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18,839 results on '"Peter, I"'

1. Acceleration and Focusing Electron/Positron Bunches in Plasma-Dielectric Wakefield Accelerator

Author

Sotnikov, Gennadiy V., Galaydych, Kostyantyn V., Hirshfield, Jay L., Markov, Peter I., and Onishchenko, Ivan M.

Subjects
Physics - Accelerator Physics
Abstract

To mitigate the BBU instability and improve characteristics of accelerated bunches in Dielectric Wakefield Accelerator one can be used the isotropic plasma filling of the transport channel. Here we present the results of analytical and numerical studies of the dynamics of accelerated electron/positron and drive electron bunches under wake acceleration in a plasma DWA (PDWA) with a vacuum channel. The wake field is excited by an electron bunch in a quartz dielectric tube inserted into a cylindrical metal waveguide. The inner region of the dielectric tube is filled with plasma with a vacuum channel along the waveguide axis. At the numerical simulations the energy and spatial characteristics, efficiency, emittance, and energy spread for accelerated positron and electron bunches is studied for different radii of the vacuum channel. The transverse instability of the drive bunch in PDWA is studied analytically and numerically. The analytical studies have discovered the presence of one surface and one bulk eigenwaves, which are absent in corresponding dielectric-loaded waveguide without plasma filling. The main contribution to amplitude of transverse wakefield, responsible for stabilization of transverse motion of bunches, brings the bulk plasma eigenwave. The comparative analysis of the data resulting from analytical studies and the ones obtained by numerical simulation has demonstrated qualitative agreement between the results., Comment: 33 pages, 13 fugures, AAC2024 Worhshop, will be submitted to Nuclear Instruments and Methods in Physics Research

Published
2024

2. Heritage Language Identity Matters: Tracing the Trajectory of a Chinese Heritage Mother and Contested Chinese Dual Language Bilingual Education

Author

Vashti Wai Yu Lee, Lee Her, and Peter I. De Costa

Abstract

This article presents a narrative inquiry of a Chinese heritage mother to theorize and explicate how historical, relational, and spatial processes impacted her negotiation with power and agency in relation to her own heritage language (HL) identity development. A narrative approach enables us to draw on participant counter-stories against master narratives that erase experiences of marginalization of Asians in Asian language education in the United States. We do this through a model of HL identity development (Zhou & Liu, 2022) supplemented by an AsianCrit lens (Iftikar & Museus, 2018). We show the importance of normalizing Chinese as a HL outside of the home in terms of language maintenance as well as the impact such normalization has on the development of an affirmative Chinese HL identity. We add that spaces for such identity development are deeply associated with language programs like dual language bilingual education (DLBE), especially as the number of DLBE opportunities grow in number and in popularity. Thus, language programs, including DLBE, have a responsibility to ensure that the language education they provide address the interests and investments of families with respect to their HL in order to decenter a primary focus on the interests of ethnolinguistic majoritized families.

Published
2024

3. Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index

Author

Xie, Qian, Astudillo, Raul, Frazier, Peter I., Scully, Ziv, and Terenin, Alexander

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Bayesian optimization is a technique for efficiently optimizing unknown functions in a black-box manner. To handle practical settings where gathering data requires use of finite resources, it is desirable to explicitly incorporate function evaluation costs into Bayesian optimization policies. To understand how to do so, we develop a previously-unexplored connection between cost-aware Bayesian optimization and the Pandora's Box problem, a decision problem from economics. The Pandora's Box problem admits a Bayesian-optimal solution based on an expression called the Gittins index, which can be reinterpreted as an acquisition function. We study the use of this acquisition function for cost-aware Bayesian optimization, and demonstrate empirically that it performs well, particularly in medium-high dimensions. We further show that this performance carries over to classical Bayesian optimization without explicit evaluation costs. Our work constitutes a first step towards integrating techniques from Gittins index theory into Bayesian optimization.

Published
2024

4. Asymptotically Optimal Regret for Black-Box Predict-then-Optimize

Author

Tan, Samuel and Frazier, Peter I.

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

We consider the predict-then-optimize paradigm for decision-making in which a practitioner (1) trains a supervised learning model on historical data of decisions, contexts, and rewards, and then (2) uses the resulting model to make future binary decisions for new contexts by finding the decision that maximizes the model's predicted reward. This approach is common in industry. Past analysis assumes that rewards are observed for all actions for all historical contexts, which is possible only in problems with special structure. Motivated by problems from ads targeting and recommender systems, we study new black-box predict-then-optimize problems that lack this special structure and where we only observe the reward from the action taken. We present a novel loss function, which we call Empirical Soft Regret (ESR), designed to significantly improve reward when used in training compared to classical accuracy-based metrics like mean-squared error. This loss function targets the regret achieved when taking a suboptimal decision; because the regret is generally not differentiable, we propose a differentiable "soft" regret term that allows the use of neural networks and other flexible machine learning models dependent on gradient-based training. In the particular case of paired data, we show theoretically that optimizing our loss function yields asymptotically optimal regret within the class of supervised learning models. We also show our approach significantly outperforms state-of-the-art algorithms on real-world decision-making problems in news recommendation and personalized healthcare compared to benchmark methods from contextual bandits and conditional average treatment effect estimation., Comment: 15 pages, 2 figures, 3 tables

Published
2024

5. Understanding solid nitrogen through machine learning simulation

Author

Kirsz, Marcin, Pruteanu, Ciprian G., Cooke, Peter I. C., and Ackland, Graeme J.

Subjects
Physics - Computational Physics, Condensed Matter - Materials Science
Abstract

We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of $N_2$. The potential is trained only on high quality quantum chemical molecule-molecule interactions, no condensed phase information is used. The potential reproduces the experimental phase diagram including the melt curve and the molecular solid phases of nitrogen up to 10 GPa. This demonstrates that many-molecule interactions are unnecessary to explain the condensed phases of $N_2$. With increased pressure, transitions are observed from cubic ($\alpha-N_2$), which optimises quadrupole-quadrupole interactions, through tetragonal ($\gamma-N_2$) which allows more efficient packing, through to monoclinic ($\lambda-N_2$) which packs still more efficiently. On heating, we obtain the hcp 3D rotor phase ($\beta-N_2$) and, at pressure, the cubic $\delta-N_2$ phase which contains both 3D and 2D rotors, tetragonal $\delta^\star-N_2$ phase with 2D rotors and the rhombohedral $\epsilon-N_2$. Molecular dynamics demonstrates where these phases are indeed rotors, rather than frustrated order. The model does not support the existence of the wide range of bondlengths reported for the complex $\iota-N_2$ phase. The thermodynamic transitions involve both shifts of molecular centres and rotations of molecules. We simulate these phase transitions between finding that the onset of rotation is rapid whereas motion of molecular centres is inhibited and the cause of the observed sluggishness of transitions. Routine density functional theory calculations give a similar picture to the potential.

Published
2024

6. VELOcities of CEpheids (VELOCE) I. High-precision radial velocities of Cepheids

Author

Anderson, Richard I., Viviani, Giordano, Shetye, Shreeya S., Mowlavi, Nami, Eyer, Laurent, Palaversa, Lovro, Holl, Berry, Blanco-Cuaresma, Sergi, Kravchenko, Kateryna, Pawlak, Michał, Reyes, Mauricio Cruz, Khan, Saniya, Netzel, Henryka E., Löbling, Lisa, Pápics, Péter I., Postel, Andreas, Roelens, Maroussia, Spetsieri, Zoi T., Thoul, Anne, Zák, Jiří, Bonvin, Vivien, Martin, David V., Millon, Martin, Saesen, Sophie, Wyttenbach, Aurélien, Figueira, Pedro, Marmier, Maxime, Prins, Saskia, Raskin, Gert, and van Winckel, Hans

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

This first VELOCE data release comprises 18,225 high-precision RV measurements of 258 bona fide classical Cepheids on both hemispheres collected mainly between 2010 and 2022, alongside 1161 additional observations of 164 other stars. The median per-observation RV uncertainty is 0.037 km/s, and some reach 0.002 km/s. Non-variable standard stars characterize RV zero-point stability and provide a base for future cross-calibrations. We determined zero-point differences between VELOCE and 31 literature data sets using template fitting and measured linear period changes of 146 Cepheids. Seventy six spectroscopic binary Cepheids and 14 candidates are identified using VELOCE data alone and are investigated in detail in a companion paper (VELOCE II). Several new insights into Cepheid pulsations were obtained, including: a) the most detailed description of the Hertzsprung progression by RVs; b) the identification of double-peaked bumps in the RV curve; c) clear evidence that virtually all Cepheids feature spectroscopic variability signals that lead to modulated RV variability. We identified 36 such stars, of which 4 also exhibit orbital motion. Linear radius variations depend strongly on pulsation period and a steep increase in slope of the $\Delta$R/p versus logP-relation is found near 10d, challenging the existence of a tight relation between Baade-Wesselink projection factors and pulsation periods. We investigated the accuracy of RV time series measurements, v$_\gamma$, and RV amplitudes published in Gaia's DR3 and determined an average offset of 0.65 \pm 0.11 km/s relative to VELOCE. We recommend adopting a single set of template correlation parameters for distinct classes of large-amplitude variable stars to avoid systematic offsets in v$_\gamma$ among stars belonging to the same class. Peak-to-peak amplitudes of Gaia RVs exhibit significant (16%) dispersion compared to VELOCE. [abridged], Comment: A&A in press, 46 pages, 35 figures, 20 tables. Some data only available via the CDS at publication. VELOCE DR1 data will be made public in FITS format via zenodo.org at DOI: 10.5281/zenodo.10793507 upon publication of the paper in A&A

Published
2024
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7. Strategizing from the COVID-19 Pandemic Experience on the Advancement in Virtual Learning in Nigeria

Author

Ramsey-Soroghaye, Blessing N., Emejuru, Peter I., Solomon-Zacchaeus, Ibiene H., and Abur, William

Abstract

Educational systems are faced with modifying and re-modifying activities that foster the improvement of better learning over the years. In-person learning, which requires the physical presence of both the student and teacher in a particular place and at a particular period of time, used to be what was best and most obtainable in most Nigerian public institutions of learning. After the global pandemic in 2020, strategizing and re-strategizing of learning cultures through virtual learning became inevitable. This qualitative study utilized semi-structured interviews to conduct in-depth interviews with 20 students. WhatsApp was the commonly mentioned tool used in virtual learning as found in this study. Poor facilities, poverty, ignorance, incompetency, and inadequate virtual learning training were the indicated hindrances to the advancement of virtual learning in the Nigerian Educational Sector. This study suggested the need for trainings on the use of the internet and other facilities, the upgrading and maintenance of these facilities, funding of the educational sector, and payment of bursary to students to enable them purchase data for virtual learning innovation in institutions of higher learning in Nigeria.

Published
2023

8. Impact of Building Plan Shape on Natural Ventilation Efficiency for Thermal Comfort in Educational Facilities: A Post-occupancy Evaluation

Author

Mba, Emeka J., Okeke, Francis O., Oforji, Peter I., Ozigbo, Ikechukwu W., Emmanuel, Ezema C., Ozigbo, Chinelo A., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, and Strauss, Eric, editor

Published
2025
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11. Bayesian Optimization of Function Networks with Partial Evaluations

Author

Buathong, Poompol, Wan, Jiayue, Astudillo, Raul, Daulton, Samuel, Balandat, Maximilian, and Frazier, Peter I.

