.
Published: 2022
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19. Diversity-sensitive measures in German hospitals – attitudes, implementation, and barriers according to administration managers

Author: Fabian Erdsiek, Tuğba Aksakal, Maria Mader, Munzir Idris, Yüce Yılmaz-Aslan, Oliver Razum, and Patrick Brzoska
Subjects: Diversity, Hospital care, Germany, Culturally sensitive, Public aspects of medicine, RA1-1270
Abstract: Abstract Background Populations have varying needs and expectations concerning health care that result from diversity characteristics such as a migrant background, gender identity, disability, and age. These needs and expectations must be considered to ensure adequate utilization and quality of health services. Approaches to address diversity do exist, however, little is known about the extent to which they are implemented by health care facilities. The present study aims to examine, which measures and structures hospitals in Germany employ to address diversity, as well as which barriers they encounter in doing so. Methods A mixed-mode survey among administration managers of all registered German hospitals (excluding rehabilitation hospitals; n = 1125) was conducted between May and October 2019 using pen-and-paper and online questionnaires. Results were analyzed descriptively. Results Data from n = 112 hospitals were available. While 57.1% of hospitals addressed diversity in their mission statement and 59.9% included diversity considerations in quality management, dedicated working groups and diversity commissioners were less prevalent (15.2% each). The majority of hospitals offered multi-lingual admission and exit interviews (59.8%), treatments or therapies (57.1%), but only few had multi-lingual meal plans (12.5%) and seminars or presentations (11.6%). While 41.1% of the hospitals offered treatment and/or nursing exclusively by staff of the same sex, only 17.0% offered group therapies for both sexes separately. According to the managers, the main barriers were a lack of financial resources (54.5%), a lack of incentives from the funding providers (49.1%), and organizational difficulties (45.5%). Other reported barriers were a lack of conviction of the necessity among decision makers (28.6%) and a lack of motivation among staff members (19.6%). Conclusions Administration managers from only a small proportion of hospitals participated in our survey on diversity sensitivity. Even hospitals of those who did are currently not adequately addressing the diversity of staff members and patients. Most hospitals address diversity on an ideational level, practical measures are not widely implemented. Existing measures suggest that most hospitals have no overarching concept to address diversity in a broader sense. The main reported barriers relate to economic aspects, a lack of support in organizing and implementing corresponding measures and a lack of awareness or motivation.
Published: 2022
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20. Metastatic gastroesophageal cancer in older patients – is this patient cohort represented in clinical trials?

Author: Maeve A. Hennessy, Munzir Hamid, Niamh M. Keegan, Lynda Corrigan, Caitriona Goggin, Nay Myo Oo, Marie Carrigan, David Mockler, Anita O’Donovan, and Anne M. Horgan
Subjects: Gastroesophageal, Metastatic, Phase III clinical trials, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Older patients are underrepresented in the clinical trials that determine the standards of care for oncological treatment. We conducted a review to identify whether there have been age-restrictive inclusion criteria in clinical trials over the last twenty five years, focusing on patients with metastatic gastroesophageal cancer. Methods A search strategy was developed encompassing Embase, PubMed and The Cochrane Library databases. Completed phase III randomised controlled trials evaluating systemic anti-cancer therapies in metastatic gastroesophageal malignancies from 1st January 1995 to 18th November 2020 were identified. These were screened for eligibility using reference management software (Covidence; Veritas Health Innovation Ltd). Data including age inclusion/exclusion criteria and median age of participants were recorded. The percentage of patients ≥ 65 enrolled was collected where available. The change over time in the proportion of studies using an upper age exclusion was estimated using a linear probability model. Results Three hundred sixty-three phase III studies were identified and screened, with 66 trials remaining for final analysis. The majority of trials were Asian (48%; n = 32) and predominantly evaluated gastric malignancies, (86%; n = 56). The median age of participants was 62 (range 18–94). Thirty-two percent (n = 21) of studies specified an upper age limit for inclusion and over half of these were Asian studies. The median age of exclusion was 75 (range 65–80). All studies prior to 2003 used an upper age exclusion (n = 12); whereas only 9 that started in 2003 or later did (17%). Among later studies, there was a very modest downward yearly-trend in the proportion of studies using an upper age exclusion (-0.02 per year; 95%CI -0.05 to 0.01; p = 0.31). Fifty-two percent (n = 34) of studies specified the proportion of their study population who were ≥ 65 years. Older patients represented only 36% of the trial populations in these studies (range 7–60%). Conclusions Recent years have seen improvements in clinical trial protocols, with many no longer specifying restrictive age criteria. Reasons for poor representation of older patients are complex and ongoing efforts are needed to broaden eligibility criteria and prioritise the inclusion of older adults in clinical trials.
Published: 2022
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21. Silver-Doped Zeolitic Imidazolate Framework (Ag@ZIF-8): An Efficient Electrocatalyst for CO2 Conversion to Syngas

Author: Muhammad Usman and Munzir H. Suliman
Subjects: metal–organic frameworks, bimetallic, electrocatalysts, CO2 utilization, syngas, Chemical technology, TP1-1185, Chemistry, QD1-999
Abstract: To enable the reuse of carbon dioxide (CO2), electrocatalytic reduction of CO2 (CO2RR) into syngas with a controllable H2/CO ratio is considered a cost-effective and intriguing approach. Here, a number of silver (Ag)-doped, zeolitic imidazole framework composites were prepared by a facile method. The outcomes demonstrate that CO2 electroreduction on Ag-doped ZIF-8 catalysts produces just CO and H2, without having any liquid fuel, resulting in a total faradaic efficiency approaching 100%. The most optimal Ag-Zn-ZIF-8 (10% Ag, 90% Zn) demonstrates good selectivity for syngas (CO and H2) that can be easily adjusted from 3:1 to 1:3 (H2/CO) by changing the applied voltage during the CO2 conversion process.
Published: 2023
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22. High-Throughput Phenotyping of Clinical Text Using Large Language Models

Author: Hier, Daniel B., Munzir, S. Ilyas, Stahlfeld, Anne, Obafemi-Ajayi, Tayo, and Carrithers, Michael D.
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, I.7, I.2
Abstract: High-throughput phenotyping automates the mapping of patient signs to standardized ontology concepts and is essential for precision medicine. This study evaluates the automation of phenotyping of clinical summaries from the Online Mendelian Inheritance in Man (OMIM) database using large language models. Due to their rich phenotype data, these summaries can be surrogates for physician notes. We conduct a performance comparison of GPT-4 and GPT-3.5-Turbo. Our results indicate that GPT-4 surpasses GPT-3.5-Turbo in identifying, categorizing, and normalizing signs, achieving concordance with manual annotators comparable to inter-rater agreement. Despite some limitations in sign normalization, the extensive pre-training of GPT-4 results in high performance and generalizability across several phenotyping tasks while obviating the need for manually annotated training data. Large language models are expected to be the dominant method for automating high-throughput phenotyping of clinical text., Comment: Submitted to IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Houston TX
Published: 2024

23. A Large Language Model Outperforms Other Computational Approaches to the High-Throughput Phenotyping of Physician Notes

Author: Munzir, Syed I., Hier, Daniel B., Oommen, Chelsea, and Carrithers, Michael D.
Subjects: Computer Science - Artificial Intelligence, I.2
Abstract: High-throughput phenotyping, the automated mapping of patient signs and symptoms to standardized ontology concepts, is essential to gaining value from electronic health records (EHR) in the support of precision medicine. Despite technological advances, high-throughput phenotyping remains a challenge. This study compares three computational approaches to high-throughput phenotyping: a Large Language Model (LLM) incorporating generative AI, a Natural Language Processing (NLP) approach utilizing deep learning for span categorization, and a hybrid approach combining word vectors with machine learning. The approach that implemented GPT-4 (a Large Language Model) demonstrated superior performance, suggesting that Large Language Models are poised to be the preferred method for high-throughput phenotyping of physician notes., Comment: Submitted to AMIA Annual Symposium 2024, San Francisco CA
Published: 2024

