Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends In Recurrent Clostridioides Difficile Infection In New Haven County

Background: Recurrent Clostridioides difficile infection (CDI) is a cause of increased burden on the healthcare system and factors associated with this disease merit understanding. This study aimed to determine the incidence rate and to describe the factors associated with recurrent CDI cases in New Haven County from 2015 to 2020. It also examined the trends in annual recurrent CDI cases across epidemiological classes. Methods: This study utilized data from a population-based surveillance program of the Healthcare-Associated Infectious Community Interface (HAIC) Program within the Connecticut Emerging Infectious Program (CT EIP) at Yale School of Public Health which served all residents of New Haven County. Annual incidence rates of CDI and recurrent CDI in aggregate and by epidemiological class were calculated. Logistic regression analysis was carried out to determine factors associated with recurrent CDI. Results: Among 7,023 CDI cases from 2015-2020, the incidence rate of CDI in 2015 and 2020 was 165.2 and 107.8 per 100,000 persons respectively (median=140.2/100,000 persons; IQR=25.6/100,000 persons). Overall, 12% of 4,301 CDI cases with complete chart reviews had recurrent CDI, which made up 13.6% of all HCFO-CDI, 14.1% of all CO-HCFA CDI, and 10.5% of all CA-CDI. Specifically, 18.1 and 16.9 per 100 persons in 2015 and 2020 respectively had recurrent CDI (median=11.3/100 persons; IQR=4.7/100 persons). There were a 37.3% and 2.3% increase in recurrent CDI among HCFO and CA cases respectively from 2019 to 2020. A significant proportion of those who had recurrent CDI were older (median age=70.0 years, IQR=23.0 years; median age of non-recurrent group=64.0 years, IQR=26.0 years, p<0.001), female (recurrent of 66.0% vs non-recurrent of 61.3% p<0.039), White race, non-Hispanic, and had healthcare-associated incident CDI. In the final multivariable model, there was a higher risk of recurrent CDI among individuals who had malignancies (OR, 1.51; 95% CI, 1.11-2.07), used nitrofurantoin (OR, 2.37; 95% CI, 1.23-4.58), or were of White race. Also, cases with incident CDI in 2017 (OR, 0.43; 95% CI, 0.26-0.73), 2018 (OR, 0.60; 95% CI, 0.37-0.97), and 2019 (OR, 0.50; 95% CI, 0.30-0.84) had lower risk of recurrent CDI when compared with incident CDI cases in 2015. Conclusions: There was a lowered risk of recurrent CDI over time (from 2015-2019) which may reflect effective measures in management of CDI. The loss of this pattern in 2020 with an increase in HCFO recurrent cases may reflect the impact of the COVID-19 pandemic in 2020. Older persons, White individuals, and those with malignancies are particularly vulnerable to recurrent CDI.
Coupled ice/ocean interactions during the future retreat of West Antarctic ice streams

10 The Amundsen Sea sector has some of the fastest-thinning ice shelves in Antarctica, caused by high, ocean-driven basal melt rates, which can lead to increased ice stream flow, causing increased sea level rise (SLR) contributions. In this study, we present the results of a new synchronously coupled ice-sheet/ocean model of the Amundsen Sea sector. We use the WAVI ice sheet model to solve for ice velocities and the MITgcm to solve for ice thickness and three-dimensional ocean properties, allowing for full mass conservation in the coupled ice/ocean system. The coupled model is initialised in the present 15 day and run forward under idealised warm and cold ocean conditions. We find that Thwaites Glacier dominates the future SLR from the Amundsen Sea sector, with a SLR that is approximately quadratic in time. The future evolution of Thwaites Glacier depends on the life-span of small pinning points that form during the retreat. The rate of melting around these pinning points provides the link between future ocean conditions and the SLR from this sector and will be difficult to capture without a coupled ice/ocean model. Grounding-line retreat leads to a progressively larger Thwaites ice-shelf cavity, leading to a positive 20 trend in total melting, resulting from the increased ice basal surface area. Despite these important sensitivities, Thwaites Glacier retreats even in a scenario with zero ocean-driven melting. This demonstrates that a tipping point may have been passed and some SLR from this sector is now committed.
Computing discrete logarithms in F p 6

