Miracle-dz/UniFAR-FTUs huggingface dataset:
pH dependence of brown-carbon optical properties in cloud water

Abstract. Light-absorbing organic species present in aerosols, collectively called brown carbon (BrC), have important but highly uncertain effects on climate. Clouds likely represent a significant medium for secondary BrC production and for bleaching reactions, though the relative importance of the formation and loss processes in clouds is unknown at present. The acidity (or pH) of atmospheric particles and clouds affects the optical properties of BrC and bleaching rates. Given the wide variability of pH in the atmosphere (pH in particles and clouds ranges from −1 to 8), the optical properties of BrC and its bleaching behavior are expected to vary significantly, and the link between pH and BrC is yet another uncertainty in attempts to constrain its climate forcing effects. In this work, we characterize the pH dependence of BrC optical properties – including light absorption at 365 nm (Abs365), the mass absorption coefficient (MAC365), and the absorption Ångström exponent (AAE) – in bulk cloud water sampled from the summit of Whiteface Mountain, NY. In all samples (n=17), Abs365 and MAC365 increased linearly with increasing pH, highlighting the importance of reporting pH in studies of BrC in aqueous media. There was strong variability in the sensitivity of Abs365 to pH, with normalized slopes that ranged from 5.1 % to 17.2 % per pH unit. The normalized slope decreased strongly with increasing cloud water [K+], suggesting that the non-biomass-burning BrC has optical properties that are more sensitive to pH than BrC associated with biomass burning. AAE also showed a distinct pH dependence as it was relatively flat between pH 1.5–5 and then decreased significantly above pH 5. The cloud water composition was used to inform thermodynamic predictions of aerosol pH upwind and/or downwind of Whiteface Mountain and the subsequent changes in BrC optical properties. Overall, these results show that, in addition to secondary BrC production, photobleaching, and the altitudinal distribution, the climate forcing of BrC is quite strongly affected by its pH-dependent absorption.
Evaluation of modelled climatologies of O3, CO, water vapour and NOy in the upper troposphere–lower stratosphere using regular in situ observations by passenger aircraft

Abstract. Evaluating global chemistry models in the upper troposphere–lower stratosphere (UTLS) is an important step toward an improved understanding of the chemical composition in this region. This composition is regularly sampled through in situ measurements based on passenger aircraft, in the framework of the In-service Aircraft for a Global Observing System (IAGOS) research infrastructure. This study focuses on the comparison of the IAGOS measurements in ozone, carbon monoxide (CO), nitrogen reactive species (NOy) and water vapour, with a 25-year simulation output from the LMDZ-OR-INCA chemistry–climate model. For this purpose, we present and apply an extension of the Interpol-IAGOS software that projects the IAGOS data onto any model grid, in order to derive a gridded IAGOS product and a masked (sub-sampled) model product that are directly comparable to one another. Climatologies are calculated in the upper troposphere (UT) and in the lower stratosphere (LS) separately but also in the UTLS as a whole, as a demonstration for the models that do not sort out the physical variables necessary to distinguish between the UT and the LS. In the northern extratropics, the comparison in the UTLS layer suggests that the geographical distribution in the tropopause height is well reproduced by the model. In the separated layers, the model simulates well the water vapour climatologies in the UT and the ozone climatologies in the LS. There are opposite biases in CO in both UT and LS, which suggests that the cross-tropopause transport is overestimated. The NOy observations highlight the difficulty of the model in parameterizing the lightning emissions. In the tropics, the upper-tropospheric climatologies are remarkably well simulated for water vapour. They also show realistic CO peaks due to biomass burning in the most convective systems, and the ozone latitudinal variations are well correlated between the observations and the model. Ozone is more sensitive to lightning emissions than to biomass burning emissions, whereas the CO sensitivity to biomass burning emissions strongly depends on location and season. The present study demonstrates that the Interpol-IAGOS software is a tool facilitating the assessment of global model simulations in the UTLS, which is potentially useful for any modelling experiment involving chemistry climate or chemistry transport models.
On the Efficiency Analysis of {wNAF} and {wMOF}

