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Solar photovoltaic (PV) farms represent a major source of global renewable energy generation, yet their true operational efficiency often remains unknown at scale. In this paper, we present a comprehensive, data-driven framework for large-scale airborne infrared inspection of North American solar installations. Leveraging high-resolution thermal imagery, we construct and curate a geographically diverse dataset encompassing thousands of PV sites, enabling machine learning-based detection and localization of defects that are not detectable in the visible spectrum. Our pipeline integrates advanced image processing, georeferencing, and airborne thermal infrared anomaly detection to provide rigorous estimates of performance losses. We highlight practical considerations in aerial data collection, annotation methodologies, and model deployment across a wide range of environmental and operational conditions. Our work delivers new insights into the reliability of large-scale solar assets and serves as a foundation for ongoing research on performance trends, predictive maintenance, and scalable analytics in the renewable energy sector.

We investigate the classical and quantum dynamics of $f(R)$ gravity's rainbow in the presence of a perfect fluid, employing Schutz's formalism to establish a well-defined notion of time. In the classical regime, we derive and solve the equations of motion, obtaining both analytical and numerical solutions. Through canonical quantisation, we formulate the Schr\"{o}dinger-Wheeler-DeWitt (SWD) equation for the quantum model. By solving its eigenfunctions, we construct the wave function of the Universe and obtain analytical solutions in scenarios dominated by stiff matter. Our results highlight the impact of rainbow gravity on quantum evolution, particularly in modifying the structure of the wave function and shaping the transition from the quantum to the classical regime., Comment: 18 pages, 3 figures

Yasutaka Nakanishi formulated the following conjecture in 1981: every link is 3-move equivalent to a trivial link. While the conjecture was proved for several specific cases, it remained an open question for over twenty years. In 2002, Mieczys{\l}aw D{\c a}bkowski and the last author showed that it does not hold, in general. In this article, we prove the Montesinos-Nakanishi $3$-move conjecture for links with up to 19 crossings and, with the exception of six pairwise non-isotopic links including the Chen link and its mirror image, for links with 20 crossings. Our work completely classifies links up 20 crossings modulo $3$-moves. This work includes computational methods, including new code in Regina that generalises pre-existing knot functions to work with links., Comment: 18 pages, comments welcomed

In recent neutrino detectors, neutrons produced in neutrino reactions play an important role. Muon capture on oxygen nuclei is one of the processes that produce neutrons in water Cherenkov detectors. We measured neutron multiplicity in the process using cosmic ray muons that stop in the gadolinium-loaded Super-Kamiokande detector. For this measurement, neutron detection efficiency is obtained with the muon capture events followed by gamma rays to be $50.2^{+2.0}_{-2.1}\%$. By fitting the observed multiplicity considering the detection efficiency, we measure neutron multiplicity in muon capture as $P(0)=24\pm3\%$, $P(1)=70^{+3}_{-2}\%$, $P(2)=6.1\pm0.5\%$, $P(3)=0.38\pm0.09\%$. This is the first measurement of the multiplicity of neutrons associated with muon capture without neutron energy threshold.

Fluid triboelectrification, also known as flow electrification, remains an under-explored yet ubiquitous phenomenon with potential applications in various fields, from material science to planetary evolution. Building upon previous efforts to position water within the triboelectric series, we investigate the charge on individual, millimetric water drops falling through air. Our experiments measured the charge and mass of each drop using a Faraday cup mounted on a mass balance, and connected to an electrometer. For pure water in a glass syringe with a grounded metal tip, we find the charge per drop ($\Delta q/\Delta m$) was approximately -5 pC/g to -1 pC/g. This was independent of the release height of the drop, tip diameter and length, tip cleaning preparation, and whether the experiment was shielded with a Faraday cage. Biasing the tip to different voltages allowed for linear control of the drop charge, and the results were consistent with known electrochemical effects, namely the Volta potential expected between most metals and bulk water ($\approx$ -0.5 V). Introducing insulating plastic materials into the experiment (from the syringe body or tip) imparted large amounts of charge on the drops with apparent stochastic charge evolution. Together these results show that the flow electrification of water is more complex than previously reported, and is driven by various, material-dependent electrostatic processes., Comment: 9 pages, 6 figures