The security of torus-based and pairing-based cryptography relies on the diﬃculty of computing discrete logarithms in small degree extensions of ﬁnite ﬁelds of large characteristic. It has already been shown that for degrees 2 and 3, the discrete logarithm problem is not as hard as once thought. We address the question of degree 6 and aim at providing real-life timings for such problems. We report on a record DL computation in a 132-bit subgroup of F p 6 for a 22-decimal digit prime, with p 6 having 422 bits. The previous record was for a 79-bit subgroup in a 240-bit ﬁeld. We used NFS-DL with a sieving phase over degree 2 polynomials, instead of the more classical degree 1 case. We show how to improve many parts of the NFS-DL algorithm to reach this target.
Long-term fertilization increases soil but not plant or microbial N in a Chihuahuan Desert Grassland

Although the negative consequences of increased nitrogen (N) supply on plant communities and soil chemistry are well known, most studies have focused on mesic grasslands, and the fate of added N in arid and semi-arid ecosystems remains unclear. To study the impacts of long-term increased N deposition on ecosystem N-pools, we sampled a 26-year-long 10 fertilization (10 g N m -2 yr -1 ) experiment in the northern Chihuahuan Desert at the Sevilleta National Wildlife Refuge (SNWR) in New Mexico. To determine the fate of the added N, we measured multiple soil, microbial, and plant N pools in shallow soils at three time points across the 2020 growing season. We found small but significant increases with fertilization in soil available (NO 3- -N and NH 4+ -N), yet the soil microbial and plant communities do not appear to be taking advantage of the increased N-availability, with no changes in biomass or N-content in either community. However, there were increases in total soil N with 15 fertilization, suggesting increases in microbial or plant N earlier in the experiment. Ultimately, the majority of the N added in this multi-decadal experiment was not found in the shallow soil, nor the microbial or plant community, and is likely to have been lost from the ecosystem entirely.
Fashion Faux Pas: Implicit Stylistic Fingerprints for Bypassing Browsers' Anti-Fingerprinting Defenses

Browser fingerprinting remains a topic of particular interest for both the research community and the browser ecosystem, and various anti-fingerprinting countermeasures have been proposed by prior work or deployed by browsers. While preventing fingerprinting presents a challenging task, modern fingerprinting techniques heavily rely on JavaScript APIs, which creates a choke point that can be targeted by countermeasures. In this paper, we explore how browser fingerprints can be generated without using any JavaScript APIs. To that end we develop StylisticFP, a novel fingerprinting system that relies exclusively on CSS features and implicitly infers system characteristics, including advanced fingerprinting attributes like the list of supported fonts, through carefully constructed and arranged HTML elements. We empirically demonstrate our system's effectiveness against privacy-focused browsers (e.g., Safari, Firefox, Brave, Tor) and popular privacy-preserving extensions. We also conduct a pilot study in a research organization and find that our system is comparable to a state-of-the-art JavaScript-based fingerprinting library at distinguishing devices, while outperforming it against browsers with anti-fingerprinting defenses. Our work highlights an additional dimension of the significant challenge posed by browser fingerprinting, and reaffirms the need for more robust detection systems and countermeasures.
The Macroeconomics of Labor, Credit, and Financial Market Imperfections ∗

Corporate loans are one of the most important avenues of credit for firms. Whereas banks keep a fraction of these loans on their books, about half are sold on a secondary over-the-counter loan market. Empirically, the size of this market is substantial and spreads therein are tightly correlated with real macroeconomic outcomes. We develop a general equilibrium, search-theoretic model with labor, credit, and financial secondary loan markets to study their linkages and the macroeconomic impacts of imperfections in these markets. We show analytically that the existence of a loan market dampens the volatility of unemployment and reduces its steady state level, whereas introducing a loan monitoring cost for banks raises steady state unemployment. Furthermore, convex monitoring costs act as an automatic stabilizer. Numerically, we find that the existence of a loan market reduces steady state unemployment by 2 . 7pp and amplifies the propagation of real and credit shocks in the economy. Financial shocks in the loan market can have sizable effect on real variables.
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.5.6-rc.1)