Elliptic Curve Cryptosystems (ECC)[1] are much more suitable for small memory device such as smart cards rather than Rivest Shamir Adleman (RSA) cryptosystems due to their small key size. In fact, an EC cryptosystem with a 160-bit-key-size and a RSA cryptosystem with a 1024-bit-key-size both have the same security level. However, when put the ECC into practice, the major problem is how to enhance the speed of the scalar multiplication, which the most important operation in ECC with limited memory resources. The most common scalar multiplication algorithm based on the binary method with pre-computation, for example sliding window on NAF, wNAF, MOF and wMOF. In this paper, we will analyze some details of wNAF (w-width non-adjacentform) and wMOF (w-width mutual-opposite-form), from which we know how they raise the speed of scalar multiplication in ECC, how much efficiency they have raised and some other details. Our basic aim is to is analyze some attributes of wNAF and wMOF, to compare them with theories and to test them by practice. For the exhaustive analysis of ECC scalar multiplication with a particular exponent recoding method, it is very important to know the average amount of 0s and non-0s in the achieved form, the average length of consecutive 0s and the average bit-length of the output in the achieved form. If we knew them in advance, we could optimize the code and save more memory resources. In this paper we will discuss these three attributes of wNAF form and wMOF form. (1) What is the average amount of 0s and non-0s? (2) What is the average length of consecutive 0s? (3) What is the average bit-length?
Understanding representations of uncertainty, an eye-tracking study part II: The effect 1 of expertise 2

As the ability to make predictions of uncertainty information representing natural 20 hazards increases, an important question for those designing and communicating hazard 21 forecasts is how visualisations of uncertainty influence understanding amongst the intended, 22 potentially varied, target audiences. End-users have a wide range of differing expertise and 23 backgrounds, possibly influencing the decision-making process they undertake for a given 24 forecast presentation. Our previous, linked study, examined how the presentation of 25 uncertainty information influenced end-user decision making. Here, we shift the focus to 26 examine the decisions and reactions of participants with differing expertise (Meteorology, 27 Psychology and Graphic Communication students) when presented with varied hypothetical 28 forecast representations (boxplot, fan plot or spaghetti plot with and without median lines), 29 using the same eye-tracking methods and experiments. Participants made decisions about a 30 fictional scenario involving the choices between ships of different sizes in the face of varying 31 ice thickness forecasts. Eye-movements to the graph area and key, and how they changed 32 over time (early, intermediate, and later viewing periods), were examined. More fixations 33 (maintained gaze on one location) and time fixating was spent on the graph and key during 34 early and intermediate periods of viewing, particularly for boxplots and fan plots. The 35 inclusion of median lines led to less fixations being made to all graph types during early and 36 intermediate viewing periods. No difference in eye movement behaviour was found due to 37 expertise, however those with greater expertise were more accurate in their decisions, 38 particularly during more difficult scenarios. Where scientific producers seek to draw users to 39 the central estimate, an anchoring line can significantly reduce cognitive load leading both 40 experts and non-experts to make more rational decisions. When asking users to consider 41 extreme scenarios or uncertainty, different prior expertise can lead to significantly different 42 cognitive load for processing information with an impact on ability to make appropriate 43 decisions. 44
E ﬀ ects of Potassium Doping on the Active Layer of Inverse-Structured Perovskite Solar Cells

