Sharp Discontinuities Research Articles

Microplastic abundance in the surface water of tropical estuarine fronts.

Estuarine fronts are formed due to sharp density discontinuities resulting from the convergence of different water masses. This study, conducted in May and August of 2022 during the southwest monsoon season, focuses on assessing the role of estuarine fronts at Kuala Terengganu estuary in the accumulation of microplastics in surface seawater. The Terengganu River basin area covers approximately 4600 km2 and consists of two main tributaries that drain into the Kuala Terengganu estuary. Microplastic samples were collected from three areas, the plume, front, and shelf, utilizing two methods: manta net (> 350µm) and bucket-water sampling (> 20µm). Results indicate that the estuarine front consistently exhibited higher microplastic concentrations than the plume and shelf regions throughout the study period, with bucket-water sampling contributing significantly to the abundance. Specifically, peak concentrations occurred during the ebb tide at the frontal region in both months, reaching 5761.703 particles m-3 and 12,687.437 particles m-3, respectively. The microplastics, predominantly transparent fibers smaller than 1000µm, mostly showed signs of oxidative and mechanical weathering through SEM-EDS analysis, providing insights into their fate in estuarine surface waters. FTIR spectroscopy revealed polypropylene, polyethylene, and polyamide as the dominant polymers. These findings establish a baseline for microplastic abundance at the estuarine front of the Kuala Terengganu estuary and may inform future strategies for mitigating and recovering microplastic contamination in aquatic environments.

The Carrot and the Stick: Bank Bailouts and the Disciplining Role of Board Appointments

We empirically examine the Capital Purchase Program (CPP) used by the US government to bail out distressed banks and its implications for regulatory policy. We find strong evidence that a feature of the CPP—the government’s ability to appoint independent directors on the board of an assisted bank that missed six dividend payments to the Treasury—had a significant effect on bank behavior. Banks were averse to these appointments—the empirical distribution of missed payments exhibits a sharp discontinuity at five. Director appointments by the Treasury were associated with improved bank performance and lower CEO pay. (JEL G21, G28, G32, G34, G35, G38, H81)

Applying Fractal Theory: Solving the Geometric Challenge of Price Change and Scaling in Economics

<i>Background</i>: Price changes in economics present significant geometric challenges due to sharp discontinuities, which cannot be efficiently described by continuous processes like Brownian motion. Traditional models often rely on linear assumptions, yet financial data frequently exhibit irregular, complex patterns. Fractal theory, a mathematical framework, offers a more accurate way to describe these fluctuations by revealing the underlying self-similar structures in price changes and scaling phenomena. This study explores the use of fractal geometry to gain deeper insights into market behavior. <i>Objective</i>: The objective is to demonstrate that an alternative model, constructed based on geometric scaling assumptions, offers a more accurate description of price changes in competitive markets. <i>Method</i>: The study combined the scaling principle from fractal geometry with a stable Levy model to formulate an integrated model. The logarithmic transformation of the model was applied over successive price changes to observe the behavior of market prices. <i>Result</i>: The scaling principle asserts that no specific time interval (such as a day or a week) holds inherent significance in competitive markets. Instead, these time features are compensated or arbitrated away, supporting the idea that market behavior is self-similar across different time scales. <i>Conclusion</i>: The scaling principle provides a more reliable framework for modeling price changes and is recommended for consideration in economic analyses.

Plasmonic devices - equivalent circuit representations.

An equivalent circuit model for plasmonic slot waveguide-based devices is presented. Taking advantage of the high mode confinement provided by this waveguide geometry, we express plasmonic waveguide geometries using transmission line parameters and express T-junctions using lumped equivalent circuit elements. By combining these fundamental building blocks, we subsequently introduce equivalent circuit models for stub filters and branch-line couplers. We show that plasmonic circuits, if designed with sharp discontinuities, feature low losses that are comparable to losses from RF circuits and even the corresponding photonic circuits. The framework presented here gives insight into the design of novel microwave-inspired plasmonic devices and circuits and significantly speeds up the design time, as a large part of the geometry optimization can be performed in the equivalent circuit domain. For instance, we use this framework in a follow-up paper to design ultra-compact plasmonic hybrids, such as those needed for coherent detection.