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

Bayesian optimization is a powerful framework for optimizing functions that are expensive or time-consuming to evaluate. Recent work has considered Bayesian optimization of function networks (BOFN), where the objective function is given by a network of functions, each taking as input the output of previous nodes in the network as well as additional parameters. Leveraging this network structure has been shown to yield significant performance improvements. Existing BOFN algorithms for general-purpose networks evaluate the full network at each iteration. However, many real-world applications allow for evaluating nodes individually. To exploit this, we propose a novel knowledge gradient acquisition function that chooses which node and corresponding inputs to evaluate in a cost-aware manner, thereby reducing query costs by evaluating only on a part of the network at each step. We provide an efficient approach to optimizing our acquisition function and show that it outperforms existing BOFN methods and other benchmarks across several synthetic and real-world problems. Our acquisition function is the first to enable cost-aware optimization of a broad class of function networks., Comment: 34 pages, 15 figures, 3 tables

Published
2023

12. Modeling the Risk of In-Person Instruction during the COVID-19 Pandemic

Author

Liu, Brian, Zhang, Yujia, Henderson, Shane G., Shmoys, David B., and Frazier, Peter I.

Subjects
Statistics - Applications, Mathematics - Optimization and Control, Physics - Physics and Society, Quantitative Biology - Quantitative Methods, Statistics - Methodology
Abstract

During the COVID-19 pandemic, safely implementing in-person indoor instruction was a high priority for universities nationwide. To support this effort at the University, we developed a mathematical model for estimating the risk of SARS-CoV-2 transmission in university classrooms. This model was used to evaluate combinations of feasible interventions for classrooms at the University during the pandemic and optimize the set of interventions that would allow higher occupancy levels, matching the pre-pandemic numbers of in-person courses. Importantly, we determined that requiring masking in dense classrooms with unrestricted seating with more than 90% of students vaccinated was easy to implement, incurred little logistical or financial cost, and allowed classes to be held at full capacity. A retrospective analysis at the end of the semester confirmed the model's assessment that the proposed classroom configuration would be safe. Our framework is generalizable and was used to support reopening decisions at Stanford University. In addition, our framework is flexible and applies to a wide range of indoor settings. It was repurposed for large university events and gatherings and could be used to support planning indoor space use to avoid transmission of infectious diseases across various industries, from secondary schools to movie theaters and restaurants.

Published
2023

13. Becoming Uyghur Elites: How Uyghur Women in a Mainstream Chinese University Negotiate Their Gendered Identities

Author

Yaqiong Cui and Peter I. De Costa

Abstract

Multilingual learners confront challenges not only in mastering new languages but also in forming new identities. Guided by the investment model, we traced the learning of Chinese and English of two Uyghur women who attended a coastal Chinese university and investigated how they navigated the Chinese mainstream education system to university level. Findings of this ethnographic work revealed that moving from their less developed hometown to a major city, the participants expanded and enriched their repertoire of symbolic and material resources on which they could rely to effect more powerful social memberships and negotiate their educated Uyghur identities. Their Chinese and English language learning journey and the educational experiences in the host community also changed how Uyghur women perceive their future possibilities. Their struggles and agency in their journey were also highlighted.

Published
2024
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14. Critical Teacher Education for Equitable Learning in Multilingual Classrooms: A Possible Way Forward

Author

Laxmi Prasad Ojha, Jennifer Burton, and Peter I. De Costa

Abstract

Addressing the ongoing calls to reform teacher education to prepare future teachers to serve students from diverse backgrounds, this introduction reviews recent developments in teacher education to situate our thematic issue on critical teacher education for equitable learning in multilingual classrooms. The five empirical papers and two commentaries included in this issue focus on the connection between language, power, and critical consciousness to address equity concerns in teacher education as it pertains to supporting multilingual learners, asking: how do teacher education programs prepare teachers to work with diverse students in schools where there exists a long-standing history of marginalization and discrimination based on racial, economic, social backgrounds? In this introductory paper, we discuss the contributions of the papers included in the issue and share a vision for new ways for reimagining teacher education for multilingual learners.

Published
2024
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15. Decolonizing Higher Education Pedagogy: Insights from Critical, Collaborative Professionalism in Practice

Author

Peter I. De Costa, Laxmi Prasad Ojha, Vashti Wai Yu Lee, and D. Philip Montgomery

Abstract

Building on the long-standing tradition of challenging oppression and questioning whose interests are being served in the field of language education, we report on a study that involved a group of U.S.-based graduate students who collaborated with a ninth-grade English teacher in Nepal. The study comes out of a larger project that sought to internationalize the curriculum of a graduate educational linguistics course at a U.S. university. At the heart of this internationalizing curriculum endeavour was a commitment to expose graduate students in the U.S. to the issues of language teaching outside of the U.S. This was done through co-designing of a unit of lessons, with six graduate students meeting virtually with their teacher partner, Ditya, in Nepal over the course of a semester. The graduate students and Ditya constitute our research participants. The graduate student participants learned about the need to develop pedagogical materials that were relevant to the local context in Nepali classroom, and not attempt to transplant a Western-centric curriculum onto the Nepali classroom. In keeping with recent calls to decolonize higher education, we illustrate how critical theory in general and decolonizing pedagogy in particular can be infused into a U.S. graduate curriculum by drawing on the rich, indigenous knowledge and resources of a teacher collaborator from the Global South. We do this by reporting how this critical, decolonizing goal was realized through collaborative professionalism, which is characterized by the sharing of knowledge, skills, and experience to improve student achievement, reflection, dialogue and collective responsibility.

Published
2024
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17. Unresolved Rossby and gravity modes in 214 A and F stars showing rotational modulation

Author

Henriksen, Andreea I., Antoci, Victoria, Saio, Hideyuki, Grundahl, Frank, Kjeldsen, Hans, Van Reeth, Timothy, Bowman, Dominic M., Pápics, Péter I., De Cat, Peter, Krüger, Joachim, Andersen, M. Fredslund, and Pallé, P. L.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Here we report an ensemble study of 214 A- and F-type stars observed by \textit{Kepler}, exhibiting the so-called \textit{hump and spike} periodic signal, explained by Rossby modes (r~modes) -- the \textit{hump} -- and magnetic stellar spots or overstable convective (OsC) modes -- the \textit{spike} -- respectively. We determine the power confined in the non-resolved hump features and find additional gravity~modes (g~modes) humps always occurring at higher frequencies than the spike. Furthermore, we derive projected rotational velocities from FIES, SONG and HERMES spectra for 28 stars and the stellar inclination angle for 89 stars. We find a strong correlation between the spike amplitude and the power in the r and g~modes, which suggests that both types of oscillations are mechanically excited by either stellar spots or OsC modes. Our analysis suggests that stars with a higher power in $m=1$ r~modes humps are more likely to also exhibit humps at higher azimuthal orders ($m$ = 2, 3, or 4). Interestingly, all stars that show g~modes humps are hotter and more luminous than the observed red edge of the $\delta$ Scuti instability strip, suggesting that either magnetic fields or convection in the outer layers could play an important role., Comment: 18 pages, 19 figures

Published
2023
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18. Developments and Further Applications of Ephemeral Data Derived Potentials

Author

Salzbrenner, Pascal T., Joo, Se Hun, Conway, Lewis J., Cooke, Peter I. C., Zhu, Bonan, Matraszek, Milosz P., Witt, William C., and Pickard, Chris J.

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

Machine-learned interatomic potentials are fast becoming an indispensable tool in computational materials science. One approach is the ephemeral data-derived potential (EDDP), which was designed to accelerate atomistic structure prediction. The EDDP is simple and cost-efficient. It relies on training data generated in small unit cells and is fit using a lightweight neural network, leading to smooth interactions which exhibit the robust transferability essential for structure prediction. Here, we present a variety of applications of EDDPs, enabled by recent developments of the open-source EDDP software. New features include interfaces to phonon and molecular dynamics codes, as well as deployment of the ensemble deviation for estimating the confidence in EDDP predictions. Through case studies ranging from elemental carbon and lead to the binary scandium hydride and the ternary zinc cyanide, we demonstrate that EDDPs can be trained to cover wide ranges of pressures and stoichiometries, and used to evaluate phonons, phase diagrams, superionicity, and thermal expansion. These developments complement continued success in accelerated structure prediction., Comment: 22 pages, 15 figures

Published
2023
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22. qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization

Author

Astudillo, Raul, Lin, Zhiyuan Jerry, Bakshy, Eytan, and Frazier, Peter I.

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Preferential Bayesian optimization (PBO) is a framework for optimizing a decision maker's latent utility function using preference feedback. This work introduces the expected utility of the best option (qEUBO) as a novel acquisition function for PBO. When the decision maker's responses are noise-free, we show that qEUBO is one-step Bayes optimal and thus equivalent to the popular knowledge gradient acquisition function. We also show that qEUBO enjoys an additive constant approximation guarantee to the one-step Bayes-optimal policy when the decision maker's responses are corrupted by noise. We provide an extensive evaluation of qEUBO and demonstrate that it outperforms the state-of-the-art acquisition functions for PBO across many settings. Finally, we show that, under sufficient regularity conditions, qEUBO's Bayesian simple regret converges to zero at a rate $o(1/n)$ as the number of queries, $n$, goes to infinity. In contrast, we show that simple regret under qEI, a popular acquisition function for standard BO often used for PBO, can fail to converge to zero. Enjoying superior performance, simple computation, and a grounded decision-theoretic justification, qEUBO is a promising acquisition function for PBO., Comment: In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023

Published
2023

23. Ultrasonic Study of Water Adsorbed in Nanoporous Glasses

Author

Ogbebor, Jason, Valenza, John J., Ravikovitch, Peter I., Karunarathne, Ashoka, Muraro, Giovanni, Lebedev, Maxim, Gurevich, Boris, Khalizov, Alexei F., and Gor, Gennady Y.

Subjects
Condensed Matter - Soft Condensed Matter, Physics - Chemical Physics, Physics - Geophysics
Abstract

Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we performed water sorption experiments on two nanoporous glass samples while concomitantly measuring the speed of longitudinal and shear ultrasonic waves in these samples. These measurements yield the longitudinal and shear moduli of the water laden nanoporous glass as a function of relative humidity that we utilized in the Gassmann theory to infer the bulk modulus of the confined water. This analysis shows that the bulk modulus (inverse of compressibility) of confined water is noticeably higher than that of the bulk water at the same temperature. Moreover, the modulus exhibits a linear dependence on the Laplace pressure. The results for water, which is a polar fluid, agree with previous experimental and numerical data reported for non-polar fluids. This similarity suggests that irrespective of intermolecular forces, confined fluids are stiffer than bulk fluids. Accounting for fluid stiffening in nanopores may be important for accurate interpretation of wave propagation measurements in fluid-filled nanoporous media, including in petrophysics, catalysis, and other applications, such as in porous materials characterization.

Published
2023
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24. An Estimation Method of the Manufacturing Process' Effect on Iron Losses

Author

SCUTARU, G., GAVRILA, H., and PETER, I.

Subjects
design engineering, energy efficiency, induction motors, magnetic circuits, magnetic losses, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer engineering. Computer hardware, TK7885-7895
Abstract

More than 60% of industrial electricity consumption is made by electrical drives with induction motors. In 2008, by IEC 60034-30, the International Electrotechnical Commission defined the efficiency classes of induction motors namely: IE1, IE2 and IE3. The IE4 was defined in 2010 by IEC 60034-3. From 1 January 2015, the induction motors with a rated output of 7.5-375 kW shall not be less efficient than the IE3 class (Premium Efficiency Class). In order to obtain IE3 motors, manufacturers need to have a design method which takes into account the influence of the technological process on the properties of materials used; specially magnetic properties. This paper presents a new method to estimate the iron losses taking into account the effect of the mechanical cutting on the specific iron losses of the sheets. The method presented enables more accurate determination of the iron losses taking into account the effect of the punching process on the magnetic properties of sheets without a significant increase of the computational time. The case of M400 iron sheets was analyzed.

