Improving transmembrane protein prediction analysis using machine learning by Kazemian, Hassan

“…This research is concerned with applications of artificial intelligence to amino acid sequences using the conventional alphabetical representation to predict alpha-helices and beta barrels transmembrane regions. …”
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Cerebral mechanisms for different second language writing systems. by Koyama, MS, Stein, J, Stoodley, C, Hansen, P

“…This additional activation is likely to reflect the lower level of visual familiarity to the L2 symbols in the English-L1/Japanese-L2 group; Kana symbols are uniquely used only in Japan, whereas Roman alphabetic symbols are seen nearly everywhere. These findings, bolstered by significant relationships between the activation of the identified regions and cognitive competence, suggest that the cerebral mechanisms for L2 reading in late learners depends both on which language is their L1 and which language is to be learnt as their L2. …”

Unpacking faculty development in Japan: an ethnography of faculty development practitioners by Machi, S, Machi Sato

“…‘<em>Tantōsha</em>’ literally means the person in charge and it is relatively 7 neutral label to describe the position. Second, alphabetically written ‘<em>FD</em>’ prevents the evolution of the concept. …”

Miscellany/Mélanges

“…Nablow, Voltaire's indebtedness to Addison in the alphabetical works <br/> Alexander Jovicevich, Voltaire and La Harpe - l'affaire des manuscrits: a reappraisal <br/> G. …”

A survey on computer password practices among medical undergraduate students at Faculty of Medicine, National University of Malaysia by M T Azmi, M T Emran

“…The questionnaire also explored the users’ password combination style, whether they used numbers only or combination of numbers and alphabets or some other pattern. A total of 39.1% used letters only but 27.6% used combination of numbers only which is less secure. …”
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Where Malay politeness is not apparent: A study of front counter staff interactions in Malaysian public hospitals by Kuang, C.H., Lau, S.K., Ang, P.S., David, M.K.

“…Spoken data were manually recorded and then transcribed into Roman alphabets for analysis and Brown and Levinson's (1987) politeness theory was adapted into The Malaysian context of politeness. …”
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Antioxidant research in Asia in the period from 2000-2008. by R.R., Hafidh, Abdulamir, Ahmed Sahib, Abu Bakar, Fatimah, Abas, Faridah, Jahanshiri, Fatemeh, Sekawi, Zamberi

“…The gathered data had been arranged alphabetically in a table depending on the plant's scientific name, common name, the used part(s) and the family name. …”
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Implementation of a machine learning algorithm for sentiment analysis of Indonesia’s 2019 presidential election by Buntoro, G. A., Arifin, R., Syaifuddiin, G. N., Selamat, A., Krejcar, O., Hamido, F.

“…This research proved that the combination of the SVM machine learning algorithm and alphabetic tokenization produced the highest accuracy value of 79.02%. …”
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Implementation of a machine learning algorithm for sentiment analysis of Indonesia‘s 2019 Presidential election by Buntoro, Ghulam Asrofi, Arifin, Rizal, Syaifuddiin, Gus Nanang, Selamat, Ali, Krejcar, Ondrej, Fujita, Hamido

“…This research proved that the combination of the SVM machine learning algorithm and alphabetic tokenization produced the highest accuracy value of 79.02%. …”
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Older adults benefit from more widespread brain network integration during working memory by C.A. Crowell, S.W. Davis, L. Beynel, L. Deng, D. Lakhlani, S.A. Hilbig, H. Palmer, A. Brito, A.V. Peterchev, B. Luber, S.H. Lisanby, L.G. Appelbaum, R. Cabeza

“…Here, individuals performed a WM task in which they held letters online while reordering them alphabetically. WM load was titrated to obtain four individualized difficulty levels with different set sizes. …”
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Letter and Speech Sound Association in Emerging Readers With Familial Risk of Dyslexia by Joanna Plewko, Katarzyna Chyl, Łukasz Bola, Łukasz Bola, Magdalena Łuniewska, Magdalena Łuniewska, Agnieszka Dębska, Anna Banaszkiewicz, Marek Wypych, Artur Marchewka, Nienke van Atteveldt, Katarzyna Jednoróg