24. Low Overpotential Electrochemical Reduction of CO2 to Ethanol Enabled by Cu/CuxO Nanoparticles Embedded in Nitrogen-Doped Carbon Cuboids

Author: Monther Q. Alkoshab, Eleni Thomou, Ismail Abdulazeez, Munzir H. Suliman, Konstantinos Spyrou, Wissam Iali, Khalid Alhooshani, and Turki N. Baroud
Subjects: electrochemical reduction, CO2, ethanol, low overpotential, porous carbon support, Cu nanoparticles, Chemistry, QD1-999
Abstract: The electrochemical conversion of CO2 into value-added chemicals is a promising approach for addressing environmental and energy supply problems. In this study, electrochemical CO2 catalysis to ethanol is achieved using incorporated Cu/CuxO nanoparticles into nitrogenous porous carbon cuboids. Pyrolysis of the coordinated Cu cations with nitrogen heterocycles allowed Cu nanoparticles to detach from the coordination complex but remain dispersed throughout the porous carbon cuboids. The heterogeneous composite Cu/CuxO-PCC-0h electrocatalyst reduced CO2 to ethanol at low overpotential in 0.5 M KHCO3, exhibiting maximum ethanol faradaic efficiency of 50% at −0.5 V vs. reversible hydrogen electrode. Such electrochemical performance can be ascribed to the synergy between pyridinic nitrogen species, Cu/CuxO nanoparticles, and porous carbon morphology, together providing efficient CO2 diffusion, activation, and intermediates stabilization. This was supported by the notably high electrochemically active surface area, rich porosity, and efficient charge transfer properties.
Published: 2023
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25. Electrochemical Reduction of CO2 to C1 and C2 Liquid Products on Copper-Decorated Nitrogen-Doped Carbon Nanosheets

Author: Munzir H. Suliman, Zain H. Yamani, and Muhammad Usman
Subjects: CO2 conversion, electrocatalysts, copper catalysts, carbon materials, ECO2RR, Chemistry, QD1-999
Abstract: Due to the significant rise in atmospheric carbon dioxide (CO2) concentration and its detrimental environmental effects, the electrochemical CO2 conversion to valuable liquid products has received great interest. In this work, the copper-melamine complex was used to synthesize copper-based electrocatalysts comprising copper nanoparticles decorating thin layers of nitrogen-doped carbon nanosheets (Cu/NC). The as-prepared electrocatalysts were characterized by XRD, SEM, EDX, and TEM and investigated in the electrochemical CO2 reduction reaction (ECO2RR) to useful liquid products. The electrochemical CO2 reduction reaction was carried out in two compartments of an electrochemical H-Cell, using 0.5 M potassium bicarbonate (KHCO3) as an electrolyte; nuclear magnetic resonance (1H NMR) was used to analyze and quantify the liquid products. The electrode prepared at 700 °C (Cu/NC-700) exhibited the best dispersion for the copper nanoparticles on the carbon nanosheets (compared to Cu/NC-600 & Cu/NC-800), highest current density, highest electrochemical surface area, highest electrical conductivity, and excellent stability and faradic efficiency (FE) towards overall liquid products of 56.9% for formate and acetate at the potential of −0.8V vs. Reversible Hydrogen Electrode (RHE).
Published: 2022
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26. High Throughput Phenotyping of Physician Notes with Large Language and Hybrid NLP Models

Author: Munzir, Syed I., Hier, Daniel B., and Carrithers, Michael D.
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, I.2, J.2
Abstract: Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic health records requires high throughput methods. Over the past thirty years, progress toward making high throughput phenotyping feasible. In this study, we demonstrate that a large language model and a hybrid NLP model (combining word vectors with a machine learning classifier) can perform high throughput phenotyping on physician notes with high accuracy. Large language models will likely emerge as the preferred method for high throughput deep phenotyping of physician notes., Comment: Submitted to IEEE EMBS Summer conference 2024
Published: 2024

27. Efficient CNN-based disaster events classification using UAV-aided images for emergency response application

Author: Bashir, Munzir Hubiba, Ahmad, Musheer, Rizvi, Danish Raza, and El-Latif, Ahmed A. Abd
Published: 2024
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28. On the Impact of Orbital Motion on Handoff and Coverage in Multi-antenna LEO Satellite Systems.

Author: Munzir Mohamed, Hina Tabassum, Hesham ElSawy, and Ekram Hossain 0001
Published: 2024
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29. Phenazine Porous Polymers for Radioactive Iodine Capture

Author: Amasha, Hassan A., Kulal, Nagendra, Sulaiman, Munzir H., Al-Abdullah, Tariq A., Al Hamouz, Othman Charles S., Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Shams, Afaque, editor, Al-Athel, Khaled, editor, Tiselj, Iztok, editor, Pautz, Andreas, editor, and Kwiatkowski, Tomasz, editor
Published: 2024
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30. Technology Adoption in Halal Logistics in Malaysia: Exploring Types, Benefits and Challenges for Halal Warehouse and Transportation

Author: Khairuddin, Muhamad Munzir, Amanshah, Tengku Nurhasya Tengku, Norman, Muhammad Raziq, Rahman, Nor Aida Abdul, editor, and Ali, Mohd Helmi, editor
Published: 2024
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31. Mathematical Representation Abilities and Self-Confidence through Application of Discovery Learning Model with Geogebra-assisted

Author: Lestari, Dwy, Usman, Usman, Munzir, Said, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Johar, Rahmah, editor, Binti Mohd Saat, Rohaida, editor, Wissehr, Cathy, editor, Sao, Vibol, editor, and Zai, Sajid Ali Yousuf, editor
Published: 2024
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32. Cooling Behaviour and Reusability of Hot Mix Asphalt

Author: Razak, Aidiel Ashraf Abdul, Hassan, Norhidayah Abdul, Zawawi, Munzir Abdullah, Mahmud, Mohd Zul Hanif, Mashros, Nordiana, Mohamed, Azman, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, and Sabtu, Nuridah, editor
Published: 2024
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33. Mathematical Representation Abilities and Self-Confidence through Application of Discovery Learning Model with Geogebra-assisted

