Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of including the adjoint sea ice rheology on estimating Arctic Ocean–sea ice state

Abstract. The adjoint assimilation method has been applied to coupled ocean and sea ice models for sensitivity studies and Arctic state estimations. However, the accuracy of the adjoint model is degraded by simplifications of the adjoint of the sea ice model, especially the adjoint sea ice rheologies. As part of ongoing developments in coupled ocean and sea ice estimation systems, we incorporate and approximate the adjoint of viscous-plastic sea ice dynamics (adjoint-VP) and compare it with the adjoint of free-drift sea ice dynamics (adjoint-FD) through assimilation experiments. Using the adjoint-VP results in a further cost reduction of 7.9 % in comparison to adjoint-FD, with noticeable improvements in the ocean temperature over the open water and the intermediate layers of the Arctic Ocean. Adjoint-VP adjusts the model input more efficiently than adjoint-FD does by involving different sea ice retreat processes. For instance, adjoint-FD melts the sea ice up to 1.0 m in the marginal seas from May to June by overadjusting air temperature (>8 ∘C); adjoint-VP reproduces the sea ice retreat with smaller adjustments to the atmospheric state within their prior uncertainty range. These developments of the adjoint model here lay the foundation for further improving Arctic Ocean and sea ice estimations by comprehensively adjusting the initial conditions, atmospheric forcings, and parameters of the model.
Quantitative Chemical Assay of Nanogram-Level PM Using Aerosol Mass Spectrometry: Characterization of Particles Collected from Uncrewed Atmospheric Measurement Platforms

Aerosol generation techniques have expanded the utility of aerosol mass spectrometry (AMS) for offline chemical analysis of airborne particles and droplets. However, standard aerosolization techniques require relatively large liquid volumes (e.g., several milliliters) and high sample masses that limit their utility. Here we report the development and characterization of a micronebulization-AMS (MN-AMS) technique that requires as low as 10 μ L of sample and can provide quantification of nanogram level of organic and inorganic substances via the usage of an isotopically labeled internal standard ( 34 SO 42- ). Using 15 standard solutions, the detection limits for this technique were determined at 0.189, 0.751, and 2.19 ng for sulfate, nitrate, and organics, respectively. The analytical recoveries for these species are 104%, 87%, and 94%, respectively. This MN-AMS technique was applied successfully to analyzing filter and impactor samples collected using miniature PM samplers deployable on uncrewed atmospheric measurement platforms, such as uncrewed aerial systems (UAS) and tethered balloon systems (TBS). Chemical composition of PM samples collected from a UAS field campaign conducted at the DOE Southern Great 20 Plains (SGP) observatory was characterized. The offline MN-AMS data compared well with the in situ PM composition measured by a co-located Aerosol Chemical Speciation Monitor (ACSM). In addition, the MN-AMS and ion chromatography (IC) agreed well for measurements of sulfate and nitrate concentrations in the PM extracts. This study demonstrates the utility of combining MN-AMS with uncrewed measurement platforms to provide quantitative measurements of ambient PM composition with temporal and spatial resolution. for ambient samples without an independent measurement of sulfate concentration. We also present the
Investigating the dependence of mineral dust depolarization on complex refractive index and size with a laboratory polarimeter at 180.0° lidar backscattering angle

Abstract. In this paper, the dependence of the particles' depolarization ratio (PDR) of mineral dust on the complex refractive index and size is for the first time investigated through a laboratory π-polarimeter operating at 180.0∘ backscattering angle and at (355, 532) nm wavelengths for lidar purposes. The dust PDR is indeed an important input parameter in polarization lidar experiments involving mineral dust. Our π-polarimeter provides 16 accurate (<1 %) values of the dust lidar PDR at 180.0∘ corresponding to four different complex refractive indices, studied at two size distributions (fine, coarse) ranging from 10 nm to more than 10 µm and at (355, 532) nm wavelengths while accounting for the highly irregular shape of mineral dust, which is difficult to model numerically. At 355 nm, the lidar PDR of coarser silica, the main oxide in mineral dust, is equal to (33±1) %, while that of coarser hematite, the main light absorbent in mineral dust, is (10±1) %. This huge difference is here explained by accounting for the high imaginary part of the hematite complex refractive index. In turn, Arizona dust exhibits higher depolarization than Asian dust, due to the higher proportion in hematite in the latter. As a result, when the strong light-absorbent hematite is involved, the dust lidar PDR primarily depends on the particles' complex refractive index, and its variations with size and shape are less pronounced. When hematite is less or not involved, the dust lidar PDR increases with increasing sizes, though the shape dependence may then also play a role. The (355, 532) nm wavelength dependence of the dust lidar PDR then allows discussing on the involved particle sizes, thus highlighting the importance of dual-wavelength (or more) polarization lidar instruments. We believe these laboratory findings will help improve our understanding of the challenging dependence of the dust lidar PDR with complex refractive index and size to help interpret the complexity and the wealth of polarization lidar signals.
Connectivity Properties of the Flip Graph After Forbidding Triangulation Edges