Published
2014
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25. Improved Mixed Estimator Using Two Auxiliary Variables For Full Extreme Maximum And Minimum Values In Single Phase Sampling

Author

Timothy O. Olatayo, Peter N. Madu, and Peter I. Ogunyinka

Subjects
auxiliary variables, extreme values, mean square error, ratio estimators, regression estimator, single-phase sampling, Probabilities. Mathematical statistics, QA273-280
Abstract

The use of multiple auxiliary variables has been established to improve precision in the estimators of ratio, regression and product respectively. However, the presence of extreme values in the distribution could annul such efficiency Olatayo et al. (2020). Extreme values could be small or minimum, large or maximum values. This study had developed a ratio-cum-regression estimator with two auxiliary variables, correlation coefficient and coefficient of variation under two types of extreme values in the distribution. This study considers full extreme value cases which assumed that both the study and two auxiliary variables had extreme values present in their distributions. Theoretical, empirical and percentage relative efficiency analyses were carried out for Full High and Maximum Extreme Values (FHMaEV) and Full Low and Minimum Extreme Values cases (FLMiEV). The analysis showed that the developed estimator is efficient over the reviewed estimators.

Published
2024
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26. Smooth Non-Stationary Bandits

Author

Jia, Su, Xie, Qian, Kallus, Nathan, and Frazier, Peter I.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Optimization and Control, Mathematics - Statistics Theory
Abstract

In many applications of online decision making, the environment is non-stationary and it is therefore crucial to use bandit algorithms that handle changes. Most existing approaches are designed to protect against non-smooth changes, constrained only by total variation or Lipschitzness over time. However, in practice, environments often change {\em smoothly}, so such algorithms may incur higher-than-necessary regret. We study a non-stationary bandits problem where each arm's mean reward sequence can be embedded into a $\beta$-H\"older function, i.e., a function that is $(\beta-1)$-times Lipschitz-continuously differentiable. The non-stationarity becomes more smooth as $\beta$ increases. When $\beta=1$, this corresponds to the non-smooth regime, where \cite{besbes2014stochastic} established a minimax regret of $\tilde \Theta(T^{2/3})$. We show the first separation between the smooth (i.e., $\beta\ge 2$) and non-smooth (i.e., $\beta=1$) regimes by presenting a policy with $\tilde O(k^{4/5} T^{3/5})$ regret on any $k$-armed, $2$-H\"older instance. We complement this result by showing that the minimax regret on the $\beta$-H\"older family of instances is $\Omega(T^{(\beta+1)/(2\beta+1)})$ for any integer $\beta\ge 1$. This matches our upper bound for $\beta=2$ up to logarithmic factors. Furthermore, we validated the effectiveness of our policy through a comprehensive numerical study using real-world click-through rate data., Comment: Accepted by ICML 2023

Published
2023

27. Forecasting subcritical cylinder wakes with Fourier Neural Operators

Author

Renn, Peter I, Wang, Cong, Lale, Sahin, Li, Zongyi, Anandkumar, Anima, and Gharib, Morteza

Subjects
Physics - Fluid Dynamics, Computer Science - Machine Learning
Abstract

We apply Fourier neural operators (FNOs), a state-of-the-art operator learning technique, to forecast the temporal evolution of experimentally measured velocity fields. FNOs are a recently developed machine learning method capable of approximating solution operators to systems of partial differential equations through data alone. The learned FNO solution operator can be evaluated in milliseconds, potentially enabling faster-than-real-time modeling for predictive flow control in physical systems. Here we use FNOs to predict how physical fluid flows evolve in time, training with particle image velocimetry measurements depicting cylinder wakes in the subcritical vortex shedding regime. We train separate FNOs at Reynolds numbers ranging from Re = 240 to Re = 3060 and study how increasingly turbulent flow phenomena impact prediction accuracy. We focus here on a short prediction horizon of ten non-dimensionalized time-steps, as would be relevant for problems of predictive flow control. We find that FNOs are capable of accurately predicting the evolution of experimental velocity fields throughout the range of Reynolds numbers tested (L2 norm error < 0.1) despite being provided with limited and imperfect flow observations. Given these results, we conclude that this method holds significant potential for real-time predictive flow control of physical systems., Comment: 12 pages, 6 figures

Published
2023

28. Structures, processes and outcomes between first referral and referral hospitals in low-income and middle-income countries: a secondary preplanned analysis of the FALCON and ChEETAh randomised trials