Motivated by the differential basis theorem of Kolchin and the difference-differential basis theorem of Cohn, in this paper we present a basis theorem for polynomial rings equipped with commuting generalised Hasse-Schmidt operators (in the sense of Moosa and Scanlon). We recover Kolchin and Cohn's results as special cases of our main theorem., Comment: 21 pages

As Large Language Models (LLMs) are integrated into electronic health record (EHR) workflows, validated instruments are essential to evaluate their performance before implementation. Existing instruments for provider documentation quality are often unsuitable for the complexities of LLM-generated text and lack validation on real-world data. The Provider Documentation Summarization Quality Instrument (PDSQI-9) was developed to evaluate LLM-generated clinical summaries. Multi-document summaries were generated from real-world EHR data across multiple specialties using several LLMs (GPT-4o, Mixtral 8x7b, and Llama 3-8b). Validation included Pearson correlation for substantive validity, factor analysis and Cronbach's alpha for structural validity, inter-rater reliability (ICC and Krippendorff's alpha) for generalizability, a semi-Delphi process for content validity, and comparisons of high-versus low-quality summaries for discriminant validity. Seven physician raters evaluated 779 summaries and answered 8,329 questions, achieving over 80% power for inter-rater reliability. The PDSQI-9 demonstrated strong internal consistency (Cronbach's alpha = 0.879; 95% CI: 0.867-0.891) and high inter-rater reliability (ICC = 0.867; 95% CI: 0.867-0.868), supporting structural validity and generalizability. Factor analysis identified a 4-factor model explaining 58% of the variance, representing organization, clarity, accuracy, and utility. Substantive validity was supported by correlations between note length and scores for Succinct (rho = -0.200, p = 0.029) and Organized ($\rho = -0.190$, $p = 0.037$). Discriminant validity distinguished high- from low-quality summaries ($p < 0.001$). The PDSQI-9 demonstrates robust construct validity, supporting its use in clinical practice to evaluate LLM-generated summaries and facilitate safer integration of LLMs into healthcare workflows.

Recent high-throughput experiments unveil substantial electrophysiological diversity among uncoupled healthy myocytes under identical conditions. To quantify inter-cell variability, the values of a subset of the parameters in a well-regarded mathematical model of the action potential of rabbit ventricular myocytes are estimated from fluorescence voltage measurements of a large number of cells. Statistical inference yields a population of nearly 1200 cell-specific model variants that, on a population-level replicate experimentally measured biomarker ranges and distributions, and in contrast to earlier studies, also match experimental biomarker values on a cell-by-cell basis. This model population may be regarded as a random sample from the phenotype of healthy rabbit ventricular myocytes. Uni-variate and bi-variate joint marginal distributions of the estimated parameters are presented, and the parameter dependencies of several commonly utilised electrophysiological biomarkers are revealed. Parameter values are weakly correlated, while summary metrics such as the action potential duration are not strongly dependent on any single electrophysiological characteristic of the myocyte. Our results demonstrate the feasibility of accurately and efficiently fitting entire action potential waveforms at scale. Keywords: cellular excitability, rabbit ventricular myocytes, fluorescence voltage measurements, action potential waveform, parameter estimation in differential equations, noisy time series, Comment: Accepted for publication in Royal Society Open Science (ISSN:2054-5703) on 2025-01-13. Supplementary material available as open source from Royal Society Open Science

We introduce an electronic structure approach for spin symmetry breaking and restoration from the mean-field level. The spin-projected constrained-unrestricted Hartree-Fock (SPcUHF) method restores the broken spin symmetry inherent in spin-constrained-UHF determinants by employing a non-orthogonal Configuration Interaction (NOCI) projection method. This method includes all possible configurations in spin space compatible with a Clebsch-Gordon recoupling scheme in a NOCI calculation. The tunable one-pair-at-a-time characteristics of the symmetry-breaking process in c-UHF allow us to reduce the computational costs of full projection. SPcUHF is tested on 4-, 6-, and 8-electron systems that exhibit dominant static and/or dynamic correlations.