The flip graph for a set P of points in the plane has a vertex for every triangulation of P , and an edge when two triangulations differ by one flip that replaces one triangulation edge by another. The flip graph is known to have some connectivity properties: (1) the flip graph is connected; (2) connectivity still holds when restricted to triangulations containing some constrained edges between the points; (3) for P in general position of size n, the flip graph is ⌈ 2 − 2⌉-connected, a recent result of Wagner and Welzl (SODA 2020). We introduce the study of connectivity properties of the flip graph when some edges between points are forbidden. An edge e between two points is a flip cut edge if eliminating triangulations containing e results in a disconnected flip graph. More generally, a set X of edges between points of P is a flip cut set if eliminating all triangulations that contain edges of X results in a disconnected flip graph. The flip cut number of P is the minimum size of a flip cut set. We give a characterization of flip cut edges that leads to an O(n log n) time algorithm to test if an edge is a flip cut edge and, with that as preprocessing, an O(n) time algorithm to test if two triangulations are in the same connected component of the flip graph. For a set of n points in convex position (whose flip graph is the 1-skeleton of the associahedron) we prove that the flip cut number is n− 3.
Organic Agriculture Harmony in Nutrition, Environment and Health: Case Study in Iran

 Abstract — Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20 th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.
Editing Fluid Flows with Divergence-Free Biharmonic Vector Field Interpolation

Achieving satisfying fluid animation through numerical simulation can be time-consuming because such simulations are computationally expensive to perform and there are few practical post-processing tools for editing of completed simulations – often, the user must modify their scene setup and launch it again from scratch. To address this challenge, we present a divergence-free biharmonic vector field interpolation and extrapolation method for reusing and/or stitching together spatial regions of existing flows. Given velocities and velocity gradients on the boundary of a domain at each timestep, which may be either user-defined or drawn from existing simulations, we fill in the given domain by constructing an optimally smooth, divergence-free, boundary-satisfying vector field. We measure smoothness using the Laplacian energy to allow smooth boundary behavior and enforce divergence constraints through explicit Lagrange multipliers. The prior methods for this problem suffer from non-zero divergence and associated visible compression artifacts, or cannot smoothly match the desired slopes at the domain boundaries. Moreover, we introduce a new extrapolation scheme that can handle unprescribed boundaries by smoothly extending the vector field through the unspecified boundary. In this case, we measure the smoothness using the Hessian energy which provides well-behaved solutions for “free” or natural boundary conditions. We demonstrate that our new interpolation and extrapolation procedures always produce smooth and incompressible flows, as well as enabling a range of natural simulation editing capabilities including hole-filling, copy-pasting, extrapolation, and scene stretching.
A cloud screening algorithm for ground-based sun photometry using all-sky images and deep transfer learning

Aerosol optical depth (AOD) is used to characterize aerosol loadings within Earth’s atmosphere. Sun photometers measure AOD from the Earth’s surface based on direct-sunlight intensity readings by spectrally narrow light detectors. However, when the solar disk is partially obscured by cloud cover, sun photometer measurements can be biased due to the interaction of sunlight with cloud constituents. We present a novel deep transfer learning 15 model on all-sky images to support more accurate AOD retrievals. We used three independent image datasets for training and testing: the novel Northern Colorado All-Sky Image (NCASI), the Whole Sky Image SEGmentation (WSISEG), and the METCRAX-II datasets from the National Center for Atmospheric Research (NCAR). We visually partitioned all-sky images into three categories: 1) clear sky around the solar disk, 2) thin cirrus obstructing the solar disk, and 3) thick, non-cirrus clouds obstructing the solar disk. Two-thirds of the images were allocated for 20 training and one-third were allocated for testing. We trained models based on all possible combinations of the training sets. The best-performing model successfully classified 95.5%, 96.9%, and 89.1% of testing images from NCASI, METCRAX-II and WSISEG datasets, respectively. Our results demonstrate that all-sky imaging with deep transfer learning can be applied toward cloud screening, which would aid ground-based AOD measurements. and bias parameters of the output were the only trainable parameters, which comprised 0.51% of the total model parameters.To limit overfitting, we applied data augmentation, which supplements training data by producing batches of randomly 215 modified images created via transformation operations. We implemented data augmentation in Tensorflow using the ImageDataGenerator module (Abadi et al., 2015) allowing rotation of 20 degrees, width/height shifting of 10%, a classifies
Current-induced magnetic vortex motion by spin-transfer torque