Author

Rajeev Sharma, Neha Mishra, Simon Cousens, Sanjay Gupta, Thomas Pinkney, Neil Smart, Jonathan Cook, David Jayne, Hemanth Kumar, Peter Brocklehurst, Mohammed Bashir, Dmitri Nepogodiev, Adesoji O Ademuyiwa, Philip Alexander, Laura Magill, Mark Monahan, Rachel Moore, Stephen Tabiri, Joseph Yorke, Dion Morton, Aneel Bhangu, Bryar Kadir, Naveen Sharma, Punam Mistry, Joshua Arthur, Muneer A Malik, Tracy Roberts, Elisee Rwagahirima, Christian Urimubabo, Ewen Harrison, Vijay Kumar, Julia Brown, Pollyanna Hardy, Amit Mahajan, Pratik Solanki, James Glasbey, Himani Gupta, Omar Omar, Joana Simoes, Sivesh K Kamarajah, Adesoji Ademuyiwa, Felix Alakaloko, Olumide Elebute, Omolara Faboya, Justina Seyi-Olajide, Anita Thomas, David Lissauer, Zainab Imam, George Ihediwa, Zainab O Imam, Felix M Alakaloko, Pradeep Zechariah, Suraj Surendran, Olatunji O Lawal, Mohammed Adnan, Savleen Kaur, Faustin Ntirenganya, JC Allen Ingabire, Lawani Ismaïl, Emmy Runigamugabo, Djifid Morel Seto, Paul Wondoh, Charles Dally, Kwabena Agbedinu, Florence Dedey, Enoch Tackie, Frank Enoch Gyamfi, Anthony Davor, Akinlabi Ajao, Omobolaji Ayandipo, Olalekan Ajai, Mobolaji Oludara, Muhammad Daniyan, Danjuma Sale, Lawal Abdullahi, Olabisi Osagie, Adedeji Fatuga, Muzzammil Abdullahi, Manish Pathak, Prashant Singh, Rita Jain, Kwaku Boakye-Yiadom, Kazeem Atobatele, Ayokunle Ogunyemi, Olabode Oshodi, Christopher Bode, Omobolaji O Ayandipo, Akinlabi E Ajao, Godwin Akaba, Gabriella Hyman, Deepak Singh, Olukemi Akande, Sivesh Kathir Kamarajah, Naseem Akhtar, José A Flores, Donna Smith, Olatunji Lawal, Hadijat Olaide Raji, Zafar Khan, Matthew Francis, Emmanuel Williams, Pardeep Kumar, Oliver Samuel, María Paz Muñoz, Arun Chaturvedi, Sameer Gupta, Puneet Prakash, John Raphael, Funmilola Wuraola, Olalekan Olasehinde, Murlidhar V Pai, Deepak Jain, Anwar Sadat Seidu, Victor Ifeanyichukwu Modekwe, Jideofor Okechukwu Ugwu, Lukmon Amosu, Akan Inyang, Michael Amoah, Boateng Nimako, Dhruva Ghosh, Neil Winkles, Olabisi O Osagie, Karolin Kroese, Olubunmi Ogein, Mustapha Yakubu, Vasanth Mark Samuel, Cecil Thomas, Enono Yhoshu, Vishal Michael, William Bhatti, Swati Daniel, Jyoti Dhiman, Atul Suroy, Christopher O Bode, George C Ihediwa, Adaiah Soibi-Harry, Benedetto Osunwusi, Elizabeth Li, Sonia Mathai, Deepak Singla, Farhanul Huda, Aisha Mustapha, Anisah Yahya, Samuel Mensah, Puneet Pareek, Bernard Ofori, Souliath Lawani, Oluwafunmilayo Adeniyi, Opeyemi Rebecca Akinajo, Richard Ofosu-Akromah, Olumide Adeniyi, Adewale O. Adisa, Natacha Boumas, Fareeda Galley, Frank Enoch Gyamfi Parvez D Haque, Antonio Ramos de la Medina, Chukwuma Okereke, Ronald Tubasime, Felicity Brant, Sohini Chakrabortee, Parvez D Haque, Emily Heritage, Carmela Lapitan, Rachel Lillywhite, Pierre Sodonougbo, Pamphile Assouto, Michel Fiogbe, Houenoukpo Koco, Serge Metchinhoungbe, Hodonou Sogbo, Hulrich Behanzin, Yannick Tandje, Sosthène Kangni, Cyrile Kpangon, Marcelin Akpla, Hugues Herve Chobli, Blaise Kovohouande, Gérard Agboton, Rene Ahossi, Raoul Baderha Ngabo, Nathan Bisimwa, Covalic Melic Bokossa Kandokponou, Mireille Dokponou, Francis Moïse Dossou, Corinne Dzemta, Antoine Gaou, Roland Goudou, Emmanuel Hedefoun, Sunday Houtoukpe, Felix Kamga, Eric Kiki- Migan, Ismaïl Lawani, René Loko, Afissatou Moutaïrou, Pencome Ogouyemi, Fouad Soumanou, Pia Tamadaho, Mack-Arthur Zounon, Luke Aniakwo Adagrah, Bin Baaba Alhaji Alhassan, Mabel Pokuah Amoako-Boateng, Anthony Baffour Appiah, Alvin Asante-Asamani, Benedict Boakye, Samuel A Debrah, Donald Enti, Rahman Adebisi Ganiyu, Patience Koggoh, Richard Kpankpari, Isabella Naa M. Opandoh, Meshach Agyemang Manu, Maison Patrick Opoku Manu, Martin Tangnaa Morna, John Nkrumah, Michael Nortey, Emmanuel Owusu Ofori, Elizaberth Mercy Quartson, Esther Adjei-Acquah, Eric Agyemang Vera Agyekum, Rebecca Adjeibah Akesseh, Forster Amponsah-Manu, Ato Oppong Acquah, Leslie Issa Adam-Zakariah, Esther Asabre, Ruby Acheampong Boateng, Barbara Koomson, Ataa Kusiwaa, Emmanuel Yaw Twerefour, James Ankomah, Frank Assah-Adjei, Anthony Appiah Boakye, Godfred Fosu, Godwin Serbeh, Kofi Yeboah Gyan, Isaac Omane Nyarko, Zelda Robertson, Ralph Armah, Christopher Asare, Delali Akosua Gakpetor, Victoria Sena Gawu, Ambe Obbeng, Doris Ofosuhene, Dorcas Osei-Poku, Diana Puozaa, Arkorful Ebenezer Temitope, Regina Acquah, James Amoako, Akosua Dwamena Appiah, Mark Aseti, Charles Banka, Samuel Dadzie, Derick Essien, Romeo Hussey, Jemima Kwarteng, Naa Anyekaa Sowah, Grace Yeboah, Cynthia Yeboah, Kwame Gyambibi Addo, Enoch Appiah Akosa, Percy Boakye, Christian Larbi Coompson, Brian Gyamfi, Bismark Effah Kontor, Christian Kyeremeh, Ruth Manu, Elijah Mensah, Friko Ibrahim Solae, Gideon Kwasi Toffah, Dorcas Otuo Acheampong, Jane Acquaye, Michael Adinku, Anita Eseenam Agbeko, Emmanuel Gyimah Amankwa, George Amoah, Juliana Appiah, Alex Ayim, Emmanuel Kafui Ayodeji, Jonathan Boakye-Yiadom, Edward Amoah Boateng, Christian Kofi Gyasi-Sarpong, Naabo Nuhu Noel Hamidu, Iddrisu Haruna, Naa Kwarley, Agbenya Kobla Lovi, Bertina Beauty Nyadu, Dominic Opoku, Anita Osabutey, Robert Sagoe, Samuel Tuffour, Yaa Tufour, Francis Akwaw Yamoah, Abiboye Cheduko Yefieye, Nii Armah Adu-Aryee, Faisal Adjei, Erica Akoto, Elikem Ametefe, Joachim Kwaku Amoako, Godsway Solomon Attepor, George Darko Brown, Benjamin Fenu, Philemon Kwame Kumassah, David Olatayo Olayiwola, Theodore Wordui, Nelson Agboadoh, Fatao Abubakari, Cletus Ballu, Charles Gyamfi Barimah, Guy Casskey Boateng, Prosper Tonwisi Luri, Abraham Titigah, Frank Owusu, Raphael Adu-Brobbey, Abdul-Hamid Labaran, Junior Atta Owusu, Vivian Adobea, Amos Bennin, Fred Dankwah, Stanley Doe, Ruth Sarfo Kantanka, Ephraim Kobby, Kennedy Kofi Korankye Hanson Larnyor, Edwin Osei, Prince Yeboah Owusu, Clement Ayum Sie-Broni, Marshall Zume, Francis Atindaana Abantanga, Darling Ramatu Abdulai, Daniel Kwesi Acquah, Emmanuel Ayingayure, Imoro Osman, Sheba Kunfah, Gbana Limann, Shamudeen Alhassan Mohammed, Sheriff Mohammed, Yakubu Musah, Emmanuel Abem Owusu, Abdul-Hafiz Saba, Edwin Mwintiereh Ta-ang Yenli, Arun Gautham, Alice Hepzibah, Grace Mary, Dimple Bhatti, Karan Bir, Tapasya Dhar, Sunita Goyal, Goyal Ankush, Monika Hans, Parvez Haque, Samuel Konda, Anil Luther, Shalini Makkar, Kavita Mandrelle, Partho Mukherjee, Reuben Rajappa, Ravinder Thind, Alen Thomas, Arti Tuli, Sreejith Veetil, Esther Daniel Mark Jesudason, K Priyadarshini, Latha Madankumar, Rohin Mittal, Ida Nagomy, Rajesh Selvakumar, Bharat Shankar, Moonish Sivakumar, Rajeevan Sridhar, Devabalan Titus, Manisha Aggarwal, Parth Dhamija, Vinoth Kanna, Ashwani Kumar, Gurtaj Singh, Josy Thomas, Amos Dasari, Priya Jacob, Elizabeth Kurien, Arpit Mathew, Danita Prakash, Anju Susan, Rose Varghese, Rahul Alpheus, Ashish Choudhrie, Nitin Peters, Subrat Raul, Rakesh Vakil, Wenceslao Ángeles Bueno, Francisco Barbosa Camacho, Aldo Bernal Hernández, Ana Bogurin Arellano, Edgar Cortes Torres, Clotilde Fuentes Orozco, Erick González García de Rojas, Alejandro González Ojeda, Bertha Guzmán Ramírez, Michel Hernández Valadez, Diego Luna Acevedo, Rubén Morán Galaviz, Oscar Olvera Flores, José Pérez Navarro, Kevin Pintor Belmontes, Fernando Ramirez Marbello, Luis Ramírez-González, Laura Reyes Aguirre, Ramona Rojas García, Eduardo Valtierra Robles, Reyes Cervantes Ortiz, Gonzalo Hernandez Gonzalez, Rosa Hernandez Krauss, Luis Hernández Miguelena, Marco Hurtado Romero, Isaac Baltazar Gomez, Celina Cuellar Aguirre, Alejandro Cuevas Avendaño, Luis Dominguez Sansores, Hector Ortiz Mejia, Laura Urdapilleta Gomez del Campo, Claudia Caballero Cerdan, David Dominguez Solano, Rafael Toriz Garcia, Mariana Barreto Gallo, Ana Cortes Flores, Alejandro Gonzalez Ojeda, Monica Jimenez Velasco, Rozana Reyes Gamez, Roque Lincona Menindez, Alberto Navarrete Peón, Irani Durán Sánchez, Diana Gonzalez Vazquez, Maria Martínez Lara, Laura Martinez Perez Maldonado, Alejandra Nayen Sainz de la Fuente, Antonio Ramos De la Medina, Khadija Ado, Mohammed Aliyu, Lofty-John Anyanwu, Mahmoud Magashi, Abubakar Muhammad, Saminu Muhammad, Bello Muideen, Idris Takai, Onyekachi Ukata, Opeoluwa Adesanya, David Awonuga, Olushola Fasiku, Chidiebere Ogo, Moruf Abdulsalam, Abimbola Adeniran, Grace Eke, Esther Momson, Francisca Nwaenyi, Olufunmilade Omisanjo, Yusuf Oshodi, Yemisi Oyewole, Omotade Salami, Omolara Williams, Victoria Adeleye, Opeyemi Akinajo, David Akinboyewa, Iyabo Alasi, Oluwole Atoyebi, Olanrewaju Balogun, Orimisan Belie, Andrew Ekwesianya, Francis Ezenwankwo, Adesola Jimoh, Jubril Kuku, Oluwaseun Ladipo- Ajayi, Ayomide Makanjuola, Olayanju Mokwenyei, Samuel Nwokocha, Rufus Ojewola, Abraham Oladimeji, Thomas Olajide, Oluwaseun Oluseye, Aloy Ugwu, Ochomma Egwuonwu, Okechukwu Ekwunife, Victor Modekwe, Chukwuemeka Okoro, Chisom Uche, Kenneth Ugwuanyi, Chuka Ugwunne, Akeem Adeleke, Wilson Adenikinju, Akinfolarin Adepiti, Adewale Aderounmu, Abdulhafiz Adesunkanmi, Adewale Adisa, Samuel Ajekwu, Olusegun Ajenjfuja, Jerrie Akindojutimi, Akinbolaji Akinkuolie, Olusegun Alatise, Olubukola Allen, Micheal Archibong, Olukayode Arowolo, Deborah Ayantona, Ademola Ayinde, Olusegun Badejoko, Tajudeen Badmus, Amarachukwu Etonyeaku, Emeka Igbodike, Omotade Ijarotimi, Adedayo Lawal, Fayowole Nana, Tunde Oduanafolabi, Olaniyi Olayemi, Stephen Omitinde, Owolabi Oni, Chigozie Onyeze, Ernest Orji, Adewale Rotimi, Abdulkadir Salako, Olufemi Solaja, Oluwaseun Sowemimo, Ademola Talabi, Mohammed Tajudeen, Francis Adebayo, Oseremen Aisuodionoe- Shadrach, Lazarus Ameh, Ndubuisi Mbajiekwe, Felix Ogbo, Samson Olori, Samuel Sani Abu Sadiq, Nancy Tabuanu, Martins Uanikhoba, Godwin Chiejina, Ekpo Edet, Mary Isa, Faith Iseh, Adams Marwa, Sunday Ogbeche, Edima Olory, Gabriel Udie, Joseph Udosen, Usang Usang, Olukayode Abayomi, Rukiyat Abdus-Salam, Sikiru Adebayo, Olanrewaju Amusat, Kelvin Egbuchulem, Hyginus Ekwuazi, Peter Elemile, Taiwo Lawal, Solomon Olagunju, Peter Osuala, Bamidele Suleman, Augustine Takure, Lukman Abdur-Rahman, Nurudeen Adeleke, Muideen Adesola, Rafiat Afolabi, Sulaiman Agodirin, Isiaka Aremu, Jibril Bello, Saheed Lawal, Abdulwahab Lawal, Hadijat Raji, Olayinka Sayomi, Asimiyu Shittu, Jude Ede, Sebastian Ekenze, Vincent Enemuo, Matthew Eze, Uchechukwu Ezomike, Emmanuel Izuka, Okezie Mbadiwe, Ngozi Mbah, Uba Ezinne, Iweha Ikechukwu, Okoi Nnyonno, Philemon Okoro, Igwe Patrick, Oriji Vaduneme, Abhulimen Victor, Salathiel Kanyarukiko, Francine Mukaneza, Deborah Mukantibaziyaremye, Aphrodis Munyaneza, Gibert Ndegamiye, Ronald Tubasiime, Moses Dusabe, Emelyne Izabiriza, Hope Lydia Maniraguha, Christophe Mpirimbanyi, Josiane Mutuyimana, Olivier Mwenedata, Francine Uwizeyimana, Job Zirikana, Aime Dieudonne Hirwa, Elysee Kabanda, Salomee Mbonimpaye, Christine Mukakomite, Piolette Muroruhirwe, Georges Bucyibaruta, Gisele Juru Bunogerane, Sosthene Habumuremyi, Jean de Dieu Haragirimana, Alphonsine Imanishimwe, Violette Mukanyange, Emmanuel Munyaneza, Emmanuel Mutabazi, Isaie Ncogoza, Jeannette Nyirahabimana, Mary Augusta Adams, Richard Crawford, Chikwendu Jeffrey Ede, Maria Fourtounas, Morapedi Kwati, Mpho Nosipho Mathe, Ncamsile Anthea Nhlabathi, Hlengiwe Samkelisiwe Nxumalo, Paddy Pattinson, Nnosa Sentholang, Mmule Evelyn Sethoana, Maria Elizabeth Stassen, Laura Thornley, Cheryl Birtles, Mathete Ivy, Cynthia Mbavhalelo, Zain Ally, Abdus-sami Adewunmi, Maria Picciochi, Michael Bahrami-Hessari, Didier Ahogni Benin, Aristide Ahounou, K. Alassan Boukari, Oswald Gbehade, Thierry K Hessou, Sinama Nindopa, M.J. Bienvenue Nontonwanou, Nafissatou Orou Guessou, Arouna Sambo, Sorekou Victoire Tchati, Affisatou Tchogo, Semevo Romaric Tobome, Parfait Yanto, Isidore Gandaho, Armel Hadonou, Simplice Hinvo, Montcho Adrien Hodonou, Sambo Bio Tamou, Marie-Claire Kouroumta, Enrif Malade, Anne stredy Mkoh Dikao, Joel Nzuwa Nsilu, Nathan Bisimwa Mitima, Cyrille Kpangon, Stephane Laurent Loupeda, Mamonde Victorin Agbangla, Sena Emmanuel Hedefoun, Thierry Mavoha, Juvenal Ngaguene, Janvier Rugendabanga, Rish Romaric Soton, Martin Totin, Mouhamed Agbadebo, Irene Akpo, Hubert Dewamon, Martin Djeto, Aissatou Hada, Monsede Hollo, Albert Houndji, Anasthasie Houndote, Sylvestre Hounsa, Expedit Kpatchassou, Hugues Yome, Mohamed Moussa Alidou, Bonheur Dossou Yovo, Robert Guinnou, Souleymane Hamadou, Nabil Moussa, Boniface Cakpo, Lolyta Etchisse, Emery Hatangimana, Moise Muhindo, Katia Sanni, Agossou Barthelemy Yevide, Hermann Agossou, Fiston Basirwa Musengo, Bill Armstrong Alia, Arnaud Alitonou, Lucien Agbanda, Julien Attinon, Marcel Gbassi, Nounagnon Rene Hounsou, Derick Esssien, Yakubu Mustapha, Kojo Nunoo-Ghartey, Luke A Aniakwo, Margarey N M Adjei, Yvonne Adofo-Asamoah, Meshach M Agyapong, Thomas Agyen, Baba A B Alhassan, Mabel