Nursing professionalism and associated factors in Ethiopia: a systematic review and meta-analysis by Moges Tadesse Abebe, Agerie Mengistie Zeleke, Yeshiwas Ayale Ferede, Yosef Aragaw Gonete, Worku Chekol Tassew

“…Bachelor's degree and above educational status (POR: 1.80, CI: 1.38, 2.33), learning from government colleges (POR: 2.14, CI: 1.34, 3.42), better payment (POR: 1.85, CI: 1.16, 2.98), long years of work experience (POR: 2.15, CI: 1.73, 2.68), positive self-image (POR: 3.85, CI: 2.17, 6.84), job satisfaction (POR: 2.42, CI: 1.49, 3.95) and training opportunities (POR: 2.88, CI: 1.14, 7.32) were factors that determined higher levels of nursing professionalism in Ethiopia. …”
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Self-assessment of didactic performance of psychology and education professors in Mexico and Peru by Aldo Bazán-Ramírez, Walter Capa-Luque, Roberto Chávez-Nava, Mónica C. Dávila-Navarro, Homero Ango-Aguilar, Edmundo Hervias-Guerra, Catalina Bello-Vidal

“…Having an instrument that allows self-evaluation of teaching performance during didactic interactions will contribute to improving the quality of teaching and learning at the university level.ObjectivesThe validity and reliability evidence for the scores of the self-evaluation questionnaire of the teacher’s didactic performance are examined. …”
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Revolutionizing Civil Servant’s Work Behavior through Flexible Working Spaces: Digital Transformation &Green Practices at the Ministry of Finance by Puput Yanita Senja, Wahyu Dian Silviani, Rosana Eri Puspita

“…While the identified disadvantage is that the internet network is occasionally unstable, thus disrupting the learning and discussion processes. The civil servants at the Ministry of Finance had used several green practices before the pandemic began, such as saving water, saving electricity, and to some extent they had gone plasticless and paperless. …”
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How can competencies in minor surgery in general practice be increased? Assessing the effect of a compact intervention in postgraduate training: a mixed-methodsstudy by Joachim Szecsenyi, Jonas D Senft, Katja Krug, Simon Schwill, Aaron Poppleton, Dorothee Reith, Sandra Stengel

“…After 9 months, attendees remembered a variety of content and valued the interactive, case-oriented, peer-to-peer approach in a mixed learning group. Some attendees reported they had started to overcome competency gaps in minor surgery.Conclusions A compact intervention in minor surgery provides an ‘intense’ stimulus which could foster positive attitudes towards minor surgery and promote longitudinal personal development of related competencies in GP trainees, including those with little interest in surgery. …”
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Exploring cooking fuel choices among Ghanaian women of reproductive age: A socio-economic analysis from a statistical mechanics perspective. by Richard Kwame Ansah, Richard Kena Boadi, William Obeng-Denteh, Killian Asampana Asosega, Kassim Tawiah

“…Tailored communication strategies, peer-to-peer learning, and collaboration with local institutions are crucial for spreading awareness and encouraging the adoption of LPG.…”
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Angiotensin IV Receptors in the Rat Prefrontal Cortex: Neuronal Expression and NMDA Inhibition by Zsolt Tamás Papp, Polett Ribiczey, Erzsébet Kató, Zsuzsanna E. Tóth, Zoltán V. Varga, Zoltán Giricz, Adrienn Hanuska, Mahmoud Al-Khrasani, Ákos Zsembery, Tibor Zelles, Laszlo G. Harsing, László Köles

“…Angiotensin IV (Ang IV) and its analogs have demonstrated cognitive benefits in animal models of learning and memory deficits. Methods: Immunohistochemistry and whole-cell patch-clamp techniques were used to map the cell-type-specific localization of AT4R, identical to insulin-regulated aminopeptidase (IRAP), and to investigate the modulatory effects of Ang IV on NMDAR function in layer V pyramidal cells of the rat PFC. …”
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Optimizing Clinical Postgraduate Training: Perspectives of Postgraduate Alumni Regarding Their Residency Training at Mbarara University of Science and Technology, Uganda by Tibaijuka L, Atimango L, Kajjimu J, Owaraganise A, Kamukama N, Kato PK, Mugyenyi GR, Kayondo M, Boatin AA, Ngonzi J

“…While 80% were satisfied with the learning and teaching, only 50% expressed satisfaction with the infrastructure. …”
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Strategies to mitigate the impact of the COVID-19 pandemic on child and youth well-being: a scoping review protocol by Jeanna Parsons Leigh, Henry T Stelfox, Perri R Tutelman, Diane L Lorenzetti, Melanie C Anglin, Kirsten M Fiest, Stephana Julia Moss, Emily A FitzGerald, Stacie Smith, Micaela Harley, Kathryn Birnie, Sara J Mizen

“…Well-being will be operationalised according to pre-established domains (health and nutrition, connectedness, safety and support, learning and competence, and agency and resilience). …”
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Using a digital health intervention “INTERCEPT” to improve secondary prevention in coronary heart disease (CHD) patients: protocol for a mixed methods non-randomised feasibility st... by Catriona Jennings, Irene Gibson, Marissa Corcoran, John William McEvoy, Lis Neubeck, Lisa Hynes, Faisal Sharif, David Wood, Andrew W Murphy, Molly Byrne

“…This will enable early learning about the processes of recruitment and conducting the assessment prior to full scale deployment of INTERCEPT in the next step implementation phase. …”
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Assessing the Uses, Benefits, and Limitations of Digital Technologies Used by Health Professionals in Supporting Obesity and Mental Health Communication: Scoping Review by Amanda Kearns, Anne Moorhead, Maurice Mulvenna, Raymond Bond