SUMMARY In this report, solar cell characteristics were evaluated by doping the active layer CH 3 NH 3 PbI 3 (MAPbI 3 ) with 3.0 vol% and 6.0 vol% of potassium ion (KI) in an inverse-structured perovskite solar cells (PSCs). The Tauc plots of the absorbance characteristics and the ionization potential characteristics show that the top end of the valence band shifted by 0.21eV in the shallow direction from − 5.34eV to − 5.13eV, and the energy band gap decreased from 1.530eV to 1.525eV. Also, the XRD measurements show that the lattice constant decreased from 8. 96Å to 8. 93Å when KI was doped. The decrease in the lattice constant indicates that a part of the A site is replaced from methylammonium ion (MAI) to KI. In the J-V characteristics of the solar cell, the mean value of J sc improved from 7.0mA / cm 2 without KI to 8.8mA / cm 2 with 3.0 vol% of KI doped and to 10.2mA / cm 2 with 6.0 vol% of KI doped. As a result, the mean value of power-conversion e ﬃ ciency (PCE) without KI was 3.5%, but the mean value of PCE improved to 5.2% with 3.0 vol% of KI doped and to 4.5% with 6.0 vol% of KI doped. Thus, it has shown that it is e ﬀ ective to dope KI to MAIPBI 3 , which serves as the active layer, even in the inverse-structured PSCs.
The Origin of Randomness in Quantum Mechanics

A mysterious problem of randomness in quantum mechanics is revisited. This problem being hidden in the Schrodinger equation becomes transparent in its Madelung version. It has been demonstrated that randomness in quantum mechanics has the same mathematical source as that in turbulence and chaos. Special attention is concentrated on equivalence between the Schrodinger and the Madelung equations in connection with the concept of stability in dynamics.
Toward a New UV Index Diagnostic in the Met Office's Forecast Model

The United Kingdom sporadically experiences low ozone events in the spring which can increase UV to harmful levels and is particularly dangerous as sunburn is not expected by the public at this time of year. This study investigates the benefits to the UV Index diagnostic produced by the UM at the Met Office of including either, or both of, a more highly resolved spectrum, and forecasted ozone profiles from the ECMWF CAMS database. Two new configurations of the spectral parameters governing the radiative transfer calculation over the UV region are formulated using the correlated‐k method to give surface fluxes that are within 0.1 UV Index of an accurate reference scheme. Clear‐sky comparisons of modeled fluxes with ground‐based spectral observations at two UK sites (Reading and Chilton) between 2011 and 2015 show that when raw CAMS ozone profiles are included noontime UV indices are always overestimated, by up to 3 UV indices at a low ozone event and up to 1.5 on a clear summer day, suggesting CAMS ozone concentrations are too low. The new spectral parameterizations reduce UV Index biases, apart from when combined with ozone profiles that are significantly underestimated. When the same biases are examined spectrally across the UV region some low biases on low ozone days are found to be the result of compensating errors in different parts of the spectrum. Aerosols are postulated to be an additional source of error if their actual concentrations are higher than those modeled.
Tracing subducted oceanic slabs in the mantle by 1 using molybdenum isotopes: A case study of 2 intraplate basalts from the Northeast China 3

23 Determining subducted processes is very important for understanding lithological 24 heterogeneity because substantial quantities of slabs are recycled into the mantle. Molybdenum 25 isotopes have been used to distinguish sources materials because of the significant Mo isotopic 26 differences between the crust and the mantle. Here, we undertake a systematic Mo isotopic 27 investigation on a suite of well-characterized continental basalts from Keluo and Halaha-28 Chaoer, located in Northeast China. δ 98 Mo of Keluo varied from -0.41 to -0.23‰ with an 29 average of -0.34‰, and samples from Halaha-Chaoer ranged in δ 98 Mo from -0.18 to -0.12‰ 30 with an average of -0.15‰. The former is lighter than the mean value of fresh oceanic basalts 31 (-0.21‰), while the latter is similar to oceanic basalts. Combined with other geochemical 32 indications (LOI, Ce/Pb, La/Yb and so on), the Mo isotopic variations cannot be interrupted by 33 chemical weathering, continental crust contamination, or magmatic processes. The δ 98 Mo 34 variation in this study is explained by adding various oceanic crustal materials in magma 35 sources. The relationships of δ 98 Mo with Ba/Th, Th/U, 143 Nd/ 144 Nd for the samples indicated 36 that sediment and altered oceanic crust have contributed to the significant variations in these 37 samples. This study indicates the great potential of Mo isotopes to distinguish different types 38 of recycled oceanic crust materials in the mantle. 39
Northwestern University Initiatives on Resource and Education Development for Collaborative AI in Learning Health System

