243 research outputs found
Uncrossing the ‘X’: Characterization of alternative alleles for KSLX in Oryza
No full textThe widely cultivated Asian rice (Oryza sativa) produces a variety of physiologically relevant diterpenoid products, which range in effect from the phytohormone gibberellin, derived from ent-kaurene, to phytoalexins such as the momilactones, derived from syn-pimara-7,15-diene. Previous reports have shown functional variation in the kaurene synthase-like (KSL) genes responsible for synthesizing diterpene precursors to more specialized metabolites, leading to the creation of distinct diterpenoids from allelomorphic genes. Here is reported the product of two previously discovered but uncharacterized alleles of the unusual KSLX, representing a cross between (fusion of) the tandem pair KSL8-KSL9p found in most cultivars. The previously characterized allele (KSLXo) was reported to act on syn-copalyl pyrophosphate (syn-CPP) to produce syn-abieta-7,12-diene, precursor to the phytoalexin oryzalactone. However, at least one other functionally distinct allele was reported from the O. sativa pan-genome (KSLXn), along with another phylogenetically distinct allele found in Oryza barthii (KSLXb), but these were not further characterized. Here both KSLXn and KSLXb were found to selectively react with syn-CPP and produce syn-pimara-9(11),15-diene, a novel diterpene in rice. Additionally, evolution of this locus was investigated, with KSLXb hypothesized to be a functional KSL9. The striking complexity of this locus, which includes distinct composition (KSL8-KSL9(p) or KSLX) as well as allelomorphism of both KSL8 and KSLX, suggests it is subject to balancing selection, consistent with the competing pressures exerted on phytoalexin biosynthesis. Regardless, the studies reported here clarify this additional example of allelomorphic variation in the rice KSL family, providing insight into the rice pan-genomic diterpenoid arsenal.This article is published as Weers, Tristan, Yiling Feng, and Reuben Peters. "Uncrossing the ‘X’: Characterization of alternative alleles for KSLX in Oryza." Phytochemistry 240 (2025): 114634. https://doi.org/10.1016/j.phytochem.2025.114634This work was supported by grants from the USDA-NIFA (2020-67013-32557) and NIH (GM156300)
Doplor Sleep: Monitoring Hospital Soundscapes for Better Sleep Hygiene
No full textGood sleep is conducive to the recovery process of hospital patients - and yet, in many wards, sleep duration and quality can often be suboptimal, in part due to modifiable hospital-related sounds and noises. At the neurological ward of the Reinier de Graaf hospital in Delft, the Netherlands, we developed and evaluated a prototype information exchange system to raise awareness of specific sounds as disturbing patients' sleep. The system both classifies different relevant sound events and tracks sleep quality (using a Fitbit device). This information is then visualized for patients and staff to present the influence of the soundscape on patients' sleep hygiene in a friendly and comprehensive way. We discuss the design process, including a context study and various evaluations of the technology, interface, and created affordances. Our initial findings indicate that visualizing hospital soundscapes may, indeed, support both patients and staff in their efforts towards better sleep hygiene. Design AestheticsInternet of Thing
Double-barreled defense: dual ent-miltiradiene synthases in most rice cultivars
No full textRice (Oryza sativa) produces numerous diterpenoid phytoalexins that are important in defense against pathogens. Surprisingly, despite extensive previous investigations, a major group of such phytoalexins, the abietoryzins, were only recently reported. These aromatic abietanes are presumably derived from ent-miltiradiene, but such biosynthetic capacity has not yet been reported in O. sativa. While wild rice has been reported to contain such an enzyme, specifically ent-kaurene synthase-like 10 (KSL10), the only characterized ortholog from O. sativa (OsKSL10), specifically from the well-studied cultivar (cv.) Nipponbare, instead has been shown to make ent-sandaracopimaradiene, precursor to the oryzalexins. Notably, in many other cultivars, OsKSL10 is accompanied by a tandem duplicate, termed here OsKSL14. Biochemical characterization of OsKLS14 from cv. Kitaake demonstrates that this produces the expected abietoryzin precursor ent-miltiradiene. Strikingly, phylogenetic analysis of OsKSL10 across the rice pan-genome reveals that from cv. Nipponbare is an outlier, whereas the alleles from most other cultivars group with those from wild rice, suggesting that these also might produce ent-miltiradiene. Indeed, OsKSL10 from cv. Kitaake exhibits such activity as well, consistent with its production of abietoryzins but not oryzalexins. Similarly consistent with these results is the lack of abietoryzin production by cv. Nipponbare. Although their equivalent product outcome might suggest redundancy, OsKSL10 and OsKSL14 were observed to exhibit distinct expression patterns, indicating such differences may underlie retention of these duplicated genes. Regardless, the results reported here clarify abietoryzin biosynthesis and provide insight into the evolution of rice diterpenoid phytoalexins.This article is published as Feng, Y., Weers, T. & Peters, R.J. Double-barreled defense: dual ent-miltiradiene synthases in most rice cultivars. aBIOTECH (2024). https://doi.org/10.1007/s42994-024-00167-3. Copyright The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