Author: Lestari, Dwy, primary, Usman, Usman, additional, and Munzir, Said, additional
Published: 2024
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34. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author: Rimoldi, Valeria, Paraboschi, Elvezia M., Bandera, Alessandra, Peyvandi, Flora, Grasselli, Giacomo, Blasi, Francesco, Malvestiti, Francesco, Pelusi, Serena, Bianco, Cristiana, Miano, Lorenzo, Lombardi, Angela, Invernizzi, Pietro, Gerussi, Alessio, Citerio, Giuseppe, Biondi, Andrea, Valsecchi, Maria Grazia, Cazzaniga, Marina Elena, Foti, Giuseppe, Beretta, Ilaria, D'Angiò, Mariella, Bettini, Laura Rachele, Farré, Xavier, Iraola-Guzmán, Susana, Kogevinas, Manolis, Castaño-Vinyals, Gemma, Garcia-Etxebarria, Koldo, Nafria, Beatriz, D'Amato, Mauro, Palom, Adriana, Begg, Colin, Clohisey, Sara, Hinds, Charles, Horby, Peter, Knight, Julian, Ling, Lowell, Maslove, David, McAuley, Danny, Millar, Johnny, Montgomery, Hugh, Nichol, Alistair, Openshaw, Peter J.M., Pereira, Alexandre C., Ponting, Chris P., Rowan, Kathy, Semple, Malcolm G., Shankar-Hari, Manu, Summers, Charlotte, Walsh, Timothy, Baillie, J. Kenneth, Aravindan, Latha, Armstrong, Ruth, Biggs, Heather, Boz, Ceilia, Brown, Adam, Clark, Richard, Coutts, Audrey, Coyle, Judy, Cullum, Louise, Das, Sukamal, Day, Nicky, Donnelly, Lorna, Duncan, Esther, Fawkes, Angie, Fineran, Paul, Fourman, Max Head, Furlong, Anita, Furniss, James, Gallagher, Bernadette, Gilchrist, Tammy, Golightly, Ailsa, Griffiths, Fiona, Hafezi, Katarzyna, Hamilton, Debbie, Hendry, Ross, Law, Andy, Law, Dawn, Law, Rachel, Law, Sarah, Lidstone-Scott, Rebecca, Macgillivray, Louise, Maclean, Alan, Mal, Hanning, McCafferty, Sarah, Mcmaster, Ellie, Meikle, Jen, Moore, Shona C., Morrice, Kirstie, Murphy, Lee, Murphy, Sheena, Hellen, Mybaya, Oosthuyzen, Wilna, Zheng, Chenqing, Chen, Jiantao, Parkinson, Nick, Paterson, Trevor, Schon, Katherine, Stenhouse, Andrew, Das, Mihaela, Swets, Maaike, Szoor-McElhinney, Helen, Taneski, Filip, Turtle, Lance, Wackett, Tony, Ward, Mairi, Weaver, Jane, Wrobel, Nicola, Zechner, Marie, Arbane, Gill, Bociek, Aneta, Campos, Sara, Grau, Neus, Jones, Tim Owen, Lim, Rosario, Marotti, Martina, Ostermann, Marlies, Whitton, Christopher, Alldis, Zoe, Astin-Chamberlain, Raine, Bibi, Fatima, Biddle, Jack, Blow, Sarah, Bolton, Matthew, Borra, Catherine, Bowles, Ruth, Burton, Maudrian, Choudhury, Yasmin, Collier, David, Cox, Amber, Easthope, Amy, Ebano, Patrizia, Fotiadis, Stavros, Gurasashvili, Jana, Halls, Rosslyn, Hartridge, Pippa, Kallon, Delordson, Kassam, Jamila, Lancoma-Malcolm, Ivone, Matharu, Maninderpal, May, Peter, Mitchelmore, Oliver, Newman, Tabitha, Patel, Mital, Pheby, Jane, Pinzuti, Irene, Prime, Zoe, Prysyazhna, Oleksandra, Shiel, Julian, Taylor, Melanie, Tierney, Carey, Wood, Suzanne, Zak, Anne, Zongo, Olivier, Bonner, Stephen, Hugill, Keith, Jones, Jessica, Liggett, Steven, Headlam, Evie, Bandla, Nageswar, Gellamucho, Minnie, Davies, Michelle, Thompson, Christopher, Abdelrazik, Marwa, Bakthavatsalam, Dhanalakshmi, Elhassan, Munzir, Ganesan, Arunkumar, Haldeos, Anne, Moreno-Cuesta, Jeronimo, Purohit, Dharam, Vincent, Rachel, Xavier, Kugan, Rohit, Kumar, Alasdair, Frater, Saleem, Malik, David, Carter, Samuel, Jenkins, Lamond, Zoe, Alanna, Wall, Fernandez-Roman, Jaime, Hamilton, David O., Johnson, Emily, Johnston, Brian, Martinez, Maria Lopez, Mulla, Suleman, Shaw, David, Waite, Alicia A.C., Waugh, Victoria, Welters, Ingeborg D., Williams, Karen, Cavazza, Anna, Cockrell, Maeve, Corcoran, Eleanor, Depante, Maria, Finney, Clare, Jerome, Ellen, McPhail, Mark, Nayak, Monalisa, Noble, Harriet, O'Reilly, Kevin, Pappa, Evita, Saha, Rohit, Saha, Sian, Smith, John, Knighton, Abigail, Antcliffe, David, Banach, Dorota, Brett, Stephen, Coghlan, Phoebe, Fernandez, Ziortza, Gordon, Anthony, Rojo, Roceld, Arias, Sonia Sousa, Templeton, Maie, Meredith, Megan, Morris, Lucy, Ryan, Lucy, Clark, Amy, Sampson, Julia, Peters, Cecilia, Dent, Martin, Langley, Margaret, Ashraf, Saima, Wei, Shuying, Andrew, Angela, Bashyal, Archana, Davidson, Neil, Hutton, Paula, McKechnie, Stuart, Wilson, Jean, Baptista, David, Crowe, Rebecca, Fernandes, Rita, Herdman-Grant, Rosaleen, Joseph, Anna, O'Connor, Denise, Allen, Meryem, Loveridge, Adam, McKenley, India, Morino, Eriko, Naranjo, Andres, Simms, Richard, Sollesta, Kathryn, Swain, Andrew, Venkatesh, Harish, Khera, Jacyntha, Fox, Jonathan, Andrew, Gillian, Barclay, Lucy, Callaghan, Marie, Campbell, Rachael, Clark, Sarah, Hope, Dave, Marshall, Lucy, McCulloch, Corrienne, Briton, Kate, Singleton, Jo, Birch, Sohphie, Brimfield, Lutece, Daly, Zoe, Pogson, David, Rose, Steve, Battle, Ceri, Brinkworth, Elaine, Harford, Rachel, Murphy, Carl, Newey, Luke, Rees, Tabitha, Williams, Marie, Arnold, Sophie, Polgarova, Petra, Stroud, Katerina, Meaney, Eoghan, Jones, Megan, Ng, Anthony, Agrawal, Shruti, Pathan, Nazima, White, Deborah, Daubney, Esther, Elston, Kay, Grauslyte, Lina, Hussain, Musarat, Phull, Mandeep, Pogreban, Tatiana, Rosaroso, Lace, Salciute, Erika, Franke, George, Wong, Joanna, George, Aparna, Ortiz-Ruiz de Gordoa, Laura, Peasgood, Emily, Phillips, Claire, Bates, Michelle, Dasgin, Jo, Gill, Jaspret, Nilsson, Annette, Scriven, James, Delgado, Carlos Castro, Dawson, Deborah, Ding, Lijun, Durrant, Georgia, Ezeobu, Obiageri, Farnell-Ward, Sarah, Harrison, Abiola, Kanu, Rebecca, Leaver, Susannah, Maccacari, Elena, Manna, Soumendu, Saluzzio, Romina