We present a framework to classify PL-types of large censuses of triangulated $4$-manifolds, which we use to classify the PL-types of all triangulated $4$-manifolds with up to $6$ pentachora. This is successful except for triangulations homeomorphic to the $4$-sphere, $\mathbb{C}P^2$, and the rational homology sphere $QS^4(2)$, where we find at most four, three, and two PL-types respectively. We conjecture that they are all standard. In addition, we look at the cases resisting classification and discuss the combinatorial structure of these triangulations -- which we deem interesting in their own rights., Comment: 15 pages, 2 figures

Predicting the movement of the stock market and other assets has been valuable over the past few decades. Knowing how the value of a certain sector market may move in the future provides much information for investors, as they use that information to develop strategies to maximize profit or minimize risk. However, market data are quite noisy, and it is challenging to choose the right data or the right model to create such predictions. With the rise of large language models, there are ways to analyze certain data much more efficiently than before. Our goal is to determine whether the GPT model provides more useful information compared to other traditional transformer models, such as the BERT model. We shall use data from the Federal Reserve Beige Book, which provides summaries of economic conditions in different districts in the US. Using such data, we then employ the LLM's to make predictions on the correlations. Using these correlations, we then compare the results with well-known strategies and determine whether knowing the economic conditions improves investment decisions. We conclude that the Beige Book does contain information regarding correlations amongst different assets, yet the GPT model has too much look-ahead bias and that traditional models still triumph.

Topological Insulators (TIs) present an interesting materials platform for nanoscale, high frequency devices because they support high mobility, low scattering electronic transport within confined surface states. However, a robust methodology to control the properties of surface plasmons in TIs has yet to be developed. We propose that charge transfer between Bi$_2$Se$_3$ and crystalline C$_{60}$ films may provide tunable control of the two-dimensional plasmons in Bi$_2$Se$_3$. We have grown heterostructures of Bi$_2$Se$_3$/C$_{60}$ with exceptional crystallinity. Electron energy loss spectroscopy (EELS) reveals significant hybridisation of $\pi$ states at the interface, despite the expectation for only weak van der Waals interactions, including quenching of 2D plasmons. Momentum-resolved EELS measurements are used to probe the plasmon dispersion, with Density Functional Theory predictions providing an interpretation of results based on interfacial charge dipoles. Our measurements suggest a robust methodology for tuneable TI interfaces that can be engineered for plasmonic applications in computing, communications and sensing.

Furstenberg's $\times 2 \times 3$ conjecture has remained a central open problem in ergodic theory for over $50$ years, and it serves as the basic test case for a broad class of rigidity phenomena which are believed to hold in number-theoretic dynamics. More recently, two related statements have appeared in the literature: a question about periodic approximation raised by Levit and Vigdorovich in the context of approximate group theory and a periodic equidistribution conjecture formulated by Lindenstrauss. The purpose of this article is to provide equivalent formulations for these three statements in a complex-analytic setting and an operator-algebraic setting, giving nine conjectures grouped into three triples. The complex-analytic conjectures involve so-called Carath\'{e}odory functions on the unit disk that satisfy a certain functional identity, and we find that Furstenberg's conjecture is equivalent to the assertion that every such function is a convex combination of rational functions. The operator-algebraic conjectures involve tracial states on the full group $C^\ast$-algebra of a certain semidirect product, which is related to Baumslag-Solitar groups.

A search for proton decay into $e^+/\mu^+$ and a $\eta$ meson has been performed using data from a 0.373 Mton$\cdot$year exposure (6050.3 live days) of Super-Kamiokande. Compared to previous searches this work introduces an improved model of the intranuclear $\eta$ interaction cross section, resulting in a factor of two reduction in uncertainties from this source and $\sim$10\% increase in signal efficiency. No significant data excess was found above the expected number of atmospheric neutrino background events resulting in no indication of proton decay into either mode. Lower limits on the proton partial lifetime of $1.4\times\mathrm{10^{34}~years}$ for $p\rightarrow e^+\eta$ and $7.3\times\mathrm{10^{33}~years}$ for $p\rightarrow \mu^+\eta$ at the 90$\%$ C.L. were set. These limits are around 1.5 times longer than our previous study and are the most stringent to date.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need for advanced therapeutic strategies. Nanoparticle-based drug delivery systems have emerged as a promising approach to improve the specificity and efficacy of anticancer treatments. This review examines three cutting-edge mesoporous silica nanoparticle (MSN)-based drug delivery to introduce novel CRC therapy, each utilizing unique functionalization strategies for targeted drug release. The first system, hyaluronidase-responsive MSN-HA/DOX, employs biotin-modified hyaluronic acid to facilitate dual-stimulus drug release in the tumor microenvironment, exhibiting enhanced in vivo tumor inhibition. The DOX/SLN-PEG-Biotin utilizes polyethylene glycol and biotin to improve drug stability and target biotin-overexpressing CRC cells, demonstrating superior anti-cancer efficacy in vitro and in vivo. Lastly, galactosylated chitosan-functionalized MSNs enable targeted delivery through asialoglycoprotein receptors, providing controlled drug release and strong therapeutic potential. Collectively, these systems highlight the advancements in nanoparticle functionalization for CRC treatment, offering a pathway to overcome the limitations of conventional chemotherapy. Further research is required to translate these innovations into clinical practice, ensuring safety and scalability.