Introduction: Artificial intelligence (AI) has gained increasing momentum in health care research and application. The rapid development of learning health systems exposed the unmet need for growing a multidisciplinary workforce that can work synergistically and effectively in the dynamically evolving health care landscape. Maximizing the synergy among the multidisciplinary workforce will produce positive impact towards Collaborative AI in Health Care. Methods: We describe how we are developing a series of data, tools, and education resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Health Care. Our muti-pronged approach builds a convener for Collaborative AI in Health Care by democratizing access to un-structured health information, democratizing access to AI/ML tools and resources for health care, and de-mocratizing access to collaborative education resource. Results: Our bulk-NLP pipelines extracted structural information from clinical notes and persisted them in common data models to power research and development efforts and drive business intelligence. The developed AI/ML tools and tutorials have enriched the toolbox of the multidisciplinary workforce to analyze multi-modal health care data. The AI4H clinics have created a natural convener to bring together clinicians and AI scientists and train the next generation of AI health workforce to collaborate smoothly. Conclusions: Our Collaborative AI in Health Care initiatives have created valuable educational and practical resources. They enabled more clinicians, scientists and hospital administrators in successfully applying AI methods in their daily research and practice, bridged closer collaboration, and advanced the institution-level learning health system.
CoviText: Motor de

In the first months of 2020, the COVID-19 pandemic has severely affected several countries, including Brazil. Due to the possibility of collapse in health systems and economic losses, there is an increasing number of related researches, generating a large volume of scholarly articles, such as the CORD-19 dataset (87.5 GB, base year: 2022), available at the Kaggle website. Due to the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up, it is necessary to find ways of browsing and consulting what is already known about the Sars-Cov-2 virus and its related disease. In order to facilitate this process, this work presents the CoviText tool: a search engine for the medical literature on COVID-19, developed using text mining and machine learning techniques.
EncephalitisEpilepticus Associated with Acute Hippocampal Shape Analysis in Status

Summary: We performed MR imaging deformation-based hippocampal shape analysis in a 28-year-old woman in whom status epilepticus developed after acute encephalitis. Hippocampal shape analysis revealed severe global bilateral hippocampal atrophy. Regional volume loss was most accentuated in the medial and lateral aspects of the hippocampal head; the loss was similar to shape changes in hippocampal sclerosis of chronic temporal lobe epilepsy. This deformation pattern may reflect a common pathologic process that causes hippocampal volume loss in both of these conditions.
Singular geodesic coordinates for representing diffeomorphic maps in computational anatomy, with application to the morphometry of early Alzheimer's disease in the medial temporal lobe

In this work we develop novel algorithms for building one to one correspondences between anatomical forms by providing a sparse representation of dense registration information. These sparse parameterizations of complex high dimensional data allow robustness in the face of noise and anomalies, and a platform for inference that is effective in the face of multiple comparisons. We review background in the theory of generating smooth, invertible transformations (the diffeomorphism group), and build our parameterization as a function supported on surfaces bounding anatomical structures of interest. We show how dimensionality can be reduced even further and still provide a rich family of mappings using principal component analysis or Laplace Beltrami eigenfunctions supported on the surface. We develop algorithms for surface matching and image matching within this model, and demonstrate the desired robustness by working with published large neuroimaging datasets that include many low quality examples. Finally we turn to addressing challenges associated with some specific data types: images with multiple labels, and longitudinal data. We use the mapping tools developed to draw conclusions about the progression of early Alzheimer’s disease in the medial temporal lobe.
Data-Efficient Augmentation for Training Neural Networks