Pepermans, Queiroz, Joana, Samakomva, Tinashe, Sicat, Christine, Texeira, Joana, Da Gloria, Edna Fernandes, Lisboa, Ana, Rawlins, John, Mathew, Jisha, Kinch, Ashley, Hurt, William James, Shah, Nirav, Clark, Victoria, Thanasi, Maria, Yun, Nikki, Patel, Kamal, Bennett, Sara, Goodwin, Emma, Jackson, Matthew, Kent, Alissa, Tibke, Clare, Woodyatt, Wiesia, Zaki, Ahmed, Abraheem, Azmerelda, Bamford, Peter, Cawley, Kathryn, Dunmore, Charlie, Faulkner, Maria, Girach, Rumanah, Jeffrey, Helen, Jones, Rhianna, London, Emily, Nagra, Imrun, Nasir, Farah, Sainsbury, Hannah, Smedley, Clare, Patel, Tahera, Smith, Matthew, Chukkambotla, Srikanth, Kazi, Aayesha, Hartley, Janice, Dykes, Joseph, Hijazi, Muhammad, Keith, Sarah, Khan, Meherunnisa, Ryan-Smith, Janet, Springle, Philippa, Thomas, Jacqueline, Truman, Nick, Saad, Samuel, Coleman, Dabheoc, Fine, Christopher, Matt, Roseanna, Gay, Bethan, Dalziel, Jack, Ali, Syamlan, Goodchild, Drew, Harling, Rhiannan, Bhatterjee, Ravi, Goddard, Wendy, Davison, Chloe, Duberly, Stephen, Hargreaves, Jeanette, Bolton, Rachel, Davey, Miriam, Golden, David, Seaman, Rebecca, Cherian, Shiney, Cutler, Sean, Heron, Anne Emma, Roynon-Reed, Anna, Szakmany, Tamas, Williams, Gemma, Richards, Owen, Cheema, Yusuf, Brooke, Hollie, Buckley, Sarah, Suarez, Jose Cebrian, Charlesworth, Ruth, Hansson, Karen, Norris, John, Poole, Alice, Rose, Alastair, Sandhu, Rajdeep, Sloan, Brendan, Smithson, Elizabeth, Thirumaran, Muthu, Wagstaff, Veronica, Metcalfe, Alexandra, Brunton, Mark, Caterson, Jess, Coles, Holly, Frise, Matthew, Rai, Sabi Gurung, Jacques, Nicola, Keating, Liza, Tilney, Emma, Bartley, Shauna, Bhuie, Parminder, Gibson, Sian, Lyle, Amanda, McNeela, Fiona, Radhakrishnan, Jayachandran, Hughes, Alistair, Yates, Bryan, Reynolds, Jessica, Campbell, Helen, Thompsom, Maria, Dodds, Steve, Duffy, Stacey, Greer, Sandra, Shuker, Karen, Tridente, Ascanio, Khade, Reena, Sundar, Ashok, Tsinaslanidis, George, Birkinshaw, Isobel, Carter, Joseph, Howard, Kate, Ingham, Joanne, Joy, Rosie, Pearson, Harriet, Roche, Samantha, Scott, Zoe, Bancroft, Hollie, Bellamy, Mary, Carmody, Margaret, Daglish, Jacqueline, Moore, Faye, Rhodes, Joanne, Sangombe, Mirriam, Kadiri, Salma, Croft, Maria, White, Ian, Frost, Victoria, Aquino, Maia, Jha, Rajeev, Krishnamurthy, Vinodh, Lim, Lai, Lim, Li, Combes, Edward, Joefield, Teishel, Monnery, Sonja, Beech, Valerie, Trotman, Sallyanne, Almaden-Boyle, Christine, Austin, Pauline, Cabrelli, Louise, Cole, Stephen, Casey, Matt, Chapman, Susan, Whyte, Clare, Baird, Yolanda, Butler, Aaron, Chadbourn, Indra, Folkes, Linda, Fox, Heather, Gardner, Amy, Gomez, Raquel, Hobden, Gillian, Hodgson, Luke, King, Kirsten, Margarson, Michael, Martindale, Tim, Meadows, Emma, Raynard, Dana, Thirlwall, Yvette, Helm, David, Margalef, Jordi, Criste, Kristine, Cusack, Rebecca, Golder, Kim, Golding, Hannah, Jones, Oliver, Leggett, Samantha, Male, Michelle, Marani, Martyna, Prager, Kirsty, Williams, Toran, Roberts, Belinda, Salmon, Karen, Anderson, Peter, Archer, Katie, Austin, Karen, Davis, Caroline, Durie, Alison, Kelsall, Olivia, Thrush, Jessica, Vigurs, Charlie, Wild, Laura, Wood, Hannah-Louise, Tranter, Helen, Harrison, Alison, Cowley, Nicholas, McAlindon, Michael, Burtenshaw, Andrew, Digby, Stephen, Low, Emma, Morgan, Aled, Cother, Naiara, Rankin, Tobias, Clayton, Sarah, McCurdy, Alex, Ahmed, Cecilia, Baines, Balvinder, Clamp, Sarah, Colley, Julie, Haq, Risna, Hayes, Anne, Hulme, Jonathan, Hussain, Samia, Joseph, Sibet, Kumar, Rita, Maqsood, Zahira, Purewal, Manjit, Benham, Leonie, Bradshaw, Zena, Brown, Joanna, Caswell, Melanie, Cupitt, Jason, Melling, Sarah, Preston, Stephen, Slawson, Nicola, Stoddard, Emma, Warden, Scott, Deacon, Bethan, Lynch, Ceri, Pothecary, Carla, Roche, Lisa, Howe, Gwenllian Sera, Singh, Jayaprakash, Turner, Keri, Ellis, Hannah, Stroud, Natalie, Hunt, Jodie, Dearden, Joy, Dobson, Emma, Drummond, Andy, Mulcahy, Michelle, Munt, Sheila, O'Connor, Grainne, Philbin, Jennifer, Rishton, Chloe, Tully, Redmond, Winnard, Sarah, Cathcart, Susanne, Duffy, Katharine, Puxty, Alex, Puxty, Kathryn, Turner, Lynne, Ireland, Jane, Semple, Gary, Long, Kate, Whiteley, Simon, Wilby, Elizabeth, Ogg, Bethan, Cowton, Amanda, Kay, Andrea, Kent, Melanie, Potts, Kathryn, Wilkinson, Ami, Campbell, Suzanne, Brown, Ellen, Melville, Julie, Naisbitt, Jay, Joseph, Rosane, Lazo, Maria, Walton, Olivia, Neal, Alan, Alexander, Peter, Allen, Schvearn, Bradley-Potts, Joanne, Brantwood, Craig, Egan, Jasmine, Felton, Timothy, Padden, Grace, Ward, Luke, Moss, Stuart, Glasgow, Susannah, Abel, Lynn, Brett, Michael, Digby, Brian, Gemmell, Lisa, Hornsby, James, MacGoey, Patrick, O'Neil, Pauline, Price, Richard, Rodden, Natalie, Rooney, Kevin, Sundaram, Radha, Thomson, Nicola, Hopkins, Bridget, Thrasyvoulou, Laura, Willis, Heather, Clark, Martyn, Coulding, Martina, Jude, Edward, McCormick, Jacqueline, Mercer, Oliver, Potla, Darsh, Rehman, Hafiz, Savill, Heather, Turner, Victoria, Downes, Charlotte, Holding, Kathleen, Riches, Katie, Hilton, Mary, Hayman, Mel, Subramanian, Deepak, Daniel, Priya, Adanini, Oluronke, Bhatia, Nikhil, Msiska, Maines, Collins, Rebecca, Clement, Ian, Patel, Bijal, Gulati, A., Hays, Carole, Webster, K., Hudson, Anne, Webster, Andrea, Stephenson, Elaine, McCormack, Louise, Slater, Victoria, Nixon, Rachel, Hanson, Helen, Fearby, Maggie, Kelly, Sinead, Bridgett, Victoria, Robinson, Philip, Camsooksai, Julie, Humphrey, Charlotte, Jenkins, Sarah, Reschreiter, Henrik, Wadams, Beverley, Death, Yasmin, Bastion, Victoria, Clarke, Daphene, David, Beena, Kent, Harriet, Lorusso, Rachel, Lubimbi, Gamu, Murdoch, Sophie, Penacerrada, Melchizedek, Thomas, Alastair, Valentine, Jennifer, Vochin, Ana, Wulandari, Retno, Djeugam, Brice, Bell, Gillian, English, Katy, Katary, Amro, Wilcox, Louise, Bruce, Michelle, Connolly, Karen, Duncan, Tracy, T-Michael, Helen, Lindergard, Gabriella, Hey, Samuel, Fox, Claire, Alfonso, Jordan, Durrans, Laura