P Amoako-Boateng, Josephine Ashong, Joseph K Awindaogo, Benjamin B Brimpong, Makafui S C J K Dayie, Wendy W Ghansah, Jude E Gyamfi, Vincent Kudoh, Philip Mensah, Isabella N Morkor Opandoh, Martin T Morna, Emelia Odame, Emmanuel O Ofori, Sandra Quaicoo, Elizabert M Quartson, Cynthia Teye-Topey, Makafui Yigah, Safia Yussif, Vera O Agyekum-Gyimah, Eric Agyemang, Arko Akoto- Ampaw, Temitope E Arkorful, Moses A Dokurugu, Nanabanyin Essel, Aja Ijeoma, Emmanuel L Obiri, Karen N D Quarchey, Leslie Adam-Zakariah, Aaron B Andoh, Ruby A Boateng, Atta Kusiwaa, Adeline Naah, Ato Oppon-Acquah, Benjamin A Oppong, Emma A Agbowada, Ameley Akosua, O Lawrence Dorcas Acheampong, Frank E Gyamfi, Bertina B Nyadu, Samira Abdulai, Nii A Adu-Aryee, Joachim K Amoako, Nicholas T Aperkor, Wilfred K Asman, Godsway S Attepor, Antoinette A Bediako-Bowan, George D Brown, Victor K Etwire, Benjamin S Fenu, Philemon K Kumassah, Linda A Larbi-Siaw, Josephine Nsaful, David O Olatola, Sandra E Tsatsu, Iddrisu I A Abdul-Aziz, Johnson Akunyam, Gilbert A G Anasara, Charles G Barimah, Guy C Boateng, Ponala W Kwabena, Seidu M Kwarteng, Prosper T Luri, Kennedy Ngaaso, David K D Ogudi, Collins Kyeremeh, Clement Sie-Broni, Saba Abdul-Hafiz, Daniel K Acquah, Shamsudeen M Adams, Mohammed S Alhassan, Munira Amadu, Samuel A Asirifi, Martin Awe, Millicent Azanlerigu, Mathias K Dery, Yenli Edwin, Abantanga Atindaana Francis, Aloysius Maalekuu, Hawa Malechi, Ibrahim Mohammed, Kareem Mumuni, Bernard A Ofori, Jonathan I K Quansah, Napoleon Bellua Sam, Anwar S Seidu, Shekira Yahaya, Emmanuel Kojo Acquah, Jaabir Alhassan, Christian L Coompson, Addo K Gyambibi, Ametepe Jeffery-Felix, Bismark E Kontor, Gifty Naah, Carmen Noufuentes, Abraham Sakyi, Ramkaran Chaudhary, Sanjeev Misra, Dharma R Poonia, Kirti K Rathod, Mahaveer S Rodha, Nivedita Sharma, Subhash C Soni, Vaibhav K Varsheney, Jeevan R Vishnoi, Deepak K Garnaik, Manoj J Lokavarapu, Rohit Ranjan, Rajkumar K Seenivasagam, Shanky Singh, Raunak Verma, Suzan John, Jeffery A Kalyanapu, Ananta Kutma, Sanish Philips, Arun K Gautham, Deepak S Singh, Eunice S Abraham, Chetana Chetana, Prashant Dummala, Chinta S Gold, Jurgen Jacob, Jeremiah N Joseph, Elizabeth N Kurien, Priya Mary, Arpit J Mathew, Amy E Mathew, Danita D Prakash, Ashwin Sukumar, Niyah Syam, Alisha Bhatt, Dhruva N Ghosh, Ankush Goyal, Monika A Hans, Jyoti Jyoti, Karan Kumar, Vivin Daniel Sam, Ravinder Singh Thind, Sreejith K Veetil, Rahul Williams, D Sreekar, Esther R Daniel, Smitha E Jacob, Mark R Jesudason, Pushplatha Kumari, Soosan Prasad, Srujan Sharma, Moonish V Sivakumar, Paul Trinity, Sudheer Kanchodu, K Leshiini, Sundeep S Saluja, Ashok K Attri, Ishan Bansal, Monika Gureh, Simran Kapoor, Harmanjot Kaur, Simrandeep Singh, Viju John, Nivesh Agrawal, Uttkarsh Kumar, S Abhishek, Vikram Sehrawat, Gaurav Thami, Stanley Mathew, P S Prabhu, P T Sundeep, Shiv Rajan, Mohit Singh, Abhilasha Tripathi, Philip V Alexander, A Vijay, Moloti Kichu* Ismavel, Carolin V Solomi, Rahul A Alpheus, Ashish Victor Choudhrie, Rashmi Jacob Gunny, Susan Joseph, Nitin J Peters, Neha Pundir, Ram Samujh, Hafsa I Ahmed, Gowhar Aziz, Nisar A Chowdri, Rayees A Dar, Robindera Kour, Imtiyaz Mantoo, Asif Mehraj, Fazl Q Parray, Najmus Saqib, Zamir A Shah, Rauf A Wani, Komal Rautela, Nishu Singh, Priyanka Chowdhury, Sona Chowdhury, Pragyanmai Nayak, Bipradas Roy, Andrea S Alvarez Villaseñor, Kriscia V Ascencio Díaz, Victor J Avalos Herrera, Francisco J Barbosa, Elyoenai Bonilla Ahumada, Irma V Brancaccio, Miguel A Calderón, Guadalupe Castillo Cardiel, Guillermo A Cervantes, Gabino Cervantes Guevara, Enrique Cervantes Perez, Maria Chávez, Jonathan M Chejfec, Luis R Cifuentes, Ana O Cortés, Edgar J Cortes, Tania A Cueto, Andrea E Cueto, Esteban Cueva Martinez, Paulina Domínguez Barradas, Isaac Esparza Estrada, Paola Flores Becerril, Luis A García, Benjamín García Reyna, Eduardo Gómez Sánchez, Jaime L González, Eduardo González Espinoza, Fanny Y González, Cristhian S Guerrero, José A Guzmán, Bertha G Guzmán, Mario J Guzmán, DanielA Hérnandez Alva, SilviaA Ibarra Camargo, JuanC Ibarrola Peña, Martin Islas Torres, Jorge Jiménez Tornero, ZayraM Lara Pérez, Roberto Mares País, MelP Mellado Tellez, RobertoC Miranda Ackerman, Damián Mora Santana, Gilberto Morgan Villela, Rodrigo Nájar Hinojosa, Cesar Nuño Escobar, Itzel Ochoa Rodríguez, Angelica Ortega Barreiro, Jacqueline Osuna Rubio, Luis RPacheco Vallejo, VíctorH Pérez Bocanegra, JoseV Pérez Navarro, Francisco JPlascencia Posada, MaríaA Quirarte Hernández, LuisR Ramirez Gonzalez, Emilio AReyes Elizalde, EveliaV Romo Ascencio, Cornelio Ruelas Bravo, CarlosB Ruiz Velasco, JoséA Sánchez Martínez, Guillermo Sanchez Villaseñor, JoséI Sandoval Pulido, AlejandroG Serrano García, LuisO Suárez Carreón, JuanJ Tijerina Ávila, JesusO Vega Gastelum, MelissaL Vicencio Ramirez, MariaF Zarate Casas, CarlosJ Zuloaga, Fernández del Valle, JesusAntonion Aguilar Mata, MiguelAntonio Calderon Vanegas, RocioGuadalupe Cano Arias, Carlos Colunga Tinajero, Fernanda Diaz Samano, Fernando Duque Zepeda, BrendaVanessa Enriquez Barajas, Gerardo Gallardo Banuelos, MarijoseDe CristoGonzalez Calvillo, Francisco Ibanez Ortiz, Maryzela Lazo Ramirez, Gerardo Lopez Arroyo, LauraOlivia Montano Angeles, DavidGiovannyI Morales Iriarte, AngeloFernando Mortola Lomeli, Jose EstebanOrozco Navarro, Jaime Orozco Perez, Damaris Orozco Ramirez, LauraGabriela Pena Baolboa, Jesus Pizarro Lozano, Guillermo Yanowsky Reyes, Monica N Castillo, Ana CamilleG Dominguez, Dorihela H Mellado, Jesus FlavioM Morales, Luzdel CarmenM Namur, Jose AlbertoA Pesquera, LauraMartinez Perez Maldonado, Antonio RamosDe laMedina, Katya Bozada-Gutierrez, AnaFlorencia Casado-Zarate, Roberto Delano-Alonso, Jose Herrera-Esquivel, Mucio Moreno-Portillo, Mario Trejo-Avila, Roland Kevin CethorthFonseca, Edgard Efren LozadaHernandez, Bruno Crocco Quiros, JairoArturo Rodriguez Ramirez, Gabriela Ambriz-González, MitziR Becerra Moscoso, Ishtar Cabrera-Lozano, AnaB Calderón-Alvarado, FranciscoJ León-Frutos, ErickE Villanueva-Martínez, Aisha Abdullahi, Maimuna Abubakar, MohammedS Aliyu, Mudi Awaisu, Fadimatu Bakari, Abigail Olajumoke Balogun, Ahmad Bello, Kehinde Michael Duromola, Stephen G Gana, Mukoro Duke George, Justina Gimba, Isaac Gundu, Lambert Onahi Iji, Aminat O Jimoh, Afolabi K Koledade, Ahmad T Lawal, Bilkisu K Lawal, Stanley Emeka Nwabuoku, Oluseyi O Ogunsua, Ifeanyi Fidelis Okafor, Ethos Ike Okorie, Nasir Oyelowo, Ibrahim A Saidu, Tunde T Sholadoye, Ibrahim Sufyan, Musliu Adetola Tolani, Aliyu Muhammad Tukur, Ahmad Shehu Umar, Aminatu M Umar, Hajara Umaru-Sule, Mohammed Usman, Alfa Yakubu, Salisu Abeku Yusuf, Abdulhafiz A Abdulkarim, Lawal Barau Abdullahi, Khadija A Ado, Nura U Aliyu, Lofty-John Chukwuemeka Anyanwu, Sulaiman M Daneji, Mahmoud Kawu Magashi, Mohammad A Mohammad, Abubakar Bala Muhammad, Saminu S Muhammad, Bello Abodunde Muideen, Calistus U Nwachukwu, Suleiman B Sallau, Abdulrahman A Sheshe, Abdulmajeed Soladoye, Idris Usman Takai, Garzali I Umar, Abubakar Yahaya, Lubabatu Abdulrasheed, Joel A Adze, Lydia R Airede, Bashiru Aminu, Stephen B Bature, Firdaws Bello-Tukur, Damai Chinyio, SharonA N Duniya, Moses C Galadima, Babatunde K Hamza, Samaila Joshua, Stephen A Kache, Williams Y Kagomi, Ifeanyi A Kene, Jamila Lawal, Jerry G Makama, Caleb Mohammed, Amina A Mohammed-Durosinlorun, Deborah Nuwam, Abdulrasheed Sani, Salome Tabara, Mathew C Taingson, Emmanuel Usam, Josiah Yakubu, Folasade Adegoke, Oluwasuyi Ige, Tunde A Odunafolabi, Chukwuma E Okereke, Oluwafemi O Oladele, Oluwaseun H Olaleye, Oyetunde O Olubayo, Olukayode P Abiola, Henry O Abiyere, Idowu O Adebara, GbadeboT C Adeleye, Adebayo A Adeniyi, Olumide E Adewara, Olabisi T Adeyemo, Ademola A Adeyeye, Abimbola L Ariyibi, Babatunde S Awoyinka, Olumide M Ayankunle, Olakunle F Babalola, Adewumi Bakare, TajudeenI B Bakare, Oluseyi O Banjo, Peter A Egharevba, Oluwafemi S Fatudimu, John A Obateru, Oluremi J Odesanya, Owolabi D Ojo, Abiodun I Okunlola, Cecilia K Okunlola, Adewale T Olajide, Tesleem O Orewole, Adedayo I Salawu, Moruf A Abdulsalam, Aderinsola T Adelaja, Olalekan T Ajai, Noble Anyanwu, Kazeem M Atobatele, Oludayo Oluwaseyi Bakare, Omolara M Faboya, Francisca C Nwaenyi, Ayokunle A Ogunyemi, Mobolaji A Oludara, Olufunmilade A Omisanjo, Chinonso U Onyeka, Olabode A Oshodi, Yusuf A Oshodi, Omotade S Salami, Omolara M Williams, Esther Abunimye, Adebunmi Adeoluwa, Adedotun Adesiyakan, Victoria Ibukunoluwa Adeyeye, Moses Vincent Agbulu, David O Akinboyewa, Iyabo O Alasi, Michael Amao, Christiana Ashley-Osuzoka, Oluwole A Atoyebi, Olanrewaju S Balogun, Maryam Oluwatobi Busari, Nnamdi Jonathan Duru, Glory Bassey Edet, Olumide A Elebute, Francis Chinonso Ezenwankwo, Adedeji L Fatuga, Christianah Gbenga-Oke, Emmanuel Sylvester Inyang, Adesola I Jimoh, Jubril Oladayo Kuku, OluwaseunA Ladipo-Ajayi, Abdulrazzaq O Lawal, Christian Chigoze Makwe, Chinelo Victoria Mgbemena, Samuel U Nwokocha, Moses Adebisi Ogunjimi, Ephraim Okwudiri Ohazurike, Rufus W Ojewola, Moyosoluwa Eunice Badedale, Chike J Okeke, Adeyemi A Okunowo, Abraham T Oladimeji, Thomas O Olajide, Olabisi Olanrewaju, Olawunmi Olayioye, Oluwaseun O Oluseye, Stephen Olutola, Kenneth Onyekachi, Adeola Ayoola Orowale, Emili Osariemen, Adedapo Olumide Osinowo, Emmanuel Owie, Christianah Bidemi Oyegbola, Justina OSeyi-Olajide, AdaiahP Soibi-Harry, Manuella Talla Timo, Aloy Okechukwu Ugwu, Emmanuel Ojo Williams, Innocent O Duruewuru, Ochonma A Egwuonwu, Okechukwu Hyginus Ekwunife, James J Emeka, Chimdiebele Daisy Nwosu, Sylvester O Obiechina, Ahuizechukwu E Obiesie, Celestine I Okafor, Theophilus O Okonoboh, Odili A Okoye, Onyekachi A Onu, Chukwudubem C Onyejiaka, Chisom Faith Uche, JosephO Ugboajah, Akeem A Adeleke, Akinfolarin C Adepiti, Adewale A Aderounmu, Abdulhafiz O Adesunkanmi, Adewale O Adisa, Samuel C Ajekwu, Olusegun K Ajenifuja, Olusegun I Alatise, Tajudeen A Badmus, Tajudeen O Mohammed, Abdulkadir A Salako, Oludayo A Sowande, Ademola O Talabi, Funmilola O Wuraola, Paul Aderemi Adegoke, Abidemi Akinloye, Ayodeji Akinniyi, Joseph Ejimogu, Ideyonbe Samuel Eseile, Olakayode Olaolu Ogundoyin, Amos Okedare, Dare Isaac Olulana, Omolara Omotola, Francis Sanwo, Collins C Adumah, Adewale O Ajagbe, Olugbenga P Akintunde, Opeyemi Q Asafa, Kehinde Awodele, Amogu K Eziyi, Adeniyi O Fasanu, Olufemi O Ojewuyi, Abiodun R Ojewuyi, Abisola E Oyedele, Oluwaseun A Taiwo, Habiba I Abdullahi, Nathaniel D Adewole, Teddy E Agida, Eunice E Ailunia, Oseremen Aisuodionoe-Shadrach, Godwin O Akaba, Janet Alfred, Terkaa Atim, Kehinde G Bawa, John Y Chinda, Esther B Daluk, Sefiu B Eniola, Augusta O Ezenwa, Stephen E Garba, Philip M Mshelbwala, Ngozi O Ndukwe, Idoko P Ogolekwu, Alexander A Ohemu, Samuel A Sani, Salisu Suleiman, Helen Sunday, Nancy O Tabuanu, Aminu M Umar, Peter I Agbonrofo, Alexander I Arekhandia, Morrison E Edena, Raymond A Eghonghon, Joel E Enaholo, Genesis Ida, Stanley N Ideh, Oseihie I Iribhogbe, Omorodion O Irowa, Maradona E Isikhuemen, Oluwatomi R Odutola, Kester O Okoduwa, Scott O Omorogbe, David Oruade, Osasumwen T Osagie, Osarenkhoe Osemwegie, RukiyatA Abdus-Salam, Sikiru Adekola Adebayo, Oluwasanmi A Ajagbe, Gboyega Ajibola, Kelvin I Egbuchulem, Hyginus O Ekwuazi, Adegbolahan Fakoya, Oluwasegun C Idowu, David O Irabor, Taiwo A Lawal, Olakayode O Ogundoyin, Oluwabukade Ojediran, Naomi Olagunju, Akinsola T Sanusi, Augustine O Takure, Lukman Olajide Abdur-Rahman, Mary Oluwadamilola Adebisi, Nurudeen Abiola Adeleke, Rafiat Tinuola Afolabi, Isiaka Ishola Aremu, Jibril Oyekunle Bello, Robiat Bello, Saheed Abolade Lawal, Adeolu Ojajuni, Sabur Oyewale, Victor Abhulimen, Patrick O Igwe, Ikechukwu Enyinnaya Iweha, Raphael E John, Nnyonno Okoi, Philemon E Okoro, Vaduneme Kingsley Oriji, Ibiene T Oweredaba, Japhet Mizero, Immaculee Mutimamwiza, Francoise Nirere, Irenee Niyongombwa, Jean Paul Majyabere, Anastase Byaruhanga, Rongin Dukuzimana, Jean Aimable Habiyakare, Marie Gloriose Nabada, Marcel Uwizeye, Mathias Ruhosha, Joselyne Igiraneza, Faustine Ingabire, Aloys Karekezi, Jean pierre Masengesho, Lydia Mukamazera, Clemence Mukangabo, Jean Paul Niyomuremyi, Gabriel Ntwari, Celestin Seneza, Divine Umuhoza, Pierrine Nyirangeri, Jean Claude Uwimana, Isaie Sibomana, Desire Rubanguka, Josine Umuhoza, Roda Uwayezu, Leoncie Uzikwambara, Herbert Butana, Moise Dusabeyezu, Athanasie Mukasine, Jean N Utumatwishima, Mediatrice Batangana, Jeande Dieu Haragirimana, AllenJ C Ingabire, Espoir Mwungura, Dancilla Nyirasebura, Christian Jean Urimubabo, Anaclet Dusabimana, Sam Kanyesigye, Robert Munyaneza, Jean Yves Shyirakera, Aimee Domingo, Philip Munda, Chido Nyatsambo, Victor Ojo, Rudo Pswarayi, and Soeren Laurberg