“…Technologies such as virtual learning collaborative dashboards and videoconferencing, supported by automated SMS text messaging and social media (Facebook and WhatsApp groups), were commonly used. …”
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Effects of Simultaneously Performed Dual-Task Training with Aerobic Exercise and Working Memory Training on Cognitive Functions and Neural Systems in the Elderly by Hikaru Takeuchi, Daniele Magistro, Yuka Kotozaki, Kosuke Motoki, Keyvan Kashkouli Nejad, Rui Nouchi, Hyeonjeong Jeong, Chiho Sato, Salvatore Sessa, Ryoichi Nagatomi, Massimiliano Zecca, Atsuo Takanishi, Ryuta Kawashima

“…SDAEWMT improved executive function (performance of a frontal assessment battery); however, there was no evidence of broader transfer effects or enhanced learning with WMT. SDAEWMT resulted in mean diffusivity changes in brain areas involving the dopaminergic system, suggesting that neural tissue changes occurred in these areas. …”
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Residency training programs to support residents working in First Nations, Inuit, and Métis communities by Marghalara Rashid, Julie Nguyen, Wayne Clark, Jessica L. Foulds, Ida John, Ming-Ka Chan, Molly Whalen-Browne, Pamela Roach, Melanie Morris, Sarah Forgie

“…Equipping trainees to provide holistic care, immersing in and learning from First Nations, Inuit and/or Métis communities is essential for developing the next generation of clinicians and preceptors. …”
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Autoencoder Reconstruction of Cosmological Microlensing Magnification Maps by Somayeh Khakpash, Federica B. Bianco, Georgios Vernardos, Gregory Dobler, Charles Keeton

“…We introduce a deep-learning model that is trained on pre-computed magnification maps covering the parameter space on a grid of κ , γ , and s . …”
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Pharmacy students’ opinion on mandatory summer internships carried out in community and hospital pharmacies by Lucyna Bułaś, Anna Gołda, Ewa Długosz, Artur Owczarek, Anna Zagaja, Mariola Drozd

“…Results The paper presents the results of selected questions related specifically to the legitimacy of summer internships and learning about professional responsibilities. Altogether 447 questionnaires, evaluating summer internships in both community and hospital pharmacies were collected. …”
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Upskilling or deskilling? Measurable role of an AI-supported training for radiology residents: a lesson from the pandemic by Mattia Savardi, Alberto Signoroni, Sergio Benini, Filippo Vaccher, Matteo Alberti, Pietro Ciolli, Nunzia Di Meo, Teresa Falcone, Marco Ramanzin, Barbara Romano, Federica Sozzi, Davide Farina

“…Critical relevance statement Balancing educational benefits and deskilling risks is essential to exploit AI systems as effective learning tools in radiology residency programs. Our work highlights metrics for evaluating these aspects. …”
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Proteomic, metabolomic and lipidomic profiles in community acquired pneumonia for differentiating viral and bacterial infections by Samuel Rischke, Robert Gurke, Ann-Sophie Zielbauer, Nicole Ziegler, Lisa Hahnefeld, Michaela Köhm, Aimo Kannt, Maria JGT Vehreschild, Gerd Geisslinger, Gernot Rohde, Carla Bellinghausen, Frank Behrens, CAPNETZ Study group

“…Statistical methods, machine learning and pathway analyses were conducted investigating differences between the infection types. …”
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Development of data-driven algal bloom alert models with low temporal resolution data and application to Hong Kong rivers by Shujie Xu, Zhongnan Ye, Shu-Chien Hsu, Xiaoyi Liu, Chunmiao Zheng

“…This study presents a data-driven algal bloom alert model employing machine learning and data discretization techniques to solve the data issue, utilizing monthly water quality data of 12 rivers and daily weather data in Hong Kong. …”
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UK medical students’ mental health and their intention to drop out: a longitudinal study by Asta Medisauskaite, Antonia Rich, Milou Silkens, Neha Lagisetty

“…Medical schools should improve the learning environment for students and encourage them to seek help to reduce the stigma of mental ill-health symptoms (eg, through education, signposting). …”
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A CNN-RF Hybrid Approach for Rice Paddy Fields Mapping in Indramayu Using Sentinel-1 and Sentinel-2 Data by Dodi Sudiana, Mia Rizkinia, Rahmat Arief, Tiara De Arifani, Anugrah Indah Lestari, Dony Kushardono, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo

“…CNN-RF outperforms other classifiers owing to the hybrid learning combination, which improves the accuracy through feature extraction by CNN and handles complex relationships between features while reducing overfitting by RF. …”
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Development and validation of a novel risk-predicted model for early sepsis-associated acute kidney injury in critically ill patients: a retrospective cohort study by Bo Li, Kun Zhang, Cong-Cong Zhao, Zi-Han Nan, Yan-Ling Yin, Li-Xia Liu, Zhen-Jie Hu

“…The least absolute shrinkage and selection operator regression method was used to screen the risk factors, and the final screened risk factors were constructed into four machine learning models to determine an optimal model. External validation was performed using another single-centre intensive care unit (ICU) database.Setting Data for the development cohort were obtained from the MIMIC-IV 2.0 database, which is a large publicly available database that contains information on patients admitted to the ICUs of Beth Israel Deaconess Medical Center in Boston, Massachusetts, USA, from 2008 to 2019. …”
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