Metamaterial based power divider for millimeter wave NDT system by Cheong, Kai Yeong

“…In order to reduce downtime, cost and at the same time increase reliability, the aircraft industry have invested a huge sum into Non-Destructive Testing (NDT) technology over the years. The development of Materials Technology created many stronger, lighter, stiffer and more durable electrically insulating materials that are replacing metals in many applications. …”
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The afterlife of site-specific sculpture: a self-referential study through practice by Kim, M

“…The work explores what has been done in the past and pursues the next phase by reflecting previous attempts in stages, therefore, occasionally bringing in the concept of a meta-structure. This methodology re-influences the development of the practice and renews its formal structure. …”

Synthesis of metal alloy catalysts using high-throughput experiments and machine learning optimization by Calista, Vania

“…The periodic table comprises over a hundred elements, offering numerous possibilities for the discovery of novel materials that have superior properties and could therefore be used to address current technological and societal challenges. …”
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Persuasion for protection: an analysis of online safety videos on YouTube by Huang, Liuyu, Goh, Dion Hoe-Lian, Yin, Stella Xin

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Phonological and semantic influences on auditory word perception in children with and without reading impairments using magnetoencephalography (MEG) and electroencephalography (EEG... by Wehner, Daniel T

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Interventions for managing skeletal muscle spasticity following traumatic brain injury by Synnot, Anneliese, Chau, Marisa, Pitt, Veronica, O'Connor, Denise, Gruen, Russell Lindsay, Wasiak, Jason, Clavisi, Ornella, Pattuwage, Loyal, Phillips, Kate

“…Data were synthesised narratively; meta‐analysis was precluded due to the paucity and heterogeneity of data. …”
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Applying a nanoparticle@mof interface to activate an unconventional regioselectivity of an inert reaction at ambient conditions by Lee, Hiang Kwee, Koh, Charlynn Sher, Lo, Wei-Shang, Liu, Yejing, Phang, In Yee, Sim, Howard Yi, Lee, Yih Hong, Phan-Quang, Gia Chuong, Tsung, Chia-Kuang, Ling, Xing Yi

“…Notably, we observe an unprecedented CO₂ meta-carboxylation of an arene that was previously deemed impossible in traditional Kolbe-Schmitt reactions. …”
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Machine learning-based approaches for large-scale temporal data analytics by Seyed Ali Majid Zonoozi

“…In our first study, a scalable optimization model is proposed to track multiple concepts and participation of actors in each concept over time, in order to track the changes in underlying distribution of data. …”
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Targeted pancreatic beta cell imaging for early diagnosis by Cong, Goh Zheng, Ghosh, Krishna Kanta, Mishra, Sachin, Gulyás, Miklós, Kovács, Tibor, Máthé, Domokos, Padmanabhan, Parasuraman, Gulyás, Balázs

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Conflict-free urban air mobility planning with an airspace-resource-centric approach by Dai, Wei

“…The conventional air transport system has been operating for over a hundred years with great performances in both efficiency and safety, which raises high requirements for the future operations of UAM. …”
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Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis... by Reitsma, M. B., Kendrick, P. J., Ababneh, E., Abbafati, C., Abbasi-Kangevari, M., Abdoli, A., Abedi, A., Abhilash, E. S., Abila, D. B., Aboyans, V., Abu-Rmeileh, N. M., Adebayo, O. M., Advani, S. M., Aghaali, M., Ahinkorah, B. O., Ahmad, S., Ahmadi, K., Ahmed, H., Aji, B., Akunna, C. J., Al-Aly, Z., Alanzi, T. M., Alhabib, K. F., Ali, L., Alif, S. M., Alipour, V., Aljunid, S. M., Alla, F., Allebeck, P., Alvis-Guzman, N., Amin T. T., Amini, S., Amu, H., Amul, G. G. H., Ancuceanu, R., Anderson, J. A., Ansari-Moghaddam, A., Antonio, C. A. T., Antony, B., Anvari, D., Arabloo, J., Arian, N. D., Arora, M., Asaad, M., Ausloos, M., Awan, A. T., Ayano, G., Aynalem, G. L., Azari, S., B, D.B., Badiye, A. D., Baig, A. A., Bakhshaei, M. H., Banach, M., Banik, P.C., Barker-Collo, S. L., Bärnighausen, T. W., Barqawi, H. J., Basu, S., Bayati, M., Bazargan-Hejazi, S., Behzadifar, M., Bekuma, T. T., Bennett, D. A., Bensenor, I. M., Berfield, K. S. S., Bhagavathula, A. S., Bhardwaj, N., Bhardwaj, P., Bhattacharyya, K., Bibi, S., Bijani, A., Bintoro, B. S., Biondi, A., Birara, S., Braithwaite, D., Brenner, H., Brunoni, A. R., Burkart, K., Butt, Z. A., Caetano dos Santos, F. L., Car, Josip, Cárdenas, R., Carreras, G., Carrero, J. J., Castaldelli-Maia, J. M., Cattaruzza, M. S. S., Chang, J. C., Chen, S., Chu, D. T., Chung, S. C., Cirillo, M., Costa, V. M., Couto, R. A. S., Dadras, O., Dai, X., Damasceno, A. A. M., Damiani, G., Dandona, L.

“…We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. …”
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A machine-learned approach for reducing airborne delays and environmental impact in terminal manoeuvring area using extended arrival management by Lim, Zhi Jun

“…The agents are trained over 1 million steps using the Proximal Policy Optimization (PPO) algorithm and evaluated through 100 simulations against two baseline scenarios: no action and random action. …”
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Interventions for smoking cessation in hospitalised patients by Streck, JM, Rigotti, NA, Livingstone-Banks, J, Tindle, HA, Clair, C, Munafò, MR, Sterling-Maisel, C, Hartmann-Boyce, J

“…<p><b>Main results</b></p> We included 82 studies (74 RCTs) that included 42,273 participants in the review (71 studies, 37,237 participants included in the meta‐analyses); 36 studies are new to this update. …”

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021 by Bhattacharjee, NV, Schumacher, AE, Aali, A, Almidani, O, Bandyopadhyay, S, Graham, SM, Lacey, BWH, Maude, RJ, Runghien, T, Rodriguez, JAB

“…To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. …”