Jayne, Guerin, Jacinta, Blackledge, Bethan, Harris, Jade, Hruska, Martin, Eltayeb, Ayaa, Lamb, Thomas, Hodgkiss, Tracey, Cooper, Lisa, Rothwell, Joanne, Allan, Angela, Anderson, Felicity, Kaye, Callum, Liew, Jade, Medhora, Jasmine, Scott, Teresa, Trumper, Erin, Botello, Adriana, Lankester, Liana, Nikitas, Nikitas, Wells, Colin, Stowe, Bethan, Spencer, Kayleigh, Brandwood, Craig, Smith, Lara, Birchall, Katie, Kolakaluri, Laurel, Baines, Deborah, Sukumaran, Anila, Apetri, Elena, Basikolo, Cathrine, Catlow, Laura, Charles, Bethan, Dark, Paul, Doonan, Reece, Harvey, Alice, Horner, Daniel, Knowles, Karen, Lee, Stephanie, Lomas, Diane, Lyons, Chloe, Marsden, Tracy, McLaughlan, Danielle, McMorrow, Liam, Pendlebury, Jessica, Perez, Jane, Poulaka, Maria, Proudfoot, Nicola, Slaughter, Melanie, Slevin, Kathryn, Thomas, Vicky, Walker, Danielle, Michael, Angiy, Collis, Matthew, Cosier, Tracey, Millen, Gemma, Richardson, Neil, Schumacher, Natasha, Weston, Heather, Rand, James, Baxter, Nicola, Henderson, Steven, Kennedy-Hay, Sophie, McParland, Christopher, Rooney, Laura, Sim, Malcolm, McCreath, Gordan, Akeroyd, Louise, Bano, Shereen, Bromley, Matt, Gurr, Lucy, Lawton, Tom, Morgan, James, Sellick, Kirsten, Warren, Deborah, Wilkinson, Brian, McGowan, Janet, Ledgard, Camilla, Stacey, Amelia, Pye, Kate, Bellwood, Ruth, Bentley, Michael, Bewley, Jeremy, Garland, Zoe, Grimmer, Lisa, Gumbrill, Bethany, Johnson, Rebekah, Sweet, Katie, Webster, Denise, Efford, Georgia, Convery, Karen, Fottrell-Gould, Deirdre, Hudig, Lisa, Keshet-Price, Jocelyn, Randell, Georgina, Stammers, Katie, Bokhari, Maria, Linnett, Vanessa, Lucas, Rachael, McCormick, Wendy, Ritzema, Jenny, Sanderson, Amanda, Wild, Helen, Rostron, Anthony, Roy, Alistair, Woods, Lindsey, Cornell, Sarah, Wakinshaw, Fiona, Rogerson, Kimberley, Jarmain, Jordan, Parker, Robert, Reddy, Amie, Turner-Bone, Ian, Wilding, Laura, Harding, Peter, Abernathy, Caroline, Foster, Louise, Gratrix, Andrew, Martinson, Vicky, Parkinson, Priyai, Stones, Elizabeth, Carbral-Ortega, Llucia, Bercades, Georgia, Brealey, David, Hass, Ingrid, MacCallum, Niall, Martir, Gladys, Raith, Eamon, Reyes, Anna, Smyth, Deborah, Zitter, Letizia, Benyon, Sarah, Marriott, Suzie, Park, Linda, Keenan, Samantha, Gordon, Elizabeth, Quinn, Helen, Baines, Kizzy, Cagova, Lenka, Fofano, Adama, Garner, Lucie, Holcombe, Helen, Mepham, Sue, Mitchell, Alice Michael, Mwaura, Lucy, Praman, Krithivasan, Vuylsteke, Alain, Zamikula, Julie, Purewal, Bally, Rivers, Vanessa, Bell, Stephanie, Blakemore, Hayley, Borislavova, Borislava, Faulkner, Beverley, Gendall, Emma, Goff, Elizabeth, Hayes, Kati, Thomas, Matt, Worner, Ruth, Smith, Kerry, Stephens, Deanna, Mew, Louise, Mwaura, Esther, Stewart, Richard, Williams, Felicity, Wren, Lynn, Sutherland, Sara-Beth, Bevan, Emily, Martin, Jane, Trodd, Dawn, Watson, Geoff, Brown, Caroline Wrey, Collins, Amy, Khaliq, Waqas, Gude, Estefania Treus, Akinkugbe, Olugbenga, Bamford, Alasdair, Beech, Emily, Belfield, Holly, Bell, Michael, Davies, Charlene, Jones, Gareth A.L., McHugh, Tara, Meghari, Hamza, O'Neill, Lauran, Peters, Mark J., Ray, Samiran, Tomas, Ana Luisa, Burn, Iona, Hambrook, Geraldine, Manso, Katarina, Penn, Ruth, Shanmugasundaram, Pradeep, Tebbutt, Julie, Thornton, Danielle, Cole, Jade, Davies, Rhys, Duffin, Donna, Hill, Helen, Player, Ben, Thomas, Emma, Williams, Angharad, Griffin, Denise, Muchenje, Nycola, Mupudzi, Mcdonald, Partridge, Richard, Conyngham, Jo-Anna, Thomas, Rachel, Wright, Mary, Corral, Maria Alvarez, Jacob, Reni, Jones, Cathy, Denmade, Craig, Beavis, Sarah, Dale, Katie, Gascoyne, Rachel, Hawes, Joanne, Pritchard, Kelly, Stevenson, Lesley, Whileman, Amanda, Doble, Patricia, Hutter, Joanne, Pawley, Corinne, Shovelton, Charmaine, Vaida, Marius, Butcher, Deborah, O'Sullivan, Susie, Butterworth-Cowin, Nicola, Ahmad, Norfaizan, Barker, Joann, Bauchmuller, Kris, Bird, Sarah, Cawthron, Kay, Harrington, Kate, Jackson, Yvonne, Kibutu, Faith, Lenagh, Becky, Masuko, Shamiso, Mills, Gary