Estimation of ground vibration emission increase with respect to velocity in high-speed railways

During the design of a new line, it is often necessary to estimate railway vibration emissions at a given future speed from experimental data in similar circumstances, but at a different speed. Future levels are usually estimated according to a logarithmic evolution law with respect to speed, a typical one being that in USA FTA Report nº0123 "Transit Noise and Vibration Impact Assessment Manual", a de facto standard in the sector. Also, it is known that for high-speed lines a drastic increase in vibrations is observed when railway speed is higher than the propagation speed of surface Rayleigh waves. This phenomenon, known as trans-Rayleigh boom, produces a sharp discontinuity in the evolution of vibration emissions. However, vibration levels observed in the vicinity of a high-speed line have shown values well above the prediction rule suggested in FTA Manual, which could not be explained by a trans-Rayleigh boom. A more accurate extrapolation method based on local rail roughness measurements is capable of producing improved predictions compared to FTA rule of thumb. This contribution shows the details of the method suggested, and the improvement in the prediction (with respect to FTA extrapolation law) obtained in the specific case of a high-speed railway.

Sub‐Pixel Displacement Estimation With Deep Learning: Application to Optical Satellite Images Containing Sharp Displacements

AbstractOptical image correlation is a powerful method for remotely constraining ground movement from optical satellite imagery related to natural disasters (e.g., earthquakes, volcanoes, landslides). This approach enables the characterization, and identification of the causal factors and mechanisms underlying such processes. By employing sub‐pixel correlation algorithms, one can obtain highly accurate (m‐to‐cm level) displacement fields at high spatial resolution (dm‐to‐cm) by comparing satellite images acquired before and after a period of movement. However, this method generally assumes a homogeneous translation of all pixels within a given correlation window, which will lead to biased estimates of ground displacement if the real case is not well represented by such a simplification, especially when resolving ground displacements next to sharp gradients in displacement, such as those found in the near‐field of earthquake surface ruptures. In this paper, we present an innovative deep learning method estimating sub‐pixel displacement maps from optical satellite images for the retrieval of ground displacement. From the generation of a realistic simulated database, comprising Landsat‐8 satellite image pairs containing simulated sub‐pixel shifts and sharp discontinuities, we develop a Convolutional Neural Network able to retrieve sub‐pixel displacements. The comparison to state‐of‐the‐art correlation methods shows that our pipeline significantly reduces by 32% the estimation bias around fault ruptures, leading to more accurate characterization of the near‐field strain in surface rupturing earthquakes. Application of our model to the 2019 Ridgecrest earthquake demonstrates the ability of our model to accurately and quickly resolve ground displacement using real satellite images. Code is made available at https://gricad‐gitlab.univ‐grenoble‐alpes.fr/montagtr/cnn4l‐discontinuities.

Assessing compliance with national guidelines in diabetes care: A study leveraging data from south Africa's National Health Laboratory Service (NHLS).

