Improving the diagnostic yield of whole genome sequencing: neurodevelopmental and epilepsy disorders by Hashim, M

“…</p> <p>Amongst the disrupted a novel gene was PPP2R2A, which encodes for the regulatory subunit of Protein phosphatase 2 complex enzyme. It is part of the Phospho Protein Phosphatase 2 (PPP2) gene family of which six members are known to cause PP2A-related neurodevelopmental disorders. …”

Printing of functional materials in 2D and 3D structures by Halevi, Oded

“…Despite their extensive investigations in the past twenty years, the utilization of MOFs for industrial and commercial applications is scarce, due to physical and chemical limitations. …”
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Understanding lived experiences of bereaved parents of children with chronic life-threatening Illness : towards a culture-specific and meaning-oriented narrative E-writing interven... by Dutta, Oindrila

“…In Singapore, while deaths among children and youths (age<19) have been steadily declining over the past decade, the number of child deaths caused by chronic conditions has increased by about 27% from 120 in 2014 to 152 in 2016. …”
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Geometry guided supervised representation learning for classification by Li, Yue

“…Machine learning is an essential part of artificial intelligence and a useful tool for data mining. …”
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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.

“…Methods: We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. …”
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Neural combinatorial optimization: from routing to integer programming by Wu, Yaoxin

“…To solve two-stage stochastic integer programs (2SIPs), we use conditional variational autoencoder (CVAE) to learn scenario representations, where a graph convolutional network (GCN) based encoder embeds each scenario with the deterministic part (i.e. context) of a 2SIP instance into the latent space, from which a decoder reconstructs the scenario from its latent representation conditioned on the context. …”
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Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes by McAllan, Liam, Baranasic, Damir, Villicaña, Sergio, Brown, Scarlett, Zhang, Weihua, Lehne, Benjamin, Adamo, Marco, Jenkinson, Andrew, Elkalaawy, Mohamed, Mohammadi, Borzoueh, Hashemi, Majid, Fernandes, Nadia, Lambie, Nathalie, Williams, Richard, Christiansen, Colette, Yang, Youwen, Zudina, Liudmila, Lagou, Vasiliki, Tan, Sili, Castillo-Fernandez, Juan, King, James W. D., Soong, Richie, Elliott, Paul, Scott, James, Prokopenko, Inga, Cebola, Inês, Loh, Marie, Lenhard, Boris, Batterham, Rachel L., Bell, Jordana T., Chambers, John Campbell, Kooner, Jaspal S., Scott, William R.

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An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study by Slieker, Roderick C., Münch, Magnus, Donnelly, Louise A., Bouland, Gerard A., Dragan, Iulian, Kuznetsov, Dmitry, Elders, Petra J. M., Rutter, Guy A., Ibberson, Mark, Pearson, Ewan R., Hart, Leen M. 't, van de Wiel, Mark A., Beulens, Joline W. J.

“…Methods: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). …”
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Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk by Zhu, Yinghan, Maikusa, Norihide, Radua, Joaquim, Sämann, Philipp G., Fusar-Poli, Paolo, Agartz, Ingrid, Andreassen, Ole A., Bachman, Peter, Baeza, Inmaculada, Chen, Xiaogang, Choi, Sunah, Corcoran, Cheryl M., Ebdrup, Bjørn H., Fortea, Adriana, Garani, Ranjini Rg, Glenthøj, Birte Yding, Glenthøj, Louise Birkedal, Haas, Shalaila S., Hamilton, Holly K., Hayes, Rebecca A., He, Ying, Heekeren, Karsten, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kristensen, Tina D., Kwon, Jun Soo, Lawrie, Stephen M., Lebedeva, Irina, Lee, Jimmy, Loewy, Rachel L., Mathalon, Daniel H., McGuire, Philip, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria A., Raghava, Jayachandra M., Røssberg, Jan I., Rössler, Wulf, Salisbury, Dean F., Sasabayashi, Daiki, Smigielski, Lukasz, Sugranyes, Gisela, Takahashi, Tsutomu, Tamnes, Christian K., Tang, Jinsong, Theodoridou, Anastasia, Tomyshev, Alexander S., Uhlhaas, Peter J., Værnes, Tor G., van Amelsvoort, Therese A. M. J., Waltz, James A., Westlye, Lars T., Zhou, Juan H., Thompson, Paul M., Hernaus, Dennis, Jalbrzikowski, Maria, Koike, Shinsuke