Subjects
Medicine (General), R5-920, Infectious and parasitic diseases, RC109-216
Published
2024
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29. Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands

Author

Tim J. B. Carruthers, S. Beaux Jones, Megan K. Terrell, Jonathan F. Scheibly, Brendan J. Player, Valerie A. Black, Justin R. Ehrenwerth, Patrick D. Biber, Rod M. Connolly, Steve Crooks, Jason P. Curole, Kelly M. Darnell, Alyssa M. Dausman, Allison L. DeJong, Shawn M. Doyle, Christopher R. Esposito, Daniel A. Friess, James W. Fourqurean, Ioannis Y. Georgiou, Gabriel D. Grimsditch, Songjie He, Eva R. Hillmann, Guerry O. Holm, Jennifer Howard, Hoonshin Jung, Stacy D. Jupiter, Erin Kiskaddon, Ken W. Krauss, Paul S. Lavery, Bingqing Liu, Catherine E. Lovelock, Sarah K. Mack, Peter I. Macreadie, Karen J. McGlathery, J. Patrick Megonigal, Brian J. Roberts, Scott Settelmyer, Lorie W. Staver, Hilary J. Stevens, Ariana E. Sutton-Grier, Jorge A. Villa, John R. White, and Michelle Waycott

Subjects
blue carbon, tidal marsh, mitigation, adaptation, Louisiana, carbon credits, Environmental sciences, GE1-350
Abstract

One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.

Published
2024
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30. Evolving trends and challenges in sustainable architectural design; a practice perspective

Author

Emeka J. Mba, Francis O. Okeke, Ajuluchukwu E. Igwe, Chinelo A. Ozigbo, Peter I. Oforji, and Ikechukwu W. Ozigbo

Subjects
Sustainable architecture, Architectural practice, Sustainability, Design, Built environment, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Architects play a crucial role in shaping sustainable built environments that balance utility and aesthetics without compromising ecological integrity. Hence embracing sustainability remains an urgent imperative as construction activities expand to meet Nigeria's development needs. This research examines how architects in Enugu Metropolis, Nigeria are assimilating principles of sustainability within their design practices against a transforming professional backdrop. The study utilized primary data targeting 126 registered architectural firms in the study area through a questionnaire survey and achieved 88.9 % response rate. Data were analyzed using JASP and Pearson product moment correlation. Results revealed high conceptual awareness of sustainability among architects, with 32.2 % consistently applying strategies like renewable energy systems in designs. Economic considerations and supportive regulations emerged as key assimilation motivators. However, uneven integration levels underline lingering barriers. While 40.6 % rated sustainability incorporation in education as very good, 13.5 % perceived it as moderate, indicating gaps in practical competencies. Statistical analysis (P-value = 0.001) showed a significant positive relationship between architects' awareness of sustainability concepts and their implementation of sustainable design practices. These findings highlight the need for strengthened educational programs, policy incentives, and industry collaborations to accelerate sustainable architecture adoption. Recommendations include updating curricula, mandating green ratings for public projects, incentivizing developers, and promoting interdisciplinary knowledge transfer. By addressing identified gaps, it implies that architects can lead the sustainability transition while meeting local built environment needs, ensuring a more climate-compatible and socially equitable habitat creation.

Published
2024
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31. Modelling the spatiotemporal dynamics of blue carbon stocks in tidal marsh under Spartina alterniflora invasion

Author

Wenzhen Zhao, Xiuzhen Li, Micheli D.P. Costa, Melissa Wartman, Shiwei Lin, Jiangjing Wang, Lin Yuan, Teng Wang, Hualei Yang, Yutao Qin, Huanhong Ji, and Peter I. Macreadie

Subjects
Tidal marsh, Blue carbon, Spartina alterniflora, Invasive species, China, Random Forest, Ecology, QH540-549.5
Abstract

Spatial quantification of blue carbon ecosystem stocks is crucial for developing policies to mitigate climate change, especially in regions experiencing ongoing wetland disturbance from biological invasions. We integrated multiple machine learning models with the space-for-time substitution method to quantify the spatiotemporal impact of Spartina alterniflora invasion on tidal marsh sediment blue carbon (soil organic carbon – 'SOC') stocks at 100 cm depth in the Yangtze Estuary. Our results show that the invasive S. alterniflora contributed more than half of the total SOC stocks (2,056 ± 379 Gg C, 1 Gg = 106 kg) in the 27,600 ha tidal marshes of the Yangtze Estuary, which were estimated to be 1,107 ± 176 Gg C. S. alterniflora increased the SOC stocks in the Yangtze Estuary within the first 15 years, but this gain was not sustained in the long term, with a gradual decline (by 13.14 Mg C/ha) observed after 15 years of S. alterniflora growth. We found that sediment salinity, tidal range, and human accessibility were strong indicators for modeling and predicting SOC stocks, with Random Forest providing the best simulation of tidal marsh SOC stocks (R2 = 0.894, RMSE=7.646 Mg C/ha, and MAPE=9.469 %). Our study provides much needed information on blue carbon stocks in the Yangtze Estuary under biological invasion stress, and offers guidance for targeted S. alterniflora management actions in the future.

Published
2024
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32. SARS-CoV-2 Mpro inhibitor identification using a cellular gain-of-signal assay for high-throughput screening

Author

Renee Delgado, Jyoti Vishwakarma, Seyed Arad Moghadasi, Yuka Otsuka, Justin Shumate, Ashley Cuell, Megan Tansiongco, Christina B. Cooley, Yanjun Chen, Agnieszka Dabrowska, Rahul Basu, Paulina Duhita Anindita, Dahai Luo, Peter I. Dosa, Daniel A. Harki, Thomas Bannister, Louis Scampavia, Timothy P. Spicer, and Reuben S. Harris

Subjects
Antiviral drugs, cell-based ultra-high throughput screening (uHTS), protease inhibitors, SARS-CoV-2 main protease (Mpro/3CLpro), Medicine (General), R5-920, Biotechnology, TP248.13-248.65
Abstract

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2, SARS2) is responsible for the COVID-19 pandemic and infections that continue to affect the lives of millions of people worldwide, especially those who are older and/or immunocompromised. The SARS2 main protease enzyme, Mpro (also called 3C-like protease, 3CLpro), is a bona fide drug target as evidenced by potent inhibition with nirmatrelvir and ensitrelvir, the active components of the drugs Paxlovid and Xocova, respectively. However, the existence of nirmatrelvir and ensitrelvir-resistant isolates underscores the need to develop next-generation drugs with different resistance profiles and/or distinct mechanisms of action. Here, we report the results of a high-throughput screen of 649,568 compounds using a cellular gain-of-signal assay. In this assay, Mpro inhibits expression of a luciferase reporter, and 8,777 small molecules were considered hits by causing a gain in luciferase activity 3x SD above the sample field activity (6.8% gain-of-signal relative to 100 µM GC376). Single concentration and dose-response gain-of-signal experiments confirmed 3,522/8,762 compounds as candidate inhibitors. In parallel, all initial high-throughput screening hits were tested in a peptide cleavage assay with purified Mpro and only 39/8,762 showed inhibition. Importantly, 19/39 compounds (49%) re-tested positive in both SARS2 assays, including two previously reported Mpro inhibitors, demonstrating the efficacy of the overall screening strategy. This approach led to the rediscovery of known Mpro inhibitors such as calpain inhibitor II, as well as to the discovery of novel compounds that provide chemical information for future drug development efforts.