Data augmentation is essential to achieve state-of-the-art performance in many deep learning applications. However, the most effective augmentation techniques become computationally prohibitive for even medium-sized datasets. To address this, we propose a rigorous technique to select subsets of data points that when augmented, closely capture the training dynamics of full data augmentation. We first show that data augmentation, modeled as additive perturbations, improves learning and generalization by relatively enlarging and perturbing the smaller singular values of the network Jacobian, while preserving its prominent directions. This prevents overfitting and enhances learning the harder to learn information. Then, we propose a framework to iteratively extract small subsets of training data that when augmented, closely capture the alignment of the fully augmented Jacobian with labels/residuals. We prove that stochastic gradient descent applied to the augmented subsets found by our approach has similar training dynamics to that of fully augmented data. Our experiments demonstrate that our method achieves 6.3x speedup on CIFAR10 and 2.2x speedup on SVHN, and outperforms the baselines by up to 10% across various subset sizes. Similarly, on TinyImageNet and ImageNet, our method beats the baselines by up to 8%, while achieving up to 3.3x speedup across various subset sizes. Finally, training on and augmenting 50% subsets using our method on a version of CIFAR10 corrupted with label noise even outperforms using the full dataset. Our code is available at: https://github.com/tianyu139/data-efficient-augmentation
Who really discovered Snell's law?

Open any physics textbook and you'll soon come across what English-speaking physicists refer to as "Snell's law". The principle of refraction – familiar to anyone who has dabbled in optics – is named after the Dutch scientist Willebrord Snell (1591–1626), who first stated the law in a manuscript in 1621. In French, however, the same law is often called "la loi de Descartes" because it was Rene Descartes (1596–1650) who first put the law into widespread circulation in his Discourse on Method, published in 1637.
Starting from Non-Parametric Networks for 3D Point Cloud Analysis

We present a Non-parametric Network for 3D point cloud analysis, Point-NN, which consists of purely non-learnable components: farthest point sampling (FPS), k-nearest neighbors (k-NN), and pooling operations, with trigonometric functions. Surprisingly, it performs well on various 3D tasks, requiring no parameters or training, and even surpasses existing fully trained models. Starting from this basic non-parametric model, we propose two extensions. First, Point-NN can serve as a base architectural framework to construct Parametric Networks by simply inserting linear layers on top. Given the superior non-parametric foundation, the derived Point-PN exhibits a high performance-efficiency tradeoff with only a few learnable parameters. Second, Point-NN can be regarded as a plug-and-play module for the already trained 3D models during inference. Point-NN captures the complementary geometric knowledge and enhances existing methods for different 3D benchmarks without retraining. We hope our work may cast a light on the community for understanding 3D point clouds with non-parametric methods. Code is available at https://github.com/ZrrSkywalker/Point-NN.
51‐4: Near‐Eye Display for Vision Correction with Large FOV

We propose a see-through near-eye display capable of visual correction for -3.00-diopter myopia. Our solution features a freeform waveguide, which integrates a corrective lens and multiplexed volume holograms. Its key performance including diffraction efficiency, field of view, modulation transfer function, and distortion has been studied.
Exploring the Effects of Bilingualism Through Entrepreneurship

Entrepreneurship promotes research and development by launching innovations previously unavailable thus generating new wealth and advancement in society; however, reaching success, or startup stability and profitability, is statistically shown to consist of very slim margins. If failure rates are high what makes for an effective entrepreneur? As researchers study variables such as education and gender, this research considers language as an influencing factor of improved entrepreneurial capacity. Those who know two languages, also known as bilinguals, show increased proficiency in communication, selective attention, and task-switching. Consequently, this paper aims to explore the importance of entrepreneurship in the economy and the skills necessary to be a successful entrepreneur as well as investigate the effects of bilingualism, particularly in its abilities to enhance communication and cognition, in entrepreneurial pathways. The methodological approach of this research consists of standardized open-ended interviews with three monolingual entrepreneurs, which serve as a basis for comparison, and three bilingual entrepreneurs, with one question for income analysis as well. Each entrepreneur is evaluated as a separate case study, but overarching themes between groups are also cross-examined. The results will help further knowledge in commerce as entrepreneurs will be able to utilize this information to enhance their strategic decisions and business outcomes for the greater good of themselves and the economy.