Ambiguity Aversion and Household Portfolio Choice Puzzles: Empirical Evidence by Dimmock, Stephen Geoffrey, Kouwenberg, Roy, Mitchell, Olivia S., Peijnenburg, Kim

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Numerical assessment of the side impacts on lithium-ion battery module integrated with honeycomb reinforcement by Mustaffa, Zahiraniza, Al-Qadami, Ebrahim Hamid Hussein, Topa, Ameen, Budiman, Bentang Arief, Mohd Hamka, Nur Aqila, Endrayana Dharmowijoyo, Dimas Bayu, Mohammad Razi, Mohd Adib

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Towards semantic, debiased and moment video retrieval by Satar, Burak

Subjects: “…Causal inference for temporal bias…”
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Incomplete phase metasurface for wavefront reconstruction by Liu, Qiyao, Liu, Zhengtong, Ma, Xuezhi, Deng, Jie, Zhang, Chen, Chen, Zhenmin, Nemati, Arash, Ng, Sui Kit, Gorelik, Sergey, Teo, Siew Lang, Ji, Rong, Zhao, Meng, Gonzaga, Leonard Verano, Liu, Hong, Yue, Fuyong, Yu, Shaohua, Luo, Yu, Wang,Qian

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16.863J / ESD.863J System Safety, Spring 2011 by Leveson, Nancy

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16.63J / ESD.03J System Safety, Fall 2012 by Leveson, Nancy, Thomas, John P.

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PROPERTIES OF POLYMER BLENDS AND CLAY NANOCOMPOSITES / by Zurina Mohamad, editor 200440, Norhayani Othman, editor 249191, Zurina Mohamad, contributor 200440, Norhayani Othman, contributor 249191, Norfhairna Baharulrazi, 1985- contributor 594316, Siti Hajjar Che Man, contributor 222965, Wan Khairuddin Wan Ali, contributor 253428, Siti Maizatul Farhain Salehuddin, 1989-, contributor 593389, Nurathira Abd. Malek, contributor 632650, Norzita Ngadi, 1976- contributor 411591, Zaki Yamani Zakaria, 1976-, contributor 558375, Safirah Adam, contributor 632651, Siti Aishah Ramli, contributor 632652, Jau, Choy Lai, contributor 626454, Wan Aizan Wan Abdul Rahman, contributor 604310, Nur Ain Syahirah Mohamad Hatta, contributor 632653, Mohammed Ehtesham Ali Mohsin, 1985-, contributor 579367, Agus Arsad, contributor 604471, Al-Othman, Othman, contributor 632654, Sani Amril Samsudin, contributor 329204, Nur Zalina Selamat, 1988-, contributor 593407, Azman Hassan, contributor 342780, Aznizam Abu Bakar, contributor 493979, Inas Md. Rodzi, contributor 632655, Nur Nadia Mat Yusof, 1986-, contributor 613769

Growth and characterization of III-V quantum dots on SI-based substrate by Leong, Yu Yan

“…This thesis presents a systematic study of InAs quantum dot (QD) growth on Sibased substrates. …”
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Polarization dependence of intraband absorption in self-organized quantum dots by Chua, S. J., Xu, S. J., Zhang, X. H., Wang, X. C., Mei, T., Fan, Weijun, Wang, C. H., Jiang, J., Xie, X. G.

“…Photoluminescence and intraband absorption were investigated in n-doped self-organized InAs and In0.35Ga0.65As quantum dots grown on a GaAs substrate. …”
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Heteroepitaxial growth and characterization of lll-V compound semiconductor on silicon by Hendrix Tanoto

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Mitigation of the anchoring effect in an electronic audit setting. by Chen, Yingtong., Li, Si En., Loong, Hui Jiun.

“…Forewarning failed to mitigate the bias, but an additional reminder to the forewarning successfully attenuated the bias.…”
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Genotype-phenotype maps for gene networks: from evolution to computation by Camargo, FQ

“…We find that these maps show a strong bias towards simple phenotypes, a pattern known as <em>simplicity bias</em>. …”

Blue shift in photoluminescene of semiconductor nanostructures by Khin, San Thit.

“…Because of band gap expands with reducing particle size, which gives rise to the blue shift in the photoluminescence (PL) and photoabsorbance of nanometric semiconductors such as Si, Si oxides, III-VI semiconductor (GaN, GaP, GaAs, InP and InAs) and II-Vl semiconductor (CdS, CdSe, CdTe, ZnS, ZnSe and ZnTe) compounds. …”
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Quantum computing and quantum neural networks: their foundation, optimisation, and application by Pointing, J

“…We explore the foundation of QNNs by studying their bias and expressivity. We investigate whether a QNN can have a classical deep neural network's (DNN) bias, known as simplicity bias, which is hypothesised to contribute to the success of DNNs. …”

TiN-Mediated Multi-Level Negative Photoconductance of the ZrO2 Breakdown Path by Zhou, Yu, Kawashima, Tomohito, Ang, Diing Shenp

“…A negative voltage-bias does not produce such a tuning effect but can restore the NPC response suppressed by the positive voltage-bias before a re-breakdown step. …”
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The robust F-statistic as a test for weak instruments by Windmeijer, F

“…For the linear model with a single endogenous variable, (Montiel Olea and Pflueger 2013) proposed the effective F-statistic as a test for weak instruments in terms of the Nagar bias of the two-stage least squares (2SLS) or limited information maximum likelihood (LIML) estimator relative to a benchmark worst-case bias. …”

Models for predicting risk of endometrial cancer: a systematic review by Forder, BH, Ardasheva, A, Atha, K, Nentwich, H, Abhari, R, Kartsonaki, C

“…The Prediction model Risk-of-Bias Assessment Tool was used to assess model quality. …”

Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms by Richter, T, Shani, R, Tal, S, Derakshan, N, Cohen, N, Enock, PM, McNally, RJ, Mor, N, Daches, S, Williams, AD, Yiend, J, Carlbring, P, Kuckertz, JM, Yang, W, Reinecke, A, Beevers, CG, Bunnell, BE, Koster, EHW, Zilcha-Mano, S, Okon-Singer, H

“…Machine learning methods, alongside traditional statistical approaches, were employed to analyze 22 datasets with 1544 participants who underwent working memory training, attention bias modification, interpretation bias modification, or inhibitory control training. …”

The role of polarity in nonplanar semiconductor nanostructures by de la Mata, María, Zamani, Reza R., Martí-Sánchez, Sara, Eickhoff, Martin, Xiong, Qihua, Fontcuberta i Morral, Anna, Caroff, Philippe, Arbiol, Jordi

“…The present study has been extended over a wide range of semiconductor compounds, covering the most commonly synthesized III-V (GaN, GaP, GaAs, GaSb, InN, InP, InAs, InSb) and II-VI (ZnO, ZnTe, CdS, CdSe, CdTe) nanowires and other free-standing nanostructures (tripods, tetrapods, belts, and membranes). …”
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Studies on high-frequency noise characteristics in deep submicron NMOSFETs by Zeng, Rong

“…The reduction of minimum noise figure with the increase in body bias may provide a possible methodology to finely adjust the device high-frequency noise performance for circuit design.…”
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