Published
2024
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34. Regret Bounds and Experimental Design for Estimate-then-Optimize

Author

Tan, Samuel and Frazier, Peter I.

Subjects
Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

In practical applications, data is used to make decisions in two steps: estimation and optimization. First, a machine learning model estimates parameters for a structural model relating decisions to outcomes. Second, a decision is chosen to optimize the structural model's predicted outcome as if its parameters were correctly estimated. Due to its flexibility and simple implementation, this ``estimate-then-optimize'' approach is often used for data-driven decision-making. Errors in the estimation step can lead estimate-then-optimize to sub-optimal decisions that result in regret, i.e., a difference in value between the decision made and the best decision available with knowledge of the structural model's parameters. We provide a novel bound on this regret for smooth and unconstrained optimization problems. Using this bound, in settings where estimated parameters are linear transformations of sub-Gaussian random vectors, we provide a general procedure for experimental design to minimize the regret resulting from estimate-then-optimize. We demonstrate our approach on simple examples and a pandemic control application.

Published
2022

36. Calculating the Raman signal of solid hydrogen beyond perturbation theory

Author

Cooke, Peter I. C., Ackland, Graeme, Loa, Ingo, Pena Alvarez, Miriam, and Hermann, Andreas

Subjects
Raman signal, solid hydrogen, perturbation theory, solid phases of hydrogen, solid metallic phase, metallic hydrogen, density functional theory (DFT), Raman spectroscopy, Raman spectra, Vibrational Raman transitions, nuclear quantum effects (NQEs), eigenstates, parameterised mean-field
Abstract

The study of the solid phases of hydrogen has become an area of intense interest in recent decades. The majority of this work has been focused on obtaining a solid metallic phase, famously predicted to exist by Wigner and Huntington in 1935. As a result of the search for metallic hydrogen, a rich phase diagram has gradually been uncovered and hydrogen is now believed to form at least five solid phases. Powerful computational techniques, utilising density functional theory (DFT), have been used to predict several structural candidates for each of these phases. However, owing to experimental constraints imposed by working with hydrogen at high pressure, none of the proposed candidates have been unequivocally verified. The most common experimental technique used to characterise the solid hydrogens is Raman spectroscopy. Analysis of the Raman spectra for a given system can often elucidate its precise structure and the nature of the excited states. Vibrational Raman transitions in solid hydrogen have been well described by DFT based methods, but the rotational spectra are not obtainable in this way. Significant nuclear quantum effects (NQEs) in hydrogen, cause the diatomic molecule to form a quantum rotor. The ground state has a spherically symmetric wavefunction and the angular momentum is quantised. In this thesis I present a single molecule method for predicting the rotational Raman signal of various systems of quantum rotors. I firstly apply this method to a diatomic molecule in a range of model mean-field potentials, and evaluate the evolution of the associated Raman spectra with field strength. This reveals that dramatic changes occur in the appearance of the Raman spectrum for a diatomic molecule without any associated change in the symmetry of the surrounding potential. I show that the ground state corresponds to a quantum rotor at low field strength and a quantum oscillator at high field strength. However, there are also 're-orientational' modes and many mixed modes which are neither rotons nor librons. The mass-dependence of the various states is different - rotors, oscillators and reorientations have 1/m, 1/√m and weaker mass dependence respectively. This may allow one to identify the character of the mode with isotope spectroscopy. However, it is complicated by mixed modes and transitions between two different eigenstates with different character. I demonstrate that with these simple potentials, all of which are simpler than those expected for any solid phase of hydrogen, interpretation of the Raman spectra is already overwhelming complex. Significant changes in the Raman spectra are seen even in a simple fixed symmetry potential, leading to the conclusion that such changes in isolation are not sufficient evidence for a phase transition in a diatomic solid. I adapt the method to recreate the experimental Raman signal for phase I in hydrogen and deuterium. I fit a parameterised mean-field consisting of long range electrostatic and short range steric terms to experimental data. The fitted potential reveals a large repulsion out of the A-B plane, consistent with recent neutron scattering data but in opposition to previous theoretical models. By incorporating experimental geometry into the model, I reveal the importance of such effects in predicting Raman spectra for experiments using DACs. This has wider implications for previous Raman spectra prediction with other methods. Moving to phase II, I analyse single molecule excitations for various structure candidates from the literature. This is motivated by the appearance of low frequency peaks in the experimental data at the phase I-II transition. Previous predictions of Raman spectra for phase II structural candidates have focused on delocalised collective excitations, but previous experiments on deuterium and hydrogen mixtures suggest these peaks are not associated with long range order. I use molecular dynamics trajectories with a classical hydrogen forcefield to generate mean-field potentials. I then incorporate nuclear quantum effects to these potentials by rescaling the temperature. I predict that in the case of hydrogen the ground state exhibits preferred orientation but is only weakly bound. A previously unassigned Raman active peak may be explained by a re-orientation transition from the first excited state. The nature of the modes predicted in this regime is inconsistent with the canonical view of Raman transitions as either vibrons, librons or phonons, rather the excitations correspond to either a re-orientation of the molecule or mixed modes between the rotor and librator regime. Overall, the quantum treatment developed in this thesis reveals the complexity of interpreting Raman spectra for diatomic molecular solids. I demonstrate that the simplified view of rotons and librons is insufficient to describe the solid phases of hydrogen. Furthermore, perturbative approaches fail to predict the existence of low frequency modes in the ordered phases. In some cases these peaks can be assigned to single molecule modes in the heavily hindered rotor regime. Finally I find that details such as the geometry of the experiment and ortho:para ratio of the sample can significantly effect the observed modes in the signal. The method developed here is applicable to any system containing diatomic molecules and could be further adapted to include higher numbers of atoms.

Published
2023
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37. A universal molecular control for DNA, mRNA and protein expression

Author

Helen M. Gunter, Scott E. Youlten, Andre L. M. Reis, Tim McCubbin, Bindu Swapna Madala, Ted Wong, Igor Stevanovski, Arcadi Cipponi, Ira W. Deveson, Nadia S. Santini, Sarah Kummerfeld, Peter I. Croucher, Esteban Marcellin, and Tim R. Mercer

Subjects
Science
Abstract

Abstract The expression of genes encompasses their transcription into mRNA followed by translation into protein. In recent years, next-generation sequencing and mass spectrometry methods have profiled DNA, RNA and protein abundance in cells. However, there are currently no reference standards that are compatible across these genomic, transcriptomic and proteomic methods, and provide an integrated measure of gene expression. Here, we use synthetic biology principles to engineer a multi-omics control, termed pREF, that can act as a universal molecular standard for next-generation sequencing and mass spectrometry methods. The pREF sequence encodes 21 synthetic genes that can be in vitro transcribed into spike-in mRNA controls, and in vitro translated to generate matched protein controls. The synthetic genes provide qualitative controls that can measure sensitivity and quantitative accuracy of DNA, RNA and peptide detection. We demonstrate the use of pREF in metagenome DNA sequencing and RNA sequencing experiments and evaluate the quantification of proteins using mass spectrometry. Unlike previous spike-in controls, pREF can be independently propagated and the synthetic mRNA and protein controls can be sustainably prepared by recipient laboratories using common molecular biology techniques. Together, this provides a universal synthetic standard able to integrate genomic, transcriptomic and proteomic methods.

Published
2024
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38. Intradiscal treatment of the cartilage endplate for improving solute transport and disc nutrition

Author

Habib, Mohamed, Hussien, Shayan, Jeon, Oju, Lotz, Jeffrey C, Wu, Peter I-Kung, Alsberg, Eben, and Fields, Aaron J

Subjects
Biomedical and Clinical Sciences, Engineering, Biomedical Engineering, cartilage endplate, intervertebral disc degeneration, biotransport, spine biomechanics, low back pain, tissue engineering, Other Biological Sciences, Medical Biotechnology, Industrial biotechnology, Medical biotechnology, Biomedical engineering
Abstract

Poor nutrient transport through the cartilage endplate (CEP) is a key factor in the etiology of intervertebral disc degeneration and may hinder the efficacy of biologic strategies for disc regeneration. Yet, there are currently no treatments for improving nutrient transport through the CEP. In this study we tested whether intradiscal delivery of a matrix-modifying enzyme to the CEP improves solute transport into whole human and bovine discs. Ten human lumbar motion segments harvested from five fresh cadaveric spines (38-66 years old) and nine bovine coccygeal motion segments harvested from three adult steers were treated intradiscally either with collagenase enzyme or control buffer that was loaded in alginate carrier. Motion segments were then incubated for 18 h at 37 °C, the bony endplates removed, and the isolated discs were compressed under static (0.2 MPa) and cyclic (0.4-0.8 MPa, 0.2 Hz) loads while submerged in fluorescein tracer solution (376 Da; 0.1 mg/ml). Fluorescein concentrations from site-matched nucleus pulposus (NP) samples were compared between discs. CEP samples from each disc were digested and assayed for sulfated glycosaminoglycan (sGAG) and collagen contents. Results showed that enzymatic treatment of the CEP dramatically enhanced small solute transport into the disc. Discs with enzyme-treated CEPs had up to 10.8-fold (human) and 14.0-fold (bovine) higher fluorescein concentration in the NP compared to site-matched locations in discs with buffer-treated CEPs (p < 0.0001). Increases in solute transport were consistent with the effects of enzymatic treatment on CEP composition, which included reductions in sGAG content of 33.5% (human) and 40% (bovine). Whole disc biomechanical behavior-namely, creep strain and disc modulus-was similar between discs with enzyme- and buffer-treated CEPs. Taken together, these findings demonstrate the potential for matrix modification of the CEP to improve the transport of small solutes into whole intact discs.