We investigate the dynamics of a magnetic vortex driven by spin-transfer torque due to spin current in the adiabatic case. The vortex core represented by collective coordinate experiences a transverse force proportional to the product of spin current and gyrovector, which can be interpreted as the geometric force determined by topological charges. We show that this force is just a reaction force of Lorentz-type force from the spin current of conduction electrons. Based on our analyses, we propose analytically and numerically a possible experiment to check the vortex displacement by spin current in the case of single magnetic nanodot.
A Survey of 30SiO Emission from Evolved Stars

We present the first detection of 30SiO v = 1, J = 1–0 maser emission toward the Mira variable TX Cam among 18 surveyed evolved stars. The line width of this maser is much narrower than that of 30SiO v = 0, J = 1–0 masers and the intensity is also weaker, indicating that it is unsaturated. The detection of the 30SiO maser emission in the lowest rotational transition of the first vibrationally excited state, together with nearly simultaneous observations of the large number of 29SiO and 28SiO masers, provides good constraints for establishing the SiO maser pumping model of TX Cam. The global features of 30SiO and 29SiO v = 1, J = 1–0 lines are similar, but detailed characteristics, such as their half-widths, their peak intensity ratios of the v = 1, J = 1–0 line to the v = 0, J = 1–0 line, and their intensity variation with time, are different. New detection of the 30SiO v = 0, J = 1–0 and J = 2–1 lines is also reported in six evolved stars: TX Cam, R Cas, χ Cyg, W Hya, U Lyn, and WX Psc. They show a different masing characteristics of the 30SiO that depends on both sources and transitions. This is probably related to a critical condition for masing.
Multi-million-year cycles in modelled δ13C as a response to astronomical forcing of organic matter fluxes

Abstract. Along with 400 kyr periodicities, multi-million-year cycles have been found in δ13C records over different time periods. An ∼ 8–9 Myr periodicity is found throughout the Cenozoic and part of the Mesozoic. The robust presence of this periodicity in δ13C records suggests an astronomical origin. However, this periodicity is barely visible in the astronomical forcing. Due to the large fractionation factor of organic matter, its burial or oxidation produces large δ13C variations for moderate carbon variations. Therefore, astronomical forcing of organic matter fluxes is a plausible candidate to explain the oscillations observed in the δ13C records. So far, modelling studies forcing astronomically the organic matter burial have been able to produce 400 kyr and 2.4 Myr cycles in δ13C but were not able to produce longer cycles, such as 8–9 Myr cycles. Here, we propose a mathematical mechanism compatible with the biogeochemistry that could explain the presence of multi-million-year cycles in the δ13C records and their stability over time: a preferential phase locking to multiples of the 2.4 Myr eccentricity period. With a simple non-linear conceptual model for the carbon cycle that has multiple equilibria, we are able to extract longer periods than with a simple linear model – more specifically, multi-million-year periods.
Quantitative comparison of methods and sensors for monitoring land subsidence based on SAR interferometric stacking

Interferometric stacking techniques emerged in the last decade as methods to obtain very precise measurements of terrain displacements, and in particular subsidence phenomena. In particular, the so-called Persistent Scatterers (Ferretti et al. 2001) and Small BASeline (Berardino et al. 2002) methods can be considered as the two most representative stacking approaches. In both cases, the exploitation of 20 or more satellite Synthetic Aperture Radar (SAR) acquisitions obtained from the same satellite sensor with similar geometries on the interest area allows to measure displacements with an accuracy in the order of few mm / year, and to derive the full location history of good pixels with an accuracy of 1cm or better for every available date. A main difference between the two approaches is the type of objects and land cover that are favoured in the analysis: the PS technique focuses on so-called Point Targets, i.e. objects possibly of small size and with a very well characterized geometry like corner reﬂectors (e.g. buildings, rocks) and with a high temporal stability of the backscattered signal; the SBAS technique vice-versa is concentrating the analysis on so-called distributed targets, like open ﬁelds and not very geometrically characterized objects. The PS approach is then not making any assumption on spatial correlation of the displacement to be measured, but more on its linearity; the SBAS approach vice-versa is more robust in case of spatially correlated displacements, and allows in this case to monitor larger displacement rates. This paper is performing an extensive analysis and comparison of the results that have been obtained with the two approaches in a same geographical area in Japan, characterized by subsidence due to water and natural gas extraction. The analysis is based on data acquired from the ALOS PALSAR (L-band), ENVISAT ASAR (C-band) and COSMO-Skymed (X-band) satellite instruments, and the validation of the results is based on GPS and leveling measurements. The analysis allows to draw conclusions on pros and cons of the different approaches and sensors for deriving the displacement measures for monitoring subsidence phenomena. The feasibility of exploiting the same approach in different geographical areas is also discussed. Finally, comments are given on the outcomes of this analysis in view of the exploitation of the data to be available from the forthcoming Sentinel-1 (C-Band) and ALOS-2 (L-Band) missions.
A method for generating a quasi-linear convective system suitable for observing system simulation experiments