Diabetes is a major global health issue. We evaluated compliance to laboratory-based management guidelines for diabetes (type 1 and 2), essential for effective treatment and reducing diabetes-related morbidity and mortality. Our study utilized South Africa's National Health Laboratory Services (NHLS) data, focusing on patients from birth to age 80 years who underwent initial diabetes laboratory testing between January 1, 2012-January 1, 2016. Patients were categorized into type 1 (<30 years) or type 2 (≥30-80 years) diabetes based on age at first diabetes test. National diabetes guidelines recommend blood glucose to be checked every three-six months post laboratory-diagnosis. We employed a sharp regression discontinuity design to estimate the effect of a laboratory-diagnosis of diabetes on the likelihood of having a follow-up laboratory test 24 months post-diagnosis. Among patients with type 2 diabetes, the probability of a diabetes follow-up laboratory test within 24 months was 52.4% for patients presenting above the diabetes diagnosis threshold vs 31.1% for those presenting below. Although the likelihood of repeat testing rose with higher HbA1c and glucose levels, at the diagnostic threshold there was no clinically meaningful difference (risk difference: -2.2%, 95% CI: -3.3%, -1.2%). These results were consistent among patients with type 1 diabetes, those living with and without HIV, and healthcare setting. In a national laboratory cohort, diabetes laboratory-diagnosis did not lead to increased monitoring as recommended in national guidelines. Strategies to improve patient education, healthcare provider communication, and healthcare system support are essential to enhance guideline compliance and overall diabetes management.

Platform-Provided Disclosure on Investor Base and Entrepreneurial Success: Evidence from Crowdfunding

ABSTRACT We employ a sharp regression discontinuity design to identify the causal effects of investor-base disclosure (IB DISCLOSE) on funding outcomes and entrepreneurship success. Since February 2016, Kickstarter has disclosed IB information, namely, backer statistics including geographic locations and previous funding experience of the backers, once the number of backers for a project reaches ten. Exploiting this discontinuity, we show the disclosure increases the likelihood of funding success by 10 percent and the amount of funds pledged by 13 percent. The effect is more pronounced when the project quality is high and for projects with less credible creators, high ex ante uncertainty, high information asymmetry between creators and backers, and high financial costs to backers. We also find IB DISCLOSE increases the likelihood of product delivery. Our study highlights the importance of platform-provided disclosure in improving the efficiency of capital allocation. JEL Classifications: M41; G24; L15; O31; D04.

Genomic data reveal a north-south split and introgression history of blood fluke (Schistosoma haematobium) populations from across Africa.

The human parasitic fluke, Schistosoma haematobium hybridizes with the livestock parasite S. bovis in the laboratory, but the extent of hybridization in nature is unclear. We analyzed 34.6 million single nucleotide variants in 162 samples from 18 African countries, revealing a sharp genetic discontinuity between northern and southern S. haematobium. We found no evidence for recent hybridization. Instead the data reveal admixture events that occurred 257-879 generations ago in northern S. haematobium populations. Fifteen introgressed S. bovis genes are approaching fixation in northern S. haematobium with four genes potentially driving adaptation. We identified 19 regions that were resistant to introgression; these were enriched on the sex chromosomes. These results (i) demonstrate strong barriers to gene flow between these species, (ii) indicate that hybridization may be less common than currently envisaged, but (iii) reveal profound genomic consequences of interspecific hybridization between schistosomes of medical and veterinary importance.

Party identity and social-distancing behaviours in Brazil

ABSTRACT Does political affiliation of local politicians determine citizens’ compliance to social distancing behaviours? I provide causal estimates of the effect of political identity of municipal mayors on regional differences in engaging in COVID preventive behaviours in the context of Brazil. I employ a sharp regression discontinuity design based on close mayoral elections in 2016 to examine the effects of having a mayor from one of three political parties that President Jair Bolsonaro is closely associated with, by combining Facebook mobility data that tracks regional movement relative to February 2020 levels with electoral data from the 2016 mayoral municipal elections. The methodology compares municipalities that are similar along a wide array of predetermined and observable correlates of the spread of coronavirus, and where the incumbent mayor was selected as-if randomly. I find that residents of Bolsonaro-affiliated municipalities exhibit 60% smaller relative declines in regional movement and are 13% more likely to cross regional boundaries over the months of March, April, and May in 2020. The findings hold for each of the three political parties, for each of the three months since the onset of the pandemic, and after controlling for anti-lockdown measures of 15 March 2020 in Brazil.