During the last decades, the impact of multiphase chemistry on secondary organic aerosol (SOA) has been demonstrated to be key in explaining lab experiments and field measurements. However, global atmospheric models still show large biases when simulating atmospheric observations of organic aerosols (OA). Major reasons for the model errors are the use of simplified chemistry schemes of gas-phase oxidation of vapors and parameterization of heterogeneous surface reactions. The photochemical oxidation of anthropogenic and biogenic volatile organic compounds (VOC) leads to products that either 5 produce new SOA or are taken up by existing aqueous media like cloud droplets and deliquescent aerosols. After partitioning, aqueous-phase processing results in polyols, organosulfates, and other products with a high molar mass and oxygen content. In this work, we have introduced the formation of new low-volatility organic compounds (LVOC) into the multiphase chemistry box model CAABA/MECCA. Most notable is the addition of the SOA precursors limonene, long-chain alkanes (up to 8 C atoms), and a semi-explicit chemical mechanism for the formation of LVOC from isoprene oxidation in the gas- and 10 aqueous-phase. Moreover, Henry’s law solubility constants and their temperature dependences have been estimated for the partitioning of organic molecules to the aqueous phase. Box model simulations indicate that the new chemical scheme predicts enhanced formation of LVOC, which are accounted for being precursor species to SOA. As expected, the model predicts that LVOC is positively correlated to temperature but negatively correlated to NO x levels. However, the aqueous-phase processing of isoprene-epoxydiols (IEPOX) displays a more complex dependence on these two key variables. Semi-quantitative 15 comparison with observations from the SOAS campaign suggests that the model may overestimate methylbutane-1,2,3,4-tetrol (MeBuTETROL) from IEPOX. The extensions in CAABA/MECCA will be ported to the 3D-atmospheric model MESSy for a comprehensive evaluation of the impact of aqueous-phase chemistry on SOA at a global scale
IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water

Abstract. We present developments to the physical model and the open-source numerical code IMEX_SfloW2D (de' Michieli Vitturi et al., 2019). These developments consist of a generalization of the depth-averaged (shallow-water) fluid equations to describe a polydisperse fluid–solid mixture, including terms for sedimentation and entrainment, transport equations for solid particles of different sizes, transport equations for different components of the carrier phase, and an equation for temperature/energy. Of relevance for the simulation of volcanic mass flows, vaporization and entrainment of water are implemented in the new model. The model can be easily adapted to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). The numerical algorithm and the code have been improved to allow for simulation of sub- to supercritical regimes and to simplify the setting of initial and boundary conditions. The code is open-source. The results of synthetic numerical benchmarks demonstrate the robustness of the numerical code in simulating transcritical flows interacting with the topography. Moreover, they highlight the importance of simulating transient in comparison to steady-state flows and flows in 2D versus 1D. Finally, we demonstrate the model capabilities to simulate a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles, through application to Krakatau volcano, showing the relevance, at a large scale, of non-linear fluid dynamic features, such as hydraulic jumps and von Kármán vortices, to flow conditions such as velocity and runout.
Neuronal networks in the brain

Recent advances in neuroscience are making it possible to describe the architecture and properties of some of the networks of neurones (brain cells) in brain structures, while neuronal network theory, including approaches related to the statistical mechanics of spin glasses, is becoming helpful in analysing the computational properties of these networks. These developments are illuminating processes of information storage in the brain, and this is illustrated in the case of one brain structure considered here, the hippocampus.
Non-Volatility Property and Pinched Hysteresis Loops of 2-terminal Devices and Memristors

It is well known that memristors can be classified into the four classes according to the complexity of their mathematical representation. Furthermore, the four classes of memristors are used to qualitatively simulate many of the experimentally measured pinched hysteresis loops. In this paper, we define the 2-terminal devices, which do not belong to the above four classes of memristors, but have the same non-volatile property as the ideal memristor. We then study the non-volatile mechanism of these devices and the memristors that can retain the previous value of the state even when the driving signal is set to zero. We show that the ideal generic memristors and the generalized 2-terminal devices can have interesting applications: non-volatile multi-valued memories and two-element chaotic oscillators, if we remove the condition that no state change occurs after the zero driving signal. We also show that the 2-terminal devices and the four classes of memristors can exhibit a wide variety of pinched hysteresis loops similar to those measured experimentally. Furthermore, we show that a wide variety of Lissajous curves are possible, depending on whether the direction of the Lissajous curve is clockwise or counterclockwise and which quadrants the Lissajous curve passes through.
Quasi-Optimal Control for Path Constrained Relative Spacecraft Maneuvers Based on Dynamic Programming

Autonomous close flight and docking of a chaser spacecraft to a target are still challenging problems. In this paper the Hill Clohessy-Wiltshire equations are taken as dynamic model and inverted, after a variable change, in order to be used by a control algorithm to drive the chaser spacecraft along a specified path. The path parameterization is performed by rising cubic B-splines and by having the curvilinear abscissa as parameter. The proposed optimization algorithm uses dynamic programming to find quasi-optimal controls. The number of optimization parameters is drastically reduced by working only on the acceleration component along the vehicle trajectory. The shape of the path can be chosen according to the specific maneuver requirements. In particular, the optimization algorithm is split into a trajectory planner which generates the best tangential acceleration sequence through backward exploration of a tree of possible policies, and a control generator which inverts the parameterized dynamics in order to get the thrusters commands sequence. The optimization algorithm has been coded in Simulink as a library of embedded functions and has been experimentally proved to run in real time.
A framework for time-dependent ice sheet uncertainty quantification, applied to three West Antarctic ice streams