Abstract. To understand the impact of different assimilated observations on convection-allowing model forecast skill, a diverse range of observing system simulation experiment (OSSE) case studies are required (different storm modes and environments). Many previous convection-allowing OSSEs predicted the evolution of an isolated supercell generated via a warm air perturbation in a horizontally homogenous environment. This study introduces a new methodology in which a quasi-linear convective system is generated in a highly sheared and modestly unstable environment. Wind, temperature, and moisture perturbations superimposed on a horizontally homogeneous environment simulate a cold front that initiates an organized storm system that spawns multiple mesovortices. Mature boundary layer turbulence is also superimposed onto the initial environment to account for typical convective-scale uncertainties. Creating an initial forecast ensemble remains a challenge for convection-allowing OSSEs because mesoscale uncertainties are difficult to quantify and represent. The generation of the forecast ensemble is described in detail. The forecast ensemble is initialized by 24 h full-physics simulations (e.g., radiative forcing, surface friction, and microphysics). The simulations assume different surface conditions to alter surface moisture and heat fluxes and modify the effects of friction. The subsequent forecast ensemble contains robust non-Gaussian errors that persist until corrected by the data assimilation system. This purposely degraded initial forecast ensemble provides an opportunity to assess whether assimilated environmental observations can improve, e.g., the wind profile. An example OSSE suggests that a combination of radar and conventional (surface and soundings) observations are required to produce a skilled quasi-linear convective system forecast, which is consistent with real-world case studies. The OSSE framework introduced in this study will be used to understand the impact of assimilated environmental observations on forecast skill.
Efficient and Generic Transformations for Chosen-Ciphertext Secure Predicate Encryption

Predicate encryption (PE) is a type of public-key encryption that captures many useful primitives such as attribute-based encryption (ABE). Although much progress has been made to generically achieve security against chosen-plaintext attacks (CPA) efficiently, in practice, we also require security against chosen-ciphertext attacks (CCA). Because achieving CCA-security on a case-by-case basis is a complicated task, several generic conversion methods have been proposed. However, these conversion methods may incur a significant efficiency trade-off. Notably, for ciphertext-policy ABE, all generic conversion methods provide a significant overhead in the key generation, encryption or decryption algorithm. Additionally, many generic conversion techniques use one-time signatures to achieve authenticity, which are also known to significantly impact the efficiency. In this work, we present a new approach to achieving CCA-security as generically and efficiently as possible, by splitting the CCA-conversion in two steps. The predicate of the scheme is first extended in a certain way, which is then used to achieve CCA-security generically e.g., by combining it with a hash function. To facilitate the first step efficiently, we also propose a novel predicate-extension transformation for a large class of pairing-based PE—covered by the pair and the predicate encodings frameworks—which incurs only a small constant overhead for all algorithms. In particular, this yields the most efficient generic CCAconversion for ciphertext-policy ABE.
Merger versus Accretion and the Structure of Dark Matter Halos

High-resolution N-body simulations of hierarchical clustering in a wide variety of cosmogonies show that the density profiles of dark matter halos are universal, with low-mass halos being denser than their more massive counterparts. This mass-density correlation is interpreted as reflecting the earlier typical formation time of less massive objects. We investigate this hypothesis in the light of formation times defined as the epoch at which halos experience their last major merger. Such halo formation times are calculated by means of a modification of the extended Press & Schechter formalism that includes a phenomenological frontier, Δm, between tiny and notable relative mass captures leading to the distinction between merger and accretion. For Δm ~ 0.6, we confirm that the characteristic density of halos is essentially proportional to the mean density of the universe at their time of formation. Yet, proportionality with respect to the critical density yields slightly better results for open universes. In addition, we find that the scale radius of halos is also essentially proportional to their virial radius at the time of formation. We show that these two relations are consistent with the following simple scenario. Violent relaxation caused by mergers rearranges the structure of halos leading to the same density profile with universal values of the dimensionless characteristic density and scale radius. Between mergers, halos grow gradually through the accretion of surrounding layers by keeping their central parts steady and expanding their virial radius as the critical density of the universe diminishes.
CPSC 532D — STATISTICAL LEARNING THEORY

2 PAC learning and finite hypothesis classes 3 2.1 Realizable finite hypothesis classes . 3 2.2 PAC learning . 5 2.3 Agnostic PAC learning . 5 2.4 Uniform convergence and ERM . 6 2.5 ERM agnostically PAC learns finite classes . 7