The effect of transport apertures on relay-imaged, sharp-edged laser profiles in photoinjectors and the impact on electron beam properties

In a photoinjector electron source, the initial transverse electron bunch properties are determined by the spatial properties of the laser beam on the photocathode. Spatial shaping of the laser is commonly achieved by relay imaging an illuminated circular mask onto the photocathode. However, the Gibbs phenomenon shows that recreating the sharp edge and discontinuity of the cut profile at the mask on the cathode is not possible with an optical relay of finite aperture. Furthermore, the practical injection of the laser into the photoinjector results in the beam passing through small or asymmetrically positioned apertures. This work uses wavefront propagation to show how the transport apertures cause ripple structures to appear in the transverse laser profile even when effectively the full laser power is transmitted. The impact of these structures on the propagated electron bunch has also been studied with electron bunches of high and low charge density. With high charge density, the ripples in the initial charge distribution rapidly wash-out through space charge effects. However, for bunches with low charge density, the ripples can persist through the bunch transport. Although statistical properties of the electron bunch in the cases studied are not greatly affected, there is the potential for the distorted electron bunch to negatively impact machine performance. Therefore, these effects should be considered in the design phase of accelerators using photoinjectors.

Physics-aware recurrent convolutional neural networks for modeling multiphase compressible flows

Multiphase compressible flow systems can exhibit unsteady and fast-transient dynamics, marked by sharp gradients and discontinuities, and material boundaries that interact with the evolving flow. The transient nature of the dynamics presents challenges to employing artificial intelligence (AI) and data-driven models for predicting flow behaviors. In this study, we explore the potential of physics-aware recurrent convolutional neural networks (PARC) to model the spatiotemporal dynamics of multiphase flows in the presence of shocks and reaction fronts. PARC is a neural network model that incorporates the generic form of the diffusion–advection–reaction equation in its network architecture, which mimics the process of solving the governing equations of fluid flows. In contrast to physics-informed machine learning approaches such as physics-informed neural networks (PINNs) where models are trained to directly minimize the residual of governing equations, PARC takes a dynamical systems viewpoint and does not seek to minimize potentially nonconvex and nonlinear loss terms. To assess the ability of PARC to accurately learn and simulate the physics of multiphase flows, we train and test PARC on various flow simulation problems, including the Burgers’ equation, fluid flow behind a cylindrical cross-section, and unsteady shock interactions with a particle at varying Mach numbers. We analyze PARC’s performance and examine sources of error in its prediction, in terms of differentiation and integration schemes and different weighting strategies for the model update. Based on our observations, we discuss PARC’s capabilities and limitations in multiphase flow applications and propose future research directions.

Towards accurate binocular vision of satellites: A cascaded multi-scale pyramid network for stereo matching on satellite imagery

Stereo matching of high-resolution satellite stereo images is a fundamental and challenging task in photogrammetry, geoscience, and remote sensing. Some deep learning-based methods have shown great potential in solving this task recently. However, these methods have not attracted much attention as their accuracy is still unsatisfactory, especially in regions with intractable factors (e.g., occlusions, repetitive patterns, low texture, non-texture, and disparity discontinuities). To tackle these challenging factors and improve disparity accuracy, we propose an end-to-end stereo matching network named Cascaded Multi-Scale Pyramid Network (CMSP-Net). Firstly, to fully utilize the multi-level spatial context information and mitigate the ambiguous matching caused by repetitive patterns, low texture, non-texture, and occlusions, a cost volume pyramid is constructed with multi-scale image features. Then, each cost volume in the pyramid is aggregated with an hourglass structure to exploit the multi-scale context in a single cost volume. Secondly, considering that high-resolution cost volumes contain more detailed information but have small receptive fields, while low-resolution ones have large receptive fields but lack details, we design an Attention-Guided Cost Fusion (AGCF) strategy to fuse pyramid cost volumes, which effectively integrates the advantages of multi-scale cost volumes while mitigating the backfiring caused by semantic inconsistency across different scales. Thirdly, a disparity refinement module is designed to improve overall disparity accuracy further, which incorporates the reconstruction error and edge clues of input satellite stereo images. Extensive experimental results on multiple satellite datasets demonstrate that the proposed method can effectively reduce matching ambiguities and recover sharp disparity discontinuities, achieving clear superiority over existing state-of-the-art methods.