Abstract. Ice sheet models are the main tool to generate forecasts of ice sheet mass loss, a significant contributor to sea level rise; thus, knowing the likelihood of such projections is of critical societal importance. However, to capture the complete range of possible projections of mass loss, ice sheet models need efficient methods to quantify the forecast uncertainty. Uncertainties originate from the model structure, from the climate and ocean forcing used to run the model, and from model calibration. Here we quantify the latter, applying an error propagation framework to a realistic setting in West Antarctica. As in many other ice sheet modelling studies we use a control method to calibrate grid-scale flow parameters (parameters describing the basal drag and ice stiffness) with remotely sensed observations. Yet our framework augments the control method with a Hessian-based Bayesian approach that estimates the posterior covariance of the inverted parameters. This enables us to quantify the impact of the calibration uncertainty on forecasts of sea level rise contribution or volume above flotation (VAF) due to the choice of different regularization strengths (prior strengths), sliding laws, and velocity inputs. We find that by choosing different satellite ice velocity products our model leads to different estimates of VAF after 40 years. We use this difference in model output to quantify the variance that projections of VAF are expected to have after 40 years and identify prior strengths that can reproduce that variability. We demonstrate that if we use prior strengths suggested by L-curve analysis, as is typically done in ice sheet calibration studies, our uncertainty quantification is not able to reproduce that same variability. The regularization suggested by the L curves is too strong, and thus propagating the observational error through to VAF uncertainties under this choice of prior leads to errors that are smaller than those suggested by our two-member “sample” of observed velocity fields.
The challenge of comparing pollen-based quantitative vegetation reconstructions with outputs from vegetation models – a European perspective

Abstract. We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene.
OH, HO2, and RO2 radical chemistry in a rural forest environment: measurements, model comparisons, and evidence of a missing radical sink

Abstract. The hydroxyl (OH), hydroperoxy (HO2), and organic peroxy (RO2) radicals play important roles in atmospheric chemistry. In the presence of nitrogen oxides (NOx), reactions between OH and volatile organic compounds (VOCs) can initiate a radical propagation cycle that leads to the production of ozone and secondary organic aerosols. Previous measurements of these radicals under low-NOx conditions in forested environments characterized by emissions of biogenic VOCs, including isoprene and monoterpenes, have shown discrepancies with modeled concentrations. During the summer of 2016, OH, HO2, and RO2 radical concentrations were measured as part of the Program for Research on Oxidants: Photochemistry, Emissions, and Transport – Atmospheric Measurements of Oxidants in Summer (PROPHET-AMOS) campaign in a midlatitude deciduous broadleaf forest. Measurements of OH and HO2 were made by laser-induced fluorescence–fluorescence assay by gas expansion (LIF-FAGE) techniques, and total peroxy radical (XO2) mixing ratios were measured by the Ethane CHemical AMPlifier (ECHAMP) instrument. Supporting measurements of photolysis frequencies, VOCs, NOx, O3, and meteorological data were used to constrain a zero-dimensional box model utilizing either the Regional Atmospheric Chemical Mechanism (RACM2) or the Master Chemical Mechanism (MCM). Model simulations tested the influence of HOx regeneration reactions within the isoprene oxidation scheme from the Leuven Isoprene Mechanism (LIM1). On average, the LIM1 models overestimated daytime maximum measurements by approximately 40 % for OH, 65 % for HO2, and more than a factor of 2 for XO2. Modeled XO2 mixing ratios were also significantly higher than measured at night. Addition of RO2 + RO2 accretion reactions for terpene-derived RO2 radicals to the model can partially explain the discrepancy between measurements and modeled peroxy radical concentrations at night but cannot explain the daytime discrepancies when OH reactivity is dominated by isoprene. The models also overestimated measured concentrations of isoprene-derived hydroxyhydroperoxides (ISOPOOH) by a factor of 10 during the daytime, consistent with the model overestimation of peroxy radical concentrations. Constraining the model to the measured concentration of peroxy radicals improves the agreement with the measured ISOPOOH concentrations, suggesting that the measured radical concentrations are more consistent with the measured ISOPOOH concentrations. These results suggest that the models may be missing an important daytime radical sink and could be overestimating the rate of ozone and secondary product formation in this forest.