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Adapting Fairness-Intervention Algorithms to Missing Data
No full textMissing values in real-world data pose a significant and unique challenge to algorithmic fairness. Different demographic groups may be unequally affected by missing data, and standard procedures for handling missing values such as impute-then-classify can exacerbate discrimination. In this thesis, we analyze how missing values in data affect algorithmic fairness. We discuss the fairness risks posed by disparate missingness and the limitations of impute-then-classify. We then prove a theoretical result that characterizes the reduction in fairness-accuracy potential when training a model on imputed data. We present scalable adaptive algorithms for fair classification with missing values. These algorithms can be combined with any preexisting fairness-intervention algorithm to handle all possible missing patterns while avoiding the disadvantages of impute-then-classify. Numerical experiments with an array of state-of-the-art fairness interventions demonstrate that our adaptive algorithms consistently achieve higher fairness and accuracy than impute-then-classify across many different datasets, particularly when the missingness pattern of the data conveys significant information about the predictive label
A Machine with Short-Term, Episodic, and Semantic Memory Systems
No full textInspired by the cognitive science theory of the explicit human memory systems, we have modeled an agent with short-term, episodic, and semantic memory systems, each of which is modeled with a knowledge graph. To evaluate this system and analyze the behavior of this agent, we designed and released our own reinforcement learning agent environment, the Room , where an agent has to learn how to encode, store, and retrieve memories to maximize its return by answering questions. We show that our deep Q-learning based agent successfully learns whether a short-term memory should be forgotten, or rather be stored in the episodic or semantic memory systems. Our experiments indicate that an agent with human-like memory systems can outperform an agent without this memory structure in the environment
Oryzalexin S biosynthesis: a cross-stitched disappearing pathway
No full textRice produces many diterpenoid phytoalexins and, reflecting the importance of these natural products in this important cereal crop plant, its genome contains three biosynthetic gene clusters (BGCs) for such metabolism. The chromosome 4 BGC (c4BGC) is largely associated with momilactone production, in part due to the presence of the initiating syn-copalyl diphosphate (CPP) synthase gene (OsCPS4). Oryzalexin S is also derived from syn-CPP. However, the relevant subsequently acting syn-stemarene synthase gene (OsKSL8) is not located in the c4BGC. Production of oryzalexin S further requires hydroxylation at carbons 2 and 19 (C2 and C19), presumably catalyzed by cytochrome P450 (CYP) monooxygenases. Here it is reported the closely related CYP99A2 and CYP99A3, whose genes are also found in the c4BGC catalyze the necessary C19-hydroxylation, while the closely related CYP71Z21 and CYP71Z22, whose genes are found in the recently reported chromosome 7 BGC (c7BGC), catalyze subsequent hydroxylation at C2α. Thus, oryzalexin S biosynthesis utilizes two distinct BGCs, in a pathway cross-stitched together by OsKSL8. Notably, in contrast to the widely conserved c4BGC, the c7BGC is subspecies (ssp.) specific, being prevalent in ssp. japonica and only rarely found in the other major ssp. indica. Moreover, while the closely related syn-stemodene synthase OsKSL11 was originally considered to be distinct from OsKSL8, it has now been reported to be a ssp. indica derived allele at the same genetic loci. Intriguingly, more detailed analysis indicates that OsKSL8(j) is being replaced by OsKSL11 (OsKSL8i), suggesting introgression from ssp. indica to (sub)tropical japonica, with concurrent disappearance of oryzalexin S production.This article is published as Zhao, L., Oyagbenro, R., Feng, Y. et al. Oryzalexin S biosynthesis: a cross-stitched disappearing pathway. aBIOTECH 4, 1–7 (2023). https://doi.org/10.1007/s42994-022-00092-3. Copyright The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
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Machine Learning-Aided Economic Design
No full textNowadays, online markets (e.g. online advertising market and online two-sided markets) grow larger and larger everyday. Designing an efficient and near-optimal market is an intricate task. Market designers are facing challenges not only in regard to scalability, but also coming from the use of data to better understand the
behavior of strategic participants. At the same time, these participants are trying to understand how these markets work and to maximize reward. For these reasons, we continue to need improved frameworks for the design of online markets. One challenge for market design is to make effective use of data in order to design better markets. For the players, a central problem is how to optimize their strategy, adaptively learning from feedback and incorporating this along with other side information.
