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Unlock Your Earning Potential with the Treehouse Affiliate Program

At Treehouse, our students have always been at the heart of everything we do. By committing to the highest standards of educational content, we’ve grown organically, fueled by the enthusiastic word-of-mouth recommendations from our wonderful learners. These learners haven’t just...

The post Unlock Your Earning Potential with the Treehouse Affiliate Program appeared first on Treehouse Blog.




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Online and offline learning using fading memory functions in HfSiOx-based ferroelectric tunnel junctions

J. Mater. Chem. C, 2024, 12,17362-17376
DOI: 10.1039/D4TC03397C, Communication
Jungwoo Lee, Chaewon Youn, Jungang Heo, Sungjun Kim
We demonstrate online and offline learning as well as associative learning such as in Pavlov's dog experiments using the non-volatile and volatile properties of HfSiOx-based FTJs.
The content of this RSS Feed (c) The Royal Society of Chemistry




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Wild style (1982) / written, produced and directed by Charlie Ahearn [DVD].

[U.K.] : Second Sight, [2009]




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“It is not just the shape, there is more”: students’ learning of enzyme–substrate interactions with immersive Virtual Reality

Chem. Educ. Res. Pract., 2025, Advance Article
DOI: 10.1039/D4RP00210E, Paper
Henry Matovu, Mihye Won, Roy Tasker, Mauro Mocerino, David Franklin Treagust, Dewi Ayu Kencana Ungu, Chin-Chung Tsai
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry




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Self-regulated learning strategies for success in an online first-year chemistry course

Chem. Educ. Res. Pract., 2025, Accepted Manuscript
DOI: 10.1039/D4RP00159A, Paper
Langanani Rakhunwana, Angelique Kritzinger, Lynne Alison Pilcher
During their first year of study at university, many students encounter challenges in developing learning strategies that align with success in the courses in which they are enrolled. The emergence...
The content of this RSS Feed (c) The Royal Society of Chemistry




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Elucidating the impact of oxygen functional groups on the catalytic activity of M–N4–C catalysts for the oxygen reduction reaction: a density functional theory and machine learning approach

Mater. Horiz., 2024, 11,1719-1731
DOI: 10.1039/D3MH02115G, Communication
Liang Xie, Wei Zhou, Yuming Huang, Zhibin Qu, Longhao Li, Chaowei Yang, Yani Ding, Junfeng Li, Xiaoxiao Meng, Fei Sun, Jihui Gao, Guangbo Zhao, Yukun Qin
While current experimental and computational studies often concentrate on introducing external structures or idealized MN4 models, we emphasize the often-overlooked impact of inherent OGs within the carbon structure of MN4 materials, presenting a new perspective on their catalytic activity origin.
The content of this RSS Feed (c) The Royal Society of Chemistry




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Exploring negative thermal expansion materials with bulk framework structures and their relevant scaling relationships through multi-step machine learning

Mater. Horiz., 2024, Advance Article
DOI: 10.1039/D3MH01509B, Communication
Yu Cai, Chunyan Wang, Huanli Yuan, Yuan Guo, Jun-Hyung Cho, Xianran Xing, Yu Jia
We uses the multi-step ML method to mine 1000 potential NTE materials from ICSD, MPD and COD databases, and the presented phase diagram can serve as a preliminary criterion for judging and designing new NTE materials.
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry




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Union Budget 2024-25 — no signs of learning

The mismatch between the problem at hand and what the Budget offers is stark be it welfare or even taking care of key political allies




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Centre earns over ₹650 crore revenue from scrap disposal during special cleanliness campaign in October

Special campaigns conducted by the government from 2021-24 have generated a revenue of ₹2,364 crore through disposal of scrap, says Personnel Ministry in an official statement




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When the U.S. catches a cold, Canada sneezes: a lower-bound tale told by deep learning [electronic journal].




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What Does Earnings Management Signal? The Role of Managerial Honesty in Investment Decisions [electronic journal].




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Tax Simplicity and Heterogeneous Learning [electronic journal].

National Bureau of Economic Research




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Social learning in agriculture: does smallholder heterogeneity impede technology diffusion in Sub-Saharan Africa? [electronic journal].




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Sequential Learning with Endogenous Consideration Sets [electronic journal].




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Sequential Learning [electronic journal].




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The Role of Parenthood on the Gender Gap among Top Earners [electronic journal].




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The Rise of US Earnings Inequality: Does the Cycle Drive the Trend? [electronic journal].

National Bureau of Economic Research




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Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium [electronic journal].




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Predicting Consumer Default: A Deep Learning Approach [electronic journal].

National Bureau of Economic Research




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Predictably Unequal? The Effects of Machine Learning on Credit Markets [electronic journal].




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Potential consequences of post-Brexit trade barriers for earnings inequality in the UK [electronic journal].




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Pareto-improving tax reforms and the Earned Income Tax Credit [electronic journal].




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Market Power and Price Discrimination: Learning from Changes in Renewables Regulation [electronic journal].




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Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence [electronic journal].




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The Lost Human Capital: Teacher Knowledge and Student Learning in Africa [electronic journal].




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Learning When to Quit: An Empirical Model of Experimentation [electronic journal].

National Bureau of Economic Research




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Learning to Import from Your Peers [electronic journal].




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Learning over the Business Cycle: Policy Implications [electronic journal].




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Learning Management Through Matching: A Field Experiment Using Mechanism Design [electronic journal].

National Bureau of Economic Research




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Learning from Noise: Evidence from India's IPO Lotteries [electronic journal].




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Learning from Nationally Determined Contributions [electronic journal].




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Learning from House Prices: Amplification and Business Fluctuations [electronic journal].




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Learning from failure across products [electronic journal].




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Learning about one's self [electronic journal].




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Learning About Demand Abroad From Wholesalers: a B2B Analysis [electronic journal].




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Immersive Learning Research Network (iLRN), Conference of the [electronic journal].

IEEE / Institute of Electrical and Electronics Engineers Incorporated




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Identifying and Estimating the Effects of Unconventional Monetary Policy: How to Do It And What Have We Learned? [electronic journal].




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How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm [electronic journal].




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Girls' and Boys' Performance in Competitions: What We Can Learn from a Korean Quiz Show [electronic journal].




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Firms' Beliefs and Learning: Models, Identification, and Empirical Evidence [electronic journal].




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Financial Incentives and Earnings of Disability Insurance Recipients: Evidence from a Notch Design [electronic journal].

National Bureau of Economic Research




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Family and Government Insurance: Wage, Earnings, and Income Risks in the Netherlands and the U.S. [electronic journal].

National Bureau of Economic Research




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Experimentation, Learning, and Preemption [electronic journal].




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Earnings Dynamics and Firm-Level Shocks [electronic journal].

National Bureau of Economic Research




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Do Analysts Learn from Each Other? Evidence from Analysts' Location Diversity [electronic journal].




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Distance Learning in Higher Education: Evidence from a Randomized Experiment [electronic journal].




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Current account adjustment and retained earnings [electronic journal].




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Building(s and) cities: Delineating urban areas with a machine learning algorithm [electronic journal].




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Always Egalitarian? Australian Earnings Inequality 1870-1910 [electronic journal].




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2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) [electronic journal].

IEEE Computer Society