H., Raithatha, Ajay, Wiles, Matthew, Willson, Jayne, Newell, Helen, Lye, Alison, Nwafor, Lorenza, Jarman, Claire, Rowland-Jones, Sarah, Foote, David, Cole, Joby, Thompson, Roger, Watson, James, Hesseldon, Lisa, Macharia, Irene, Chetam, Luke, Smith, Jacqui, Ford, Amber, Anderson, Samantha, Birchall, Kathryn, Housley, Kay, Walker, Sara, Milner, Leanne, Hanratty, Helena, Trower, Helen, Phillips, Patrick, Oxspring, Simon, Donne, Ben, Jardine, Catherine, Williams, Dewi, Hay, Alasdair, Flanagan, Rebecca, Hughes, Gareth, Latham, Scott, McKenna, Emma, Anderson, Jennifer, Hull, Robert, Rhead, Kat, Cruz, Carina, Pattison, Natalie, Charnock, Rob, McFarland, Denise, Cosgrove, Denise, Ahmed, Ashar, Morris, Anna, Jakkula, Srinivas, Ali, Asifa, Brady, Megan, Dale, Sam, Dance, Annalisa, Gledhill, Lisa, Greig, Jill, Hanson, Kathryn, Holdroyd, Kelly, Home, Marie, Kelly, Diane, Kitson, Ross, Matapure, Lear, Melia, Deborah, Mellor, Samantha, Nortcliffe, Tonicha, Pinnell, Jez, Robinson, Matthew, Shaw, Lisa, Shaw, Ryan, Thomis, Lesley, Wilson, Alison, Wood, Tracy, Bayo, Lee-Ann, Merwaha, Ekta, Ishaq, Tahira, Hanley, Sarah, Hibbert, Meg, Tetla, Dariusz, Woodford, Chrsitopher, Durga, Latha, Kennard-Holden, Gareth, Branney, Debbie, Frankham, Jordan, Pitts, Sally, White, Nigel, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Altabaibeh, Abdelhakim, Alvaro, Ana, Gilbert, Kayleigh, Ma, Louise, Mostoles, Loreta, Parmar, Chetan, Simpson, Kathryn, Jetha, Champa, Booker, Lauren, Pratley, Anezka, Adams, Colene, Agasou, Anita, Arden, Tracie, Bowes, Amy, Boyle, Pauline, Beekes, Mandy, Button, Heather, Capps, Nigel, Carnahan, Mandy, Carter, Anne, Childs, Danielle, Donaldson, Denise, Hard, Kelly, Hurford, Fran, Hussain, Yasmin, Javaid, Ayesha, Jones, James, Jose, Sanal, Leigh, Michael, Martin, Terry, Millward, Helen, Motherwell, Nichola, Rikunenko, Rachel, Stickley, Jo, Summers, Julie, Ting, Louise, Tivenan, Helen, Tonks, Louise, Wilcox, Rebecca, Holland, Maureen, Keenan, Natalie, Lyons, Marc, Wassall, Helen, Marsh, Chris, Mahenthran, Mervin, Carter, Emma, Kong, Thomas, Blackman, Helen, Creagh-Brown, Ben, Donlon, Sinead, Michalak-Glinska, Natalia, Mtuwa, Sheila, Pristopan, Veronika, Salberg, Armorel, Smith, Eleanor, Stone, Sarah, Piercy, Charles, Verula, Jerik, Burda, Dorota, Montaser, Rugia, Harden, Lesley, Mayangao, Irving, Marriott, Cheryl, Bradley, Paul, Harris, Celia, Anderson, Susan, Andrews, Eleanor, Birch, Janine, Collins, Emma, Hammerton, Kate, O'Leary, Ryan, Clark, Michele, Purvis, Sarah, Barber, Russell, Hewitt, Claire, Hilldrith, Annette, Jackson-Lawrence, Karen, Shepardson, Sarah, Wills, Maryanne, Butler, Susan, Tavares, Silvia, Cunningham, Amy, Hindale, Julia, Arif, Sarwat, Bean, Sarah, Burt, Karen, Spivey, Michael, Demetriou, Carrie, Eckbad, Charlotte, Hierons, Sarah, Howie, Lucy, Mitchard, Sarah, Ramos, Lidia, Serrano-Ruiz, Alfredo, White, Katie, Kelly, Fiona, Cristiano, Daniele, Dormand, Natalie, Farzad, Zohreh, Gummadi, Mahitha, Liyanage, Kamal, Patel, Brijesh, Salmi, Sara, Sloane, Geraldine, Thwaites, Vicky, Varghese, Mathew, Zborowski, Anelise C., Allan, John, Geary, Tim, Houston, Gordon, Meikle, Alistair, O'Brien, Peter, Forsey, Miranda, Kaliappan, Agilan, Nicholson, Anne, Riches, Joanne, Vertue, Mark, Allan, Elizabeth, Darlington, Kate, Davies, Ffyon, Easton, Jack, Kumar, Sumit, Lean, Richard, Menzies, Daniel, Pugh, Richard, Qiu, Xinyi, Davies, Llinos, Williams, Hannah, Scanlon, Jeremy, Davies, Gwyneth, Mackay, Callum, Lewis, Joannne, Rees, Stephanie, Oblak, Metod, Popescu, Monica, Thankachen, Mini, Higham, Andrew, Simpson, Kerry, Craig, Jayne, Baruah, Rosie, Morris, Sheila, Ferguson, Susie, Shepherd, Amy, Prockter Moore, Luke Stephen, Vizcaychipi, Marcela Paola, Gomes de Almeida Martins, Laura, Carungcong, Jaime, Mohamed Ali, Inthakab Ali, Beaumont, Karen, Blunt, Mark, Coton, Zoe, Curgenven, Hollie, Elsaadany, Mohamed, Fernandes, Kay, Ally, Sameena Mohamed, Rangarajan, Harini, Sarathy, Varun, Selvanayagam, Sivarupan, Vedage, Dave, White, Matthew, Gill, Mandy, Paul, Paul, Ratnam, Valli, Shelton, Sarah, Wynter, Inez, Carmody, Siobhain, Page, Valerie Joan, Beith, Claire Marie, Black, Karen, Clements, Suzanne, Morrison, Alan, Strachan, Dominic, Taylor, Margaret, Clarkson, Michelle, D'Sylva, Stuart, Norman, Kathryn, Auld, Fiona, Donnachie, Joanne, Edmond, Ian, Prentice, Lynn, Runciman, Nikole, Salutous, Dario, Symon, Lesley, Todd, Anne, Turner, Patricia, Short, Abigail, Sweeney, Laura, Murdoch, Euan, Senaratne, Dhaneesha, Hill, Michaela, Kannan, Thogulava, Laura, Wild, Crawley, Rikki, Crew, Abigail, Cunningham, Mishell, Daniels, Allison, Harrison, Laura, Hope, Susan, Inweregbu, Ken, Jones, Sian, Lancaster, Nicola, Matthews, Jamie, Nicholson, Alice, Wray, Gemma, Langton, Helen, Prout, Rachel, Watters, Malcolm, Novis, Catherine, Barron, Anthony, Collins, Ciara, Kaul, Sundeep, Passmore, Heather, Prendergast, Claire, Reed, Anna, Rogers, Paula, Shokkar, Rajvinder, Woodruff, Meriel, Middleton, Hayley, Polgar, Oliver, Nolan, Claire, Mahay, Kanta, Collier, Dawn, Hormis, Anil, Maynard, Victoria, Graham, Cheryl, Walker, Rachel, Knights, Ellen, Price, Alicia, Thomas, Alice, Thorpe, Chris, Behan, Teresa, Burnett, Caroline, Hatton, Jonathan, Heeney, Elaine, Mitra, Atideb, Newton, Maria, Pollard, Rachel, Stead, Rachael, Amin, Vishal, Anastasescu, Elena, Anumakonda, Vikram, Karthik, Komala, Kausar, Rizwana, Reid, Karen, Smith, Jacqueline, Imeson-Wood, Janet, Skinner, Denise, Gaylard, Jane, Mullan, Dee, Newman, Julie, Brown, Alison, Crickmore, Vikki, Debreceni, Gabor, Wilkins, Joy, Nicol, Liz, Reece-Anthony, Rosie, Birt, Mark, Ghosh, Alison, Williams, Emma, Allen, Louise, Beranova, Eva, Crisp, Nikki, Deery, Joanne, Hazelton, Tracy, Knight, Alicia, Price, Carly, Tilbey, Sorrell, Turki, Salah, Turney, Sharon, Cooper, Joshua, Finch, Cheryl, Liderth, Sarah, Quinn, Alison, Waddington, Natalia, Coventry, Tina, Fowler, Susan, MacMahon, Michael, McGregor, Amanda, Cowley, Anne, Highgate, Judith, Gregory, Jane, O'Connell, Susan, Smith, Tim, Barberis, Luigi, Gopal, Shameer, Harris, Nichola, Lake, Victoria, Metherell, Stella, Radford, Elizabeth, Daniel, Amelia, Finn, Joanne, Saha, Rajnish, White, Nikki, Donnison, Phil, Trim, Fiona, Eapen, Beena, Birch, Jenny, Bough, Laura, Goodsell, Josie, Tutton, Rebecca, Williams, Patricia, Williams, Sarah, Winter-Goodwin, Barbara, Nichol, Ailstair, Brickell, Kathy, Smyth, Michelle, Murphy, Lorna, Coetzee, Samantha, Gales, Alistair, Otahal, Igor, Raj, Meena, Sell, Craig, Hilltout, Paula, Evitts, Jayne, Tyler, Amanda, Waldron, Joanne, Beesley, Kate, Board, Sarah, Kubisz-Pudelko, Agnieszka, Lewis, Alison, Perry, Jess, Pippard, Lucy, Wood, Di, Buckley, Clare, Barry, Peter, Flint, Neil, Rekha, Patel, Hales, Dawn, Bunni, Lara, Jennings, Claire, Latif, Monica, Marshall, Rebecca, Subramanian, Gayathri, McGuigan, Peter