“…In alphabetic scripts, learning letter-sound (LS) association (i.e., letter knowledge) is a strong predictor of later reading skills. …”
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Effect of the stimulation of Two-point discrimination sensation on Brailles’ writing and reading skills in blind children by Supaporn Chinchai, Wichita Kesaraksha, Siriporn Wongrujipairoj, Soisuda Vittayakorn

“…The instruments used were the Disk criminator and the Test of Braille Alphabets. Data were collected at before and after sensory re-education program. …”
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Network‐based rTMS to modulate working memory: The difficult choice of effective parameters for online interventions by Lysianne Beynel, Moritz Dannhauer, Hannah Palmer, Susan A. Hilbig, Courtney A. Crowell, Joyce E‐H. Wang, Andrew M. Michael, Eleanor A. Wood, Bruce Luber, Sarah H. Lisanby, Angel V. Peterchev, Roberto Cabeza, Simon W. Davis, Lawrence G. Appelbaum

“…Methods Twenty‐nine subjects completed a 4‐day protocol, in which active or sham 5Hz rTMS was applied over the DLPFC and LPC in separate blocks of trials while participants performed tasks that required either maintenance alone, or both maintenance and manipulation (alphabetization) of information. Stimulation targets were defined individually based on fMRI activation and structural network properties. …”
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Differences and Similarities in the Contributions of Phonological Awareness, Orthographic Knowledge and Semantic Competence to Reading Fluency in Chinese School-Age Children With a... by Linjun Zhang, Tian Hong, Yu Li, Jiuju Wang, Jiuju Wang, Yang Zhang, Hua Shu

“…Compared with the large number of studies on reading of children with hearing loss (HL) in alphabetic languages, there are only a very limited number of studies on reading of Chinese-speaking children with HL. …”
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Gesture-to-Text Translation Using SURF for Indian Sign Language by Kaustubh Mani Tripathi, Pooja Kamat, Shruti Patil, Ruchi Jayaswal, Swati Ahirrao, Ketan Kotecha

“…The study uses a dataset of 42,000 photographs consisting of alphabets (A–Z) and numbers (1–9), divided into 35 classes with 1200 shots per class. …”
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Enhancement of COPD biological networks using a web-based collaboration interface [v2; ref status: indexed, http://f1000r.es/5ew] by The sbv IMPROVER project team (in alphabetical order), Stephanie Boue, Brett Fields, Julia Hoeng, Jennifer Park, Manuel C. Peitsch, Walter K. Schlage, Marja Talikka, The Challenge Best Performers (in alphabetical order), Ilona Binenbaum, Vladimir Bondarenko, Oleg V. Bulgakov, Vera Cherkasova, Norberto Diaz-Diaz, Larisa Fedorova, Svetlana Guryanova, Julia Guzova, Galina Igorevna Koroleva, Elena Kozhemyakina, Rahul Kumar, Noa Lavid, Qingxian Lu, Swapna Menon, Yael Ouliel, Samantha C. Peterson, Alexander Prokhorov, Edward Sanders, Sarah Schrier, Golan Schwaitzer Neta, Irina Shvydchenko, Aravind Tallam, Gema Villa-Fombuena, John Wu, Ilya Yudkevich, Mariya Zelikman

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MIDV-2020: a comprehensive benchmark dataset for identity document analysis by K.B. Bulatov, E.V. Emelianova, D.V. Tropin, N.S. Skoryukina, Y.S. Chernyshova, A.V. Sheshkus, S.A. Usilin, Z. Ming, J.-C. Burie, M.M. Luqman, V.V. Arlazarov