Hydroxyapatite nanoparticles (HANs) have emerged as a promising candidate for targeted drug delivery in the treatment of colon cancer, a disease that remains one of the leading causes of cancer-related deaths globally. In this study, we synthesized and characterized HANs for their potential use as drug delivery vehicle for anticancer drugs specifically targeting colon cancer treatment. Through various in vitro assays, including drug loading efficiency, release kinetics, we demonstrated that HANs exhibit efficient drug loading capacity, and sustained release behavior, which could collectively contribute to enhanced therapeutic outcomes against colon cancer cells. The findings highlight the potential of HANs to serve as a versatile platform for the targeted drug delivery of chemotherapeutic agents, offering a novel approach that could improve treatment efficacy while minimizing side effects due to biocompatibility of the particles. Future research should focus on in vivo studies and clinical translation to further validate the potential of HANs in cancer therapy as drug carrier.

The Milky Way's Central Molecular Zone (CMZ) differs dramatically from our local solar neighbourhood, both in the extreme interstellar medium conditions it exhibits (e.g. high gas, stellar, and feedback density) and in the strong dynamics at play (e.g. due to shear and gas influx along the bar). Consequently, it is likely that there are large-scale physical structures within the CMZ that cannot form elsewhere in the Milky Way. In this paper, we present new results from the Atacama Large Millimeter/submillimeter Array (ALMA) large programme ACES (ALMA CMZ Exploration Survey) and conduct a multi-wavelength and kinematic analysis to determine the origin of the M0.8$-$0.2 ring, a molecular cloud with a distinct ring-like morphology. We estimate the projected inner and outer radii of the M0.8$-$0.2 ring to be 79" and 154", respectively (3.1 pc and 6.1 pc at an assumed Galactic Centre distance of 8.2 kpc) and calculate a mean gas density $> 10^{4}$ cm$^{-3}$, a mass of $\sim$ $10^6$ M$_\odot$, and an expansion speed of $\sim$ 20 km s$^{-1}$, resulting in a high estimated kinetic energy ($> 10^{51}$ erg) and momentum ($> 10^7$ M$_\odot$ km s$^{-1}$). We discuss several possible causes for the existence and expansion of the structure, including stellar feedback and large-scale dynamics. We propose that the most likely cause of the M0.8$-$0.2 ring is a single high-energy hypernova explosion. To viably explain the observed morphology and kinematics, such an explosion would need to have taken place inside a dense, very massive molecular cloud, the remnants of which we now see as the M0.8$-$0.2 ring. In this case, the structure provides an extreme example of how supernovae can affect molecular clouds., Comment: 17 pages, 13 figures, and 2 tables. Published in Astronomy & Astrophysics

The use of Wikipedia citations in scholarly research has been the topic of much inquiry over the past decade. A cross-publisher study (Taylor & Francis and University of Michigan Press) convened by Digital Science was established in late 2022 to explore author sentiment towards Wikipedia as a trusted source of information. A short survey was designed to poll published authors about views and uses of Wikipedia and explore how the increased addition of research citations in Wikipedia might help combat misinformation in the context of increasing public engagement with and access to validated research sources. With 21,854 surveys sent, targeting 40,402 papers mentioned in Wikipedia, a total of 750 complete surveys from 60 countries were included in this analysis. In general, responses revealed a positive sentiment towards research citation in Wikipedia and the researcher engagement practices. However, our sub analysis revealed statistically significant differences when comparison articles vs books and across disciplines, but not open vs closed access. This study will open the door to further research and deepen our understanding of authors perceived trustworthiness of the representation of their research in Wikipedia.