J., Wasson, Christopher, Finn, Stephanie, Green, Jackie, Collins, Erin, King, Bernadette, Campbell, Andy, Smuts, Sara, Duffield, Joseph, Smith, Oliver, Mallon, Lewis, Claire, Watkins, Botfield, Liam, Butler, Joanna, Dexter, Catherine, Fletcher, Jo, Garg, Atul, Kuravi, Aditya, Ranga, Poonam, Virgilio, Emma, Belagodu, Zakaula, Fuller, Bridget, Gherman, Anca, Olufuwa, Olumide, Paramsothy, Remi, Stuart, Carmel, Oakley, Naomi, Kamundi, Charlotte, Tyl, David, Collins, Katy, Silva, Pedro, Taylor, June, King, Laura, Coates, Charlotte, Crowley, Maria, Wakefield, Phillipa, Beadle, Jane, Johnson, Laura, Sargeant, Janet, Anderson, Madeleine, Brady, Ailbhe, Chan, Rebekah, Little, Jeff, McIvor, Shane, Prady, Helena, Whittle, Helen, Mathew, Bijoy, Attwood, Ben, Parsons, Penny, Ward, Geraldine, Bremmer, Pamela, Joe, West, Tracy, Baird, Jim, Ruddy, Davies, Ellie, Sathe, Sonia, Dennis, Catherine, McGregor, Alastair, Parris, Victoria, Srikaran, Sinduya, Sukha, Anisha, Clarke, Noreen, Whiteside, Jonathan, Mascarenhas, Mairi, Donaldson, Avril, Matheson, Joanna, Barrett, Fiona, O'Hara, Marianne, Okeefe, Laura, Bradley, Clare, Eastgate-Jackson, Christine, Filipe, Helder, Martin, Daniel, Maharajh, Amitaa, Garcia, Sara Mingo, Pakou, Glykeria, De Neef, Mark, Dent, Kathy, Horsley, Elizabeth, Akhtar, Muhmmad Nauman, Pearson, Sandra, Potoczna, Dorota, Spencer, Sue, Clapham, Melanie, Harper, Rosemary, Poultney, Una, Rice, Polly, Mutch, Rachel, Armstrong, Lisa, Bates, Hayley, Dooks, Emma, Farquhar, Fiona, Hairsine, Brigid, McParland, Chantal, Packham, Sophie, Bi, Rehana, Scholefield, Barney, Ashton, Lydia, George, Linsha, Twiss, Sophie, Wright, David, Chablani, Manish, Kirkby, Amy, Netherton, Kimberley, Davies, Kim, O'Brien, Linda, Omar, Zohra, Perkins, Emma, Lewis, Tracy, Sutherland, Isobel, Burns, Karen, Ben Chandler, Dr, Elliott, Kerry, Mallinson, Janine, Turnbull, Alison, Gondo, Prisca, Hadebe, Bernard, Kayani, Abdul, Masunda, Bridgett, Anderson, Taya, Hawcutt, Dan, O'Malley, Laura, Rad, Laura, Rogers, Naomi, Saunderson, Paula, Allison, Kathryn Sian, Afolabi, Deborah, Whitbread, Jennifer, Jones, Dawn, Dore, Rachael, Halkes, Matthew, Mercer, Pauline, Thornton, Lorraine, Dawson, Joy, Garrioch, Sweyn, Tolson, Melanie, Aldridge, Jonathan, Kapoor, Ritoo, Loader, David, Castle, Karen, Humphreys, Sally, Tampsett, Ruth, Mackintosh, Katherine, Ayers, Amanda, Harrison, Wendy, North, Julie, Allibone, Suzanne, Genetu, Roman, Kasipandian, Vidya, Patel, Amit, Mac, Ainhi, Murphy, Anthony, Mahjoob, Parisa, Nazari, Roonak, Worsley, Lucy, Fagan, Andrew, Bemand, Thomas, Black, Ethel, Dela Rosa, Arnold, Howle, Ryan, Jhanji, Shaman, Baikady, Ravishankar Rao, Tatham, Kate Colette, Thomas, Benjamin, Bell, Dina, Boyle, Rosalind, Douglas, Katie, Glass, Lynn, Lee, Emma, Lennon, Liz, Rattray, Austin, Taylor, Abigail, Hughes, Rachel Anne, Thomas, Helen, Rees, Alun, Duskova, Michaela, Phipps, Janet, Brooks, Suzanne, Edwards, Michelle, Quaid, Sheena, Watson, Ekaterina, Brayne, Adam, Fisher, Emma, Hunt, Jane, Jackson, Peter, Kaye, Duncan, Love, Nicholas, Parkin, Juliet, Tuckey, Victoria, Van Koutrik, Lynne, Carter, Sasha, Andrew, Benedict, Findlay, Louise, Adams, Katie, Service, Jen, Williams, Alison, Cheyne, Claire, Saunderson, Anne, Moultrie, Sam, Odam, Miranda, Hall, Kathryn, Mapfunde, Isheunesu, Willis, Charlotte, Lyon, Alex, Sri-Chandana, Chunda, Scherewode, Joslan, Stephenson, Lorraine, Marsh, Sarah, Hardy, John, Houlden, Henry, Moncur, Eleanor, Tariq, Ambreen, Tucci, Arianna, Hobrok, Maria, Loosley, Ronda, McGuinness, Heather, Tench, Helen, Wolf-Roberts, Rebecca, Irvine, Val, Shelley, Benjamin, Gorman, Claire, Gupta, Abhinav, Timlick, Elizabeth, Brady, Rebecca, Milligan, Barry, Bellini, Arianna, Bryant, Jade, Mayer, Anton, Pickard, Amy, Roe, Nicholas, Sowter, Jason, Howlett, Alex, Fidler, Katy, Tagliavini, Emma, Donnelly, Kevin, Boos, Jannik, van der Made, Caspar I., Ramakrishnan, Gayatri, Coughlan, Eamon, Asselta, Rosanna, Löscher, Britt-Sabina, Valenti, Luca V.C., de Cid, Rafael, Bujanda, Luis, Julià, Antonio, Pairo-Castineira, Erola, May, Sandra, Zametica, Berina, Heggemann, Julia, Albillos, Agustín, Banales, Jesus M., Barretina, Jordi, Blay, Natalia, Bonfanti, Paolo, Buti, Maria, Fernandez, Javier, Marsal, Sara, Prati, Daniele, Ronzoni, Luisa, Sacchi, Nicoletta, Schultze, Joachim L., Riess, Olaf, Franke, Andre, Rawlik, Konrad, Ellinghaus, David, Hoischen, Alexander, Schmidt, Axel, and Ludwig, Kerstin U.
Published: 2024
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35. Zn-Cu bimetallic gas diffusion electrodes for electrochemical reduction of CO2 to ethylene