Published
2023

40. Prevalence of Hyperuricemia and Associated Factors Among Patients With Type 2 Diabetes Mellitus in Northwestern Tanzania: A Cross-Sectional Study

Author

Kulthum A. Abdel, Samuel E. Kalluvya, Abid M. Sadiq, Abdel Ashir, and Peter I. Masikini

Subjects
Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

Background: There has been increasing evidence of the association between hyperuricemia and diabetes mellitus (DM). In the general population, hyperuricemia has been associated with pre-diabetes. In DM patients, hyperuricemia has been associated with poor outcomes. Objectives: The objective was to determine the proportion of hyperuricemia and associated factors among patients with type 2 DM in Mwanza, Tanzania. Design: This was a cross-sectional study. Methods: This study was conducted from January to March 2023 among patients with type 2 DM attending clinic at Bugando Medical Centre, Mwanza. Data was obtained from a structured questionnaire. Serum uric acid, HbA1c, lipid profile, and renal functions were analyzed. Analysis was done via STATA version 17. The primary outcome was the proportion of hyperuricemia among patients with type 2 DM, and logistic regression models were used to analyze associated factors. Results: Out of 360 patients, 59.7% were female. The median age was 61 years [IQR 57-68], and the median duration of DM was 5 years [IQR 3-9]. The mean HbA1c was 8.2 ± 2.5%, with 60% of patients having poor control. Most patients had hypertension (78.9%) and were overweight or obese (81.9%). The proportion of patients with DM and hyperuricemia was 44.4%, with mean serum uric acid levels among males and females of 410 ± 137 and 385 ± 119 µmol/L, respectively. We found that being female (P = .001), overweight (P = .021), or obese (P = .007), and having chronic kidney disease (P

Published
2024
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41. Drivers of wood‐inhabiting fungal diversity in European and Oriental beech forests

Author

Giorgi Mamadashvili, Antoine Brin, Maksym Chumak, Valeriia Diedus, Lars Drössler, Bernhard Förster, Kostadin B. Georgiev, Tigran Ghrejyan, Ruslan Hleb, Mark Kalashian, Ivan Kamburov, Gayane Karagyan, Joni Kevlishvili, Zviad Khutsishvili, Laurent Larrieu, Meri Mazmanyan, Peter I. Petrov, Levan Tabunidze, Claus Bässler, and Jörg Müller

Subjects
deadwood fungi, Fagus orientalis, Fagus sylvatica, habitat heterogeneity, Hill numbers, species diversity, Ecology, QH540-549.5
Abstract

Abstract The hyperdiverse wood‐inhabiting fungi play a crucial role in the global carbon cycle, but often are threatened by deadwood removal, particularly in temperate forests dominated by European beech (Fagus sylvatica) and Oriental beech (Fagus orientalis). To study the impact of abiotic drivers, deadwood factors, forest management and biogeographical patterns in forests of both beech species on fungal composition and diversity, we collected 215 deadwood‐drilling samples in 18 forests from France to Armenia and identified fungi by meta‐barcoding. In our analyses, we distinguished the patterns driven by rare, common, and dominant species using Hill numbers. Despite a broad overlap in species, the fungal composition with focus on rare species was determined by Fagus species, deadwood type, deadwood diameter, precipitation, temperature, and management status in decreasing order. Shifting the focus on common and dominant species, only Fagus species, both climate variables and deadwood type remained. The richness of species within the deadwood objects increased significantly only with decay stage. Gamma diversity in European beech forests was higher than in Oriental beech forests. We revealed the highest gamma diversity for old‐growth forests of European beech when focusing on dominant species. Our results implicate that deadwood retention efforts, focusing on dominant fungi species, critical for the decay process, should be distributed across precipitation and temperature gradients and both Fagus species. Strategies focusing on rare species should additionally focus on different diameters and on the conservation of old‐growth forests.

Published
2024
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42. Bronchoscopy with and without needle-based confocal laser endomicroscopy for peripheral lung nodule diagnosis: protocol for a multicentre randomised controlled trial (CLEVER trial)

Author

Marjolein A Heuvelmans, Kathleen Jahn, Jouke T Annema, Venerino Poletti, Christina Bal, Daniela Gompelmann, Daniël A Korevaar, Juergen Hetzel, Claudia Ravaglia, Grigoris Stratakos, Peter I Bonta, Tess Kramer, Evangelia Koukaki, Saskia van Heumen, Ali Sadoughi, Katerina Bakiri, Nektarios Anagnostopoulos, Jiří Votruba, Zuzana Šestáková, Johannes M.A. Daniels, and Daniel M de Bruin

Subjects
Medicine
Abstract

Introduction Despite many technological advances, the diagnostic yield of bronchoscopic peripheral lung nodule analysis remains limited due to frequent mispositioning. Needle-based confocal laser endomicroscopy (nCLE) enables real-time microscopic feedback on needle positioning, potentially improving the sampling location and diagnostic yield. Previous studies have defined and validated nCLE criteria for malignancy, airway and lung parenchyma. Larger studies demonstrating the effect of nCLE on diagnostic yield are lacking. We aim to investigate if nCLE-imaging integrated with conventional bronchoscopy results in a higher diagnostic yield compared with conventional bronchoscopy without nCLE.Methods and analysis This is a parallel-group randomised controlled trial. Recruitment is performed at pulmonology outpatient clinics in universities and general hospitals in six different European countries and one hospital in the USA. Consecutive patients with a for malignancy suspected peripheral lung nodule (10–30 mm) with an indication for diagnostic bronchoscopy will be screened, and 208 patients will be included. Web-based randomisation (1:1) between the two procedures will be performed. The primary outcome is diagnostic yield. Secondary outcomes include diagnostic sensitivity for malignancy, needle repositionings, procedure and fluoroscopy duration, and complications. Pathologists will be blinded to procedure type; patients and endoscopists will not.Ethics and dissemination Primary approval by the Ethics Committee of the Amsterdam University Medical Center. Dissemination involves publication in a peer-reviewed journal.Support Financial and material support from Mauna Kea Technologies.Trial registration number NCT06079970.

Published
2024
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43. Use of wound infusion catheters for delivery of local anesthetic following standing partial ostectomy of thoracolumbar vertebral spinous processes in horses is not associated with increased surgical site infections

Author

Francesca A. Wickstead, Peter I. Milner, and David A. Bardell

Subjects
wound catheter, local anesthetic, horse, ostectomy, vertebral spinous process, Veterinary medicine, SF600-1100
Abstract

BackgroundWound infusion catheters (WICs) have been used in humans and some veterinary species for post-operative local anesthetic administration following a variety of surgical procedures, aiming to reduce post-operative analgesia requirements and improve patient comfort. Benefit in reduction in pain, post-operative analgesia requirements and length of hospital stay are well documented in humans, but use of WICs may not have been widely adopted in veterinary species due to the concern of increased complications, such as dehiscence or surgical site infection (SSI), creating a barrier to their use. This study aimed to evaluate the use of WICs in horses undergoing standing partial ostectomy surgeries, document complications and investigate if the incidence of SSI was equivalent between those horses that did and did not have a WIC.MethodsClinical records were searched between January 2010–December 2023 for horses undergoing standing partial ostectomy surgery of thoracolumbar vertebral spinous processes at one institution. Population variables (age, breed, bodyweight), placement of a WIC or not, post-operative complications, analgesia protocols and surgical time were recorded. Horses received up to 0.1 mg kg−1 bupivacaine (0.5 mg mL−1) every 6–8 h via the WIC where one was placed. To compare SSI complication incidence between using or not using a WIC, a proportional independent equivalence test was used.ResultsThere were 64 horses included in the final analysis with a WIC placed in 29/64 horses (45.3%) and 35/64 (54.7%) having no WIC placed at surgery. Incidence of short-term SSI was 11.4% (no WIC used) and 13.8% (WIC used), respectively. The difference in proportion of SSI between the presence or absence of a WIC was not significant [−0.024 (90% CI −0.181; 0.133); p = 0.94].ConclusionThe incidence of SSIs was equivalent between groups whether a WIC was used or not. WICs should be considered as part of a multi-modal analgesic approach in the post-operative period. Further research into local anesthetic dosing and its impact on rescue analgesia requirements and pain-scores is warranted.

Published
2024
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44. Dynamic Pricing Provides Robust Equilibria in Stochastic Ridesharing Networks

Author

Cashore, J. Massey, Frazier, Peter I., and Tardos, Eva

Subjects
Mathematics - Optimization and Control, Computer Science - Computer Science and Game Theory
Abstract

Ridesharing markets are complex: drivers are strategic, rider demand and driver availability are stochastic, and complex city-scale phenomena like weather induce large scale correlation across space and time. At the same time, past work has focused on a subset of these challenges. We propose a model of ridesharing networks with strategic drivers, spatiotemporal dynamics, and stochasticity. Supporting both computational tractability and better modeling flexibility than classical fluid limits, we use a two-level stochastic model that allows correlated shocks caused by weather or large public events. Using this model, we propose a novel pricing mechanism: stochastic spatiotemporal pricing (SSP). We show that the SSP mechanism is asymptotically incentive-compatible and that all (approximate) equilibria of the resulting game are asymptotically welfare-maximizing when the market is large enough. The SSP mechanism iteratively recomputes prices based on realized demand and supply, and in this sense prices dynamically. We show that this is critical: while a static variant of the SSP mechanism (whose prices vary with the market-level stochastic scenario but not individual rider and driver decisions) has a sequence of asymptotically welfare-optimal approximate equilibria, we demonstrate that it also has other equilibria producing extremely low social welfare. Thus, we argue that dynamic pricing is important for ensuring robustness in stochastic ride-sharing networks.

Published
2022

45. Near-optimality for infinite-horizon restless bandits with many arms

Author

Zhang, Xiangyu and Frazier, Peter I.

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

Restless bandits are an important class of problems with applications in recommender systems, active learning, revenue management and other areas. We consider infinite-horizon discounted restless bandits with many arms where a fixed proportion of arms may be pulled in each period and where arms share a finite state space. Although an average-case-optimal policy can be computed via stochastic dynamic programming, the computation required grows exponentially with the number of arms $N$. Thus, it is important to find scalable policies that can be computed efficiently for large $N$ and that are near optimal in this regime, in the sense that the optimality gap (i.e. the loss of expected performance against an optimal policy) per arm vanishes for large $N$. However, the most popular approach, the Whittle index, requires a hard-to-verify indexability condition to be well-defined and another hard-to-verify condition to guarantee a $o(N)$ optimality gap. We present a method resolving these difficulties. By replacing a global Lagrange multiplier used by the Whittle index with a sequence of Lagrangian multipliers, one per time period up to a finite truncation point, we derive a class of policies, called fluid-balance policies, that have a $O(\sqrt{N})$ optimality gap. Unlike the Whittle index, fluid-balance policies do not require indexability to be well-defined and their $O(\sqrt{N})$ optimality gap bound holds universally without sufficient conditions. We also demonstrate empirically that fluid-balance policies provide state-of-the-art performance on specific problems.

Published
2022

46. Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes

Author

Lin, Zhiyuan Jerry, Astudillo, Raul, Frazier, Peter I., and Bakshy, Eytan

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

We consider Bayesian optimization of expensive-to-evaluate experiments that generate vector-valued outcomes over which a decision-maker (DM) has preferences. These preferences are encoded by a utility function that is not known in closed form but can be estimated by asking the DM to express preferences over pairs of outcome vectors. To address this problem, we develop Bayesian optimization with preference exploration, a novel framework that alternates between interactive real-time preference learning with the DM via pairwise comparisons between outcomes, and Bayesian optimization with a learned compositional model of DM utility and outcomes. Within this framework, we propose preference exploration strategies specifically designed for this task, and demonstrate their performance via extensive simulation studies.

Published
2022

47. Multi‐information source Bayesian optimization of culture media for cellular agriculture

Author

Cosenza, Zachary, Astudillo, Raul, Frazier, Peter I, Baar, Keith, and Block, David E

Subjects
Biological Sciences, Industrial Biotechnology, Agriculture, Algorithms, Animals, Bayes Theorem, Culture Media, Mice, Models, Biological, Bayesian optimization, cellular agriculture, expected improvement, Gaussian process, media optimization, multi-information source, Biotechnology
Abstract

Culture media used in industrial bioprocessing and the emerging field of cellular agriculture is difficult to optimize due to the lack of rigorous mathematical models of cell growth and culture conditions, as well as the complexity of the design space. Rapid growth assays are inaccurate yet convenient, while robust measures of cell number can be time-consuming to the point of limiting experimentation. In this study, we optimized a cell culture media with 14 components using a multi-information source Bayesian optimization algorithm that locates optimal media conditions based on an iterative refinement of an uncertainty-weighted desirability function. As a model system, we utilized murine C2C12 cells, using AlamarBlue, LIVE stain, and trypan blue exclusion cell counting assays to determine cell number. Using this experimental optimization algorithm, we were able to design media with 181% more cells than a common commercial variant with a similar economic cost, while doing so in 38% fewer experiments than an efficient design-of-experiments method. The optimal medium generalized well to long-term growth up to four passages of C2C12 cells, indicating the multi-information source assay improved measurement robustness relative to rapid growth assays alone.

Published
2022

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