“…For the task of document text field recognition, the Tesseract system was evaluated on field and character levels with grouping by field alphabets and document types. For the task of face detection, the performance of Multi Task Cascaded Convolutional Neural Networks-based method was evaluated separately for different types of image input modes. …”
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AGRAMP: machine learning models for predicting antimicrobial peptides against phytopathogenic bacteria by Jonathan Shao, Jonathan Shao, Yan Zhao, Wei Wei, Iosif I. Vaisman

“…To address these limitations, this study presents a bioinformatics approach utilizing machine learning models for predicting and selecting AMPs active against plant pathogenic bacteria.MethodsN-gram representations of peptide sequences with 3-letter and 9-letter reduced amino acid alphabets were used to capture the sequence patterns and motifs that contribute to the antimicrobial activity of AMPs. …”
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Synapses, predictions, and prediction errors: A neocortical computational study of MDD using the temporal memory algorithm of HTM by Mohamed A. Sherif, Mostafa Z. Khalil, Rammohan Shukla, Joshua C. Brown, Linda L. Carpenter

“…TM exhibits neocortical biological features such as sparse firing and continuous online learning using local Hebbian-learning rules.MethodsWe trained a TM model on random sequences of upper-case alphabetical letters, representing sequences of affective states. …”
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Length–weight relations of 44 fish species (Actinopterygii) inhabiting an unprotected tropical coastal biological corridor of Yucatan, Mexico by María Eugenia Vega-Cendejas, Mirella Hernández de Santillana, Sonia Palacios-Sánchez

“…The following species were studied (in alphabetical order): Acanthostracion quadricornis (Linnaeus, 1758); Albula vulpes (Linnaeus, 1758); Anchoa hepsetus (Linnaeus, 1758); Anchoa lamprotaenia Hildebrand, 1943, Anchoa lyolepis (Evermann et Marsh, 1900), Anchoa mitchilli (Valenciennes, 1848); Archosargus rhomboidalis (Linnaeus, 1758); Ariopsis felis (Linnaeus, 1766); Bagre marinus (Mitchill, 1815); Bairdiella chrysoura (Lacepède, 1802); Caranx latus Agassiz, 1831; Chaetodipterus faber (Broussonet, 1782); Chriodorus atherinoides Goode et Bean, 1882; Cynoscion arenarius Ginsburg, 1930; Elops saurus Linnaeus, 1766; Eucinostomus argenteus Baird et Girard, 1855; Eucinostomus gula (Quoy et Gaimard, 1824); Eucinostomus harengulus Goode et Bean, 1879; Harengula jaguana Poey, 1865; Hyporhamphus unifasciatus (Ranzani, 1841); Lagodon rhomboides (Linnaeus, 1766); Lutjanus griseus (Linnaeus, 1758); Menticirrhus americanus (Linnaeus, 1758); Menticirrhus littoralis (Holbrook, 1847); Menticirrhus saxatilis (Bloch et Schneider, 1801); Mugil curema Valenciennes, 1836; Mugil trichodon Poey, 1875; Oligoplites saurus (Bloch et Schneider, 1801); Opisthonema oglinum (Lesueur, 1818); Opsanus beta (Goode et Bean, 1880); Orthopristis chrysoptera (Linnaeus, 1766); Prionotus tribulus Cuvier, 1829; Rypticus maculatus Holbrook, 1855; Selene vomer (Linnaeus, 1758); Sphoeroides spengleri (Bloch, 1785); Sphoeroides testudineus (Linnaeus, 1758); Strongylura notata (Poey, 1860); Strongylura timucu (Walbaum, 1792); Symphurus plagiusa (Linnaeus, 1766); Synodus foetens (Linnaeus, 1766); Trachinotus carolinus (Linnaeus, 1766); Trachinotus falcatus (Linnaeus, 1758); Trachinotus goodei Jordan et Evermann, 1896; Urobatis jamaicensis (Cuvier, 1816). …”
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