Legislature size and welfare: Evidence from Brazil

AbstractHow does legislature size impact public service provision? Despite the importance of institutional design for democratic governance, the effect of legislative features on citizen welfare remains little understood. In this article, we use a formal model to show that increasing legislature size improves public goods delivery. We argue that changes in bargaining costs depend on whether additional legislators share the executive's party affiliation: More opposition members reduce the equilibrium public goods provision, while more government‐aligned members increase it. We test this theory by exploiting sharp discontinuities in city‐council size in Brazil. We show that an additional city councilor has a 91% chance of belonging to the mayoral coalition, and this significantly improves primary school enrollment and infant mortality rates. To explore possible mechanisms, we surveyed 174 former city councilors and analyzed 346,553 bills proposed between 2005 and 2008. This article has implications for the design of representative institutions.

The Moral Inefficacy of Carbon Offsetting

ABSTRACT Many real-world agents recognise that they impose harms by choosing to emit carbon, for example, by flying. Yet many do so anyway, and then attempt to make things right by offsetting those harms. Such offsetters typically believe that, by offsetting, they change the deontic status of their behaviour, making an otherwise impermissible action permissible. Do they succeed in practice? Some philosophers have argued that they do, since their offsets appear to reverse the adverse effects of their emissions. But we show that they do not. In practice, standard carbon offsetting does not reverse the harms of the original action, nor does it even benefit the same group as was harmed. Standard moral theories hence deny that such offsetting succeeds. Indeed, we show that any moral theory that allows offsetting in this setting faces a dilemma between allowing any wrong to be offset, no matter how grievous, and recognising an implausibly sharp discontinuity between offsettable actions and non-offsettable actions. The most plausible response is to accept that carbon offsetting fails to right our climate wrongs.

Ultra-sensitive current bistability and light switching in a resonant tunneling superlattice transistor

Bistability in the current–voltage characteristics of semiconductor superlattices and quantum cascade laser structures has the potential for wide-ranging applications, particularly in sensing systems. However, the interdependency of applied bias and current injection in conventional two-terminal structures has led to complications in analysis and rendered the bistability phenomenon difficult to implement in practical applications. Here, we report a new kind of electronic bistability coupled to optical switching in a resonant tunneling bipolar superlattice transistor. This bistability manifests as sharp discontinuities in the collector current with extremely small variations of the applied voltage, which arise from unstable tunneling transmission across the hetero-barrier between the two-dimensional electron gas (2DEG) at the edge of the transistor base and the collector superlattice structure. The electronic transitions between high and low quantum mechanical transmissions are demonstrated to be caused by self-consistent variations of the internal electric field at the heterointerface between the 2DEG and the superlattice. They are also present in the base current of the three-terminal device and result in sharp switching of near-infrared spontaneous light emission output from an interband radiative recombination process with a peak emission wavelength of 1.58 μm. A comprehensive quantum mechanical theoretical model accounting for the self-consistent bistable tunneling transmission is in quantitative agreement with the experimental data. The measured peak transconductance sensitivity value of 6000 mS can be used in the highly sensitive detector and non-linear device applications.

Crack propagation in anisotropic brittle materials: From a phase-field model to a shape optimization approach

The phase-field method is based on the energy minimization principle which is a geometric method for modeling diffusive cracks that are popularly implemented with irreversibility based on Griffith’s criterion. This method requires a length-scale parameter that smooths the sharp discontinuity, which influences the diffuse band and results in mesh-dependent fracture propagation results. Recently, a novel approach based on the optimization on Riemannian shape spaces has been proposