77 10 859 https://linen-dog.lnx.warwick.ac.uk/files/original/917cd65506e97cb6b8341cc6e29de284.pdf 687192ab34cbd553e4895698dbc98f9b Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The use of the Red Mason bee, Osmia Bicornis, as a managed pollinator of orchard crops Subject The topic of the resource Life Sciences Creator An entity primarily responsible for making the resource William Wassink Date A point or period of time associated with an event in the lifecycle of the resource 2023 crop yield Life Sciences Osmia Bicornis pollen analysis pollinators Red Mason Bee William Wassink https://linen-dog.lnx.warwick.ac.uk/files/original/d494118b127c0e135c1ebffbeed0ddd9.pdf 36d0bcc0ab8955132e3065f820db1e39 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Abstract The abstract of the paper Traditionally, academics have suggested that generating excess returns off timing the market, i.e. buying or selling financial products off frequent predictions requires maintaining an unreasonably high level of predictive accuracy. However, recent advancements in machine learning have motivated the adoption of predictive algorithms in financial markets. This highlights the importance of the question: How accurate do predictive algorithms have to be "useful"? To answer this, we study 2 problems related to the value of predictive accuracy in directional models for trading. We obtain results on the relationship between predictive accuracy and returns, and results on quantifying thresholds for when a predictive signal provides significant edge. Meta Tags Meta tags Mathematical Finance, Probability, Statistics, Mathematics, Trading, Predictive Models Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Daiki Asano, James Cheng, Zelin Sun, Matthew Zhao Contributor An entity responsible for making contributions to the resource Daiki Asano, James Cheng, Zelin Sun, Matthew Zhao Title A name given to the resource The Value of Predictive Accuracy in Directional Models for Trading Subject The topic of the resource Statistics Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/5bb99edb377fea12b37b55a436f017d8.pdf 93dbfd328e071609351d1598f23ecf5d Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Variance of the Fibonacci Partition Function Subject The topic of the resource Mathematics Creator An entity primarily responsible for making the resource Owen Jones Date A point or period of time associated with an event in the lifecycle of the resource 07/11/23 Asymptotics Fibonacci Numbers Number Theory Owen Jones https://linen-dog.lnx.warwick.ac.uk/files/original/b651fa6ec6403e40dcad79fdda3c0ed5.pdf e555842bb8743ca4a132e5f938b70ed6 Academic Paper An academic paper Abstract The abstract of the paper Between 2020 and 2025, Peru’s government and Congress enacted eight measures that let people withdraw money from their compulsory private pension accounts. In 2024, Congress passed a reform banning further withdrawals. The ban began to apply on 6 September 2025. Fourteen days later, Congress published a law that allowed another withdrawal and removed the restrictions the reform had introduced. This paper asks why Congress reversed a restriction it had itself approved. It proposes a working hypothesis: once withdrawals became politically normal, voting against was costlier than voting for. A legislator’s earlier stance should then predict little about their later vote. The paper tests this on a panel of 130 legislators over five plenary votes cast by the Congress elected in 2021. It uses four votes from an earlier, separate Congress only for context. The evidence is descriptive, not causal. Support never fell below 90 per cent of votes cast in the Congress elected in 2021 and reached 95.7 per cent in September 2025. Twenty-three legislators voted for a withdrawal in April 2024, for the reform in June 2024 and for the reversal in September 2025. Of the legislators who backed the reform, 33 of 38 voted for the reversal. Of those who opposed it, 9 of 10 did. Emergency relief alone is hard to reconcile with the later withdrawals. Party coordination is consistent with part of the record, not all of it. Public demand cannot be ruled out. Electoral incentives and ideology are not tested. Meta Tags Meta tags Peru, pension withdrawals, private pension system, political economy, congressional voting, pension reform, public policy, legislative behaviour, Peru Congress, social security Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Withdrawal Ratchet: Why Did Peru’s Congress Reverse Its Own Pension Restrictions? Subject The topic of the resource Economics Date A point or period of time associated with an event in the lifecycle of the resource 4th October 2026 Contributor An entity responsible for making contributions to the resource Salvador Quesada Boza https://linen-dog.lnx.warwick.ac.uk/files/original/161f76b0cedb2669cae3bc1fb3f3e28c.pdf 5bc049778e14a206aea7e6e41cca99e8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Paper An academic paper Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The World Bank and its Promotion of Privatisation as a Tool of Poverty Alleviation Subject The topic of the resource Law Creator An entity primarily responsible for making the resource Lewis Inglis Date A point or period of time associated with an event in the lifecycle of the resource 2023 banks capitalist system global Law Lewis Inglis poverty alleviation World Bank https://linen-dog.lnx.warwick.ac.uk/files/original/b95aaf25d5d7214617363b21aaff002d.pdf 06e0d70679345440814b9c293b56ad9e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Arts Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Written Word: Muslim Representation in Academia Subject The topic of the resource English and Comparative Literary Studies Creator An entity primarily responsible for making the resource Maham Mir Date A point or period of time associated with an event in the lifecycle of the resource 2023 Curriculum English and Comparative Literary Studies Higher education Literature Maham Mir Muslim representation https://linen-dog.lnx.warwick.ac.uk/files/original/14b9086de29e168b485eb9536f919d19.pdf a189f4c0d8c1a0442c3592919ca5e077 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Theoretical and Computational Study of Magnetostrictive Iron-Rich Alloys Subject The topic of the resource Physics Creator An entity primarily responsible for making the resource Jordan Edwards Date A point or period of time associated with an event in the lifecycle of the resource 2022 Copper Galfenol magnetocrystalline anisotropy magnetostriction https://linen-dog.lnx.warwick.ac.uk/files/original/32827687e0c53f3875b0699852c6c7ba.pdf 84cdcf90d14828a43407d05e1c4cbd1e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Till Irreconcilable Differences Do Us Part”: An Analysis of the Factors Leading UK Adults to Divorce Subject The topic of the resource Sociology Creator An entity primarily responsible for making the resource Charlotte Ball Date A point or period of time associated with an event in the lifecycle of the resource 2023 Charlotte Ball divorce marriage Sociology unfaithfulness https://linen-dog.lnx.warwick.ac.uk/files/original/8de4c4db9b618253fd55f486fd6c551c.pdf 03d62336fe211e31dad0594a2e122d89 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Aaron Joseph Contributor An entity responsible for making contributions to the resource Salimeh Pour Mohammad Title A name given to the resource Time Series Analysis of US Air Pollution Description An account of the resource Warwick Business School Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/85b052a3dddaf932bd8d5bb93ff26bb4.pdf 8d076455a61b154b9ec79dcde8bd32a0 Academic Poster An academic poster Abstract The abstract of the paper This project investigates whether time-series signals can be compressed without losing the information needed for reliable classification. Four compression methods—PAA, PLA, APCA and Fourier representations—are evaluated on the FordA and ECG5000 datasets using a shared neural-network classifier. The experiments examine classification performance, training and inference efficiency, and robustness to noise and missing values when only 50% or 25% of the original input width is retained. Signal reconstructions and PCA visualisations are also used to examine which structures remain after compression. The results show that Fourier representations provide the strongest overall trade-off, sometimes improving classification performance while reducing input width and model size, although computational speed-ups depend on the dataset and compression method. Meta Tags Meta tags machine learning, dimensionality reduction, signal processing, Fourier transform, neural networks, robustness Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Time-Series Compression for Classification: Performance, Efficiency and Robustness on FordA and ECG5000 Creator An entity primarily responsible for making the resource Kaitao (Kenneth) Jiang Contributor An entity responsible for making contributions to the resource Weiren Yu Subject The topic of the resource Computer Science – Machine Learning and Time-Series Analysis