To handle these challenges, my thesis focuses on two topics, \emph{Economic Design via Machine Learning} and \emph{Learning in Online Markets}. For the first topic, I propose a unified computational framework for data-driven mechanism design that can help a mechanism designer to automatically design a good mechanism to satisfy incentive constraints and achieve a desired objective (e.g. revenue, social welfare). I provide different approaches to guarantee Incentive Compatibility and prove the generalization bounds. This deep-learning framework is very general and can be extended to handle other constraints, e.g., private budget constraints. In addition, I investigate how to transform an approximately incentive compatible mechanism to a fully BIC mechanism without loss of welfare and with only negligible loss of revenue. For the second topic, I analyze the convergence of the outcome achieved by strategic bidders when they adopt mean-based learning algorithms to bid in repeated auctions. I also propose a new online learning algorithm for a bidder to use when bidding in repeated auctions, where the bidder's own value, evolving in an arbitrary manner, and observed only if the bidder wins an auction. This algorithm has exponentially faster convergence in terms of its dependence on the action space than the generic bandit algorithm
Chan zong zheng zhi
No full text劉體恕彙輯 ; 劉蔭誠, 劉允誠仝校 ; 黃誠恕✹訂 .綫裝, 1函.框18.5x12.1公分, 9行21字, 小字雙行同. 白口, 四周雙邊, 單黑魚尾. 版心上鐫題名, 中鐫卷次, 下鐫葉次.內封頁鐫"義陵無我子彙輯 道光庚戌重刊"《禪宗正指》分上, 中, 下卷.Xian zhuang, 1 han.Kuang 18.5 x 12.1 gong fen, 9 hang 21 zi, xiao zi shuang hang tong. Bai kou, si zhou shuang bian, dan hei yu wei. Ban xin shang juan ti ming, zhong juan juan ci, xia juan ye ci.Nei feng ye juan "Yiling Wuwozi hui ji Daoguang geng xu chong kan""Chan zong zheng zhi" fen shang, zhong, xia juan.Liu Tishu hui ji ; Liu Yincheng, Liu Yuncheng tong jiao ; Huang Chengshu can ding
Deep characteristics analysis on travel time of emergency traffic
No full textOwing to the rapid development of emergency rescue transportation in cities and the frequent emergencies, demand for emergency rescue is increasing drastically. How to select an emergency rescue route quickly and shorten the rescue travel time under the condition of limited urban road resources is of great significance. Based on the characteristics analysis of emergency rescue, this paper classifies priority levels of different emergency traffic, moreover, the travel times are also analysed with three scenarios: 1) emergency rescue vehicles encountering no queues; 2) encountered queues but lanes available; 3) encountered queues with no available lanes. Related case study shows that model in this paper can effectively shorten travel time of emergency traffic in the route and improve its efficiency.Accepted Author ManuscriptTransport and Plannin
Doplor Sleep: Friendly feedback towards a better hospital soundscape for sleep
No full textRecently in the Netherlands, researchers have found that sleep duration and quality were suboptimal in the hospital. Evidence proved that many modifiable hospitalrelated factors negatively associate with patients' sleep (JAMA Internal Medicine, 2018). The sound factor is the most significant sleep disturbance in the hospital. In this graduation project, collaborating with Reiner de Graaf hospital and Critical Alarms lab, an information exchange system was proposed to raise awareness of sound as sleep disturbance. The system captures the sound-producing events and visualizes them with visually attractive graphics. In this system, we use the smartphone as the sound captor. The recorded sounds are processed locally on the phone and converted into information such as sound level and the category it belongs to (alarm, speech, incidental sounds, or snore). Fitbit is implemented in the system to collect sleep information. To both patients and medical staff, The Doplor sleep system presents the influence of sound on sleep in a friendly and comprehensive way. During this project, a functioning prototype was developed. We have tested its functionality and user experience with the potential users
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