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Pnictogen-halide semiconductors for photovoltaics by Liu, P

“…<p>Indoor photovoltaic (IPV) development has garnered increasing interest in recent years because of the potential to sustainably provide energy to the billions of autonomous devices part of the Internet of Things (IoT) ecosystem. The emission spectra of indoor light sources are narrower and blue-shifted compared to the standard terrestrial outdoor AM 1.5G solar spectrum, which is the reference spectrum for standard testing of solar energy conversion systems, with a specified standard irradiance of 1000 W/m2[1]; AM stands for air mass coefficient. …”

Studies on GaN based HEMT heterostructures on 100-mm silicon grown by molecular beam epitaxy by Ravikiran Lingaparthi

“…GaN based high electron mobility transistors (HEMTs) have attracted great attention over the last two decades for the high power and high frequency applications due to their advantages of polarization induced high electron density, high break down field and high saturation electron velocity. …”
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Fabrication and characterization of Algan/Gan high electron mobility transistors on silicon by Tham, Wai Hoe

“…Therefore, we believe that the Au-free low temperature metal scheme has great prospects and potential in the fabrication of AlGaN/GaN HEMTs on Si platform. Last but not least, the performance of AlGaN/GaN HEMT is usually restricted by the severe gate leakage and high access resistance between the source and gate. …”
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Detection of road markings for advanced driver assistance by Suchitra Sathyanarayana

“…It relies on decomposing the arrow markings into its constituent parts by representing each part with a unique shape signature using a combination of GAH, signed edges and HT. …”
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Graph representation learning by Zhang, Xinyi

“…Graph representation learning has been shown to be promising in graph analysis where the graphs or part of the graphs will be converted into a lower-dimensional space while the important information (e.g., structure information and attribute information) of the graph is still well preserved. …”
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Surface engineering to manipulate solar energy for thermal management by Fei, Jipeng

“…Different from conventional radiative coolers, the metagel transfers part of the incident solar energy to the internal energy of the water vapor released. …”
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Preparation of low-dimensional materials for plasmonic bio-sensing by Das, Chandreyee Manas

“…With this our motive was to show how TMDC based functionalization-free SPR sensors can also be realized in the domain of commercial sensing platforms. Lastly, we performed some optical experiments (GH shift sensitivity) to compare the sensitivities of pure Au and graphene coated Au chips. …”
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(宋代「武夷棹歌」中的地景空間與文化意蘊) = Landscape and culture in the Wu-yi Zhao Ge (Wu-yi boat song) of Song dynasty by 衣若芬 I, Lo-fen

“…Wu-yi is a famous mountain located in the southern part of China. There is a record shown in the “Shi Ji.Feng Chan Shu” using dried fish as an offering to Wu-yi Jun( Gods of Wu-yi mountain). …”
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Video processing for home security system by Chan, Nicholas Yan Bin.

“…The security system can be divided into 4 parts, the visual component, the speech component, the text component, and lastly the integration. …”
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Effect of surfactant HLB on some gel properties of pigeonpea and cowpea starches by Mwasaru, Mwanjala A., Muhammad, Kharidah

“…Surfactants of HLB 1.8, 3.8, 6.7, 16.0, and 20.0 significantly decreased the paste consistency of pigeonpea starch pastes at 97 °C. …”
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Design and development of a bottle cap opening device by Kok, Yane Jun Yan

“…Next stage is to refine the design using SolidWorks and come out with dimensions and parts needed to bring the idea to life. The idea consists of an upper movable system, a rotation system and a gripping system. …”
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