Colorectal cancer (CRC) continues to be a significant global health burden, prompting the need for more effective and targeted therapeutic strategies. Nanoparticle-based drug delivery systems have emerged as a promising approach to address the limitations of conventional chemotherapy, offering enhanced specificity, reduced systemic toxicity, and improved therapeutic outcomes. This paper provides an in-depth review of the current advancements in the application of nanoparticles as vehicles for targeted drug delivery in CRC therapy. It covers a variety of nanoparticle types, including liposomes, polymeric nanoparticles, dendrimers, and mesoporous silica nanoparticles (MSNs), with a focus on their design, functionalization, and mechanisms of action. This review also examines the challenges associated with the clinical translation of these technologies and explores future directions, emphasizing the potential of nanoparticle-based systems to revolutionize CRC treatment.

We propose a novel framework for approximating the statistical properties of turbulent flows by combining variational methods for the search of unstable periodic orbits with resolvent analysis for dimensionality reduction. Traditional approaches relying on identifying all short, fundamental unstable periodic orbits to compute ergodic averages via cycle expansion are computationally prohibitive for high-dimensional fluid systems. Our framework stems from the observation in Lasagna, Phys. Rev. E (2020), that a single unstable periodic orbit with a period sufficiently long to span a large fraction of the attractor captures the statistical properties of chaotic trajectories. Given the difficulty of identifying unstable periodic orbits for high-dimensional fluid systems, approximate trajectories residing in a low-dimensional subspace are instead constructed using resolvent modes, which inherently capture the temporal periodicity of unstable periodic orbits. The amplitude coefficients of these modes are adjusted iteratively with gradient-based optimisation to minimise the violation of the projected governing equations, producing trajectories that approximate, rather than exactly solve, the system dynamics. A first attempt at utilising this framework on a chaotic system is made here on the Lorenz 1963 equations, where resolvent analysis enables an exact dimensionality reduction from three to two dimensions. Key observables averaged over these trajectories produced by the approach as well as probability distributions and spectra rapidly converge to values obtained from long chaotic simulations, even with a limited number of iterations. This indicates that exact solutions may not be necessary to approximate the system's statistical behaviour, as the trajectories obtained from partial optimisation provide a sufficient ``sketch'' of the attractor in state space.

This paper investigates quantum machine learning to optimize the beamforming in a multiuser multiple-input single-output downlink system. We aim to combine the power of quantum neural networks and the success of classical deep neural networks to enhance the learning performance. Specifically, we propose two hybrid quantum-classical neural networks to maximize the sum rate of a downlink system. The first one proposes a quantum neural network employing parameterized quantum circuits that follows a classical convolutional neural network. The classical neural network can be jointly trained with the quantum neural network or pre-trained leading to a fine-tuning transfer learning method. The second one designs a quantum convolutional neural network to better extract features followed by a classical deep neural network. Our results demonstrate the feasibility of the proposed hybrid neural networks, and reveal that the first method can achieve similar sum rate performance compared to a benchmark classical neural network with significantly less training parameters; while the second method can achieve higher sum rate especially in presence of many users still with less training parameters. The robustness of the proposed methods is verified using both software simulators and hardware emulators considering noisy intermediate-scale quantum devices.

Emergent effects can arise in multi-agent systems (MAS) where execution is decentralized and reliant on local information. These effects may range from minor deviations in behavior to catastrophic system failures. To formally define these effects, we identify misalignments between the global inherent specification (the true specification) and its local approximation (such as the configuration of different reward components or observations). Using established safety terminology, we develop a framework to understand these emergent effects. To showcase the resulting implications, we use two broadly configurable exemplary gridworld scenarios, where insufficient specification leads to unintended behavior deviations when derived independently. Recognizing that a global adaptation might not always be feasible, we propose adjusting the underlying parameterizations to mitigate these issues, thereby improving the system's alignment and reducing the risk of emergent failures., Comment: 18 pages, 3 figures, accepted for publication at the International Symposium on Leveraging Applications of Formal Methods (ISoLA 2024)

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Let $p$ be prime and $e,k$ be positive integers, and let $R = {\mathbb Z}_p[\sqrt[e]{p}]$. We calculate the Waring numbers $g_R(k)$ for many values of $p, e$, and $k$, and investigate how the Waring numbers for $p=2$ change as $e$ and $k$ vary., Comment: 18 pages, 3 figures