Author: Suliman, Munzir H., Al Naji, Hussain, and Usman, Muhammad
Published: 2024
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36. Technology Application in Halal Logistics

Author: Zaharah Wan-Chik, Rita, primary, Munzir Khairuddin, Muhamad, additional, and Abdul Rahman, Nor Aida, additional
Published: 2023
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37. Technology Adoption in the Halal Industry

Author: Khairuddin, Muhamad Munzir bin, primary and Rahman, Nor Aida Abdul, additional
Published: 2023
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38. Automatic Anti-Swing Gantry Crane Based on Gradient Descent Optimization Proportional Integrated Derivative (PID): A Comparison Simulation and Real Experiment.

Author: Munzir Qadri, Danang Karuna Harjanto, Jonathan Miharja, Winda Astuti, Yosica Mariana, Sofyan Tan, and Mahmud Iwan Solihin
Published: 2023
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39. Analysis of Knocking Potential Based on Vibration on a Gasoline Engine for Pertalite and Pertamax Turbo Using Signal Processing Methods

Author: Qadri, Munzir, Astuti, Winda, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Mukhopadhyay, Subhas Chandra, editor, Senanayake, S.M. Namal Arosha, editor, and Withana, P.W. Chandana, editor
Published: 2023
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40. CO2 Conversion via Catalytic Hydrogenation to Methanol, DME and Syngas

Author: Usman, Muhammad, Garba, Mustapha D., Zeb, Zonish, Israr, Muhammad, Safia, Safia, Javed, Fatima, Suliman, Munzir S., Alfaify, Bandar, Sanhoob, Mohammed A., Iqbal, Naseem, Humayun, Muhammad, Helal, Aasif, Jawaid, Mohammad, Series Editor, and Khan, Anish, Series Editor
Published: 2023
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41. Profiling the Research Landscape of Air Travel

Author: Munzir bin Khairuddin, Muhamad, primary and Abdul Rahman, Nor Aida, additional
Published: 2023
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42. Adult appendicitis score versus Alvarado score: A comparative study in the diagnosis of acute appendicitis

Author: Ghali, Mohamed Said, Hasan, Samer, Al-Yahri, Omer, Mansor, Salah, Al-Tarakji, Mohannad, Obaid, Munzir, Shah, Amjad Ali, Shehata, Mona S., Singh, Rajvir, Al-Zoubi, Raed M., and Zarour, Ahmad
Published: 2023
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43. Effect of Evotherm 3G on the performance of asphalt mixture

Author: Abdullah Zawawi, Munzir, Abdul Hassan, Norhidayah, Mahmud, Mohd Zul Hanif, Putra Jaya, Ramadhansyah, and Mohamed, Azman
Published: 2023
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44. One step fabrication of nanostructured nickel thin films on porous nickel foam for drastic electrocatalytic oxygen evolution

Author: Ehsan, Muhammad Ali, Ullah, Zaka, Nazar, Muhammad Faizan, Younas, Muhammad, and Suliman, Munzir
Published: 2023
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45. Growth of ultrathin nanosheets of nickel iron layered double hydroxide for the oxygen evolution reaction

Author: Suliman, Munzir, Al Ghamdi, Abdullah, Baroud, Turki, Drmosh, Qasem, Rafatullah, Mohd, Yamani, Zain, and Qamar, Mohammad
Published: 2022
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46. A review of metal-organic frameworks/graphitic carbon nitride composites for solar-driven green H2 production, CO2 reduction, and water purification

Author: Usman, Muhammad, Zeb, Zonish, Ullah, Habib, Suliman, Munzir H., Humayun, Muhammad, Ullah, Latif, Shah, Syed Niaz Ali, Ahmed, Usama, and Saeed, Muhammad
Published: 2022
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47. Diversity-sensitive measures in German hospitals – attitudes, implementation, and barriers according to administration managers

Author: Erdsiek, Fabian, Aksakal, Tuğba, Mader, Maria, Idris, Munzir, Yılmaz-Aslan, Yüce, Razum, Oliver, and Brzoska, Patrick
Published: 2022
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48. Metastatic gastroesophageal cancer in older patients – is this patient cohort represented in clinical trials?

Author: Hennessy, Maeve A., Hamid, Munzir, Keegan, Niamh M., Corrigan, Lynda, Goggin, Caitriona, Oo, Nay Myo, Carrigan, Marie, Mockler, David, O’Donovan, Anita, and Horgan, Anne M.
Published: 2022
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49. Facile Synthesis of Porous Zinc Nanosheets for Highly Selective Electrochemical CO2 Reduction to CO.

Author: Mahyoub, Samah A., Drmosh, Husam Q., Qaraah, Fahim A., Suliman, Munzir, Al‐Fadhil, Danah A., and Drmosh, Qasem A.
Subjects: ZINC catalysts, CLEAN energy, CARBON emissions, CATALYTIC activity, POWER resources, ELECTROLYTIC reduction
Abstract: With the increasing levels of CO2 emissions and the decreasing availability of energy resources, the electrocatalytic CO2 reduction reaction (CO2RR) offers a promising method for utilizing CO2 as a valuable resource using sustainable electrical energy. However, developing cost‐effective and highly efficient catalysts remains a significant challenge. Although zinc, an abundant element on Earth, has shown potential for converting CO2 into CO, its effectiveness as a catalyst for CO2 reduction is hindered by its low selectivity and stability. This study introduces a fast, efficient, and simple electrochemical deposition method for preparing porous zinc nanosheets (NS) using the hydrogen bubble template approach. The as‐prepared zinc NS catalyst demonstrates exceptional catalytic activity due to its highly porous structure and high specific surface area. At a voltage of −1 V versus RHE, it achieves a maximum CO Faradaic efficiency of 89.5 %. The performance of this system is characterized by a partial current density of around −6.17 mA cm−2 in an H‐cell configuration. Additionally, our catalyst exhibits remarkable durability over 10 h, highlighting its significant potential for real‐world utilization in CO2RR. [ABSTRACT FROM AUTHOR]
Published: 2024
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50. sBERT: Parameter-Efficient Transformer-Based Deep Learning Model for Scientific Literature Classification.

Author: Ahanger, Mohammad Munzir, Wani, Mohd Arif, and Palade, Vasile
Subjects: LANGUAGE models, SCIENTIFIC literature, SCIENCE education, MACHINE learning, DEEP learning
Abstract: This paper introduces a parameter-efficient transformer-based model designed for scientific literature classification. By optimizing the transformer architecture, the proposed model significantly reduces memory usage, training time, inference time, and the carbon footprint associated with large language models. The proposed approach is evaluated against various deep learning models and demonstrates superior performance in classifying scientific literature. Comprehensive experiments conducted on datasets from Web of Science, ArXiv, Nature, Springer, and Wiley reveal that the proposed model's multi-headed attention mechanism and enhanced embeddings contribute to its high accuracy and efficiency, making it a robust solution for text classification tasks. [ABSTRACT FROM AUTHOR]
Published: 2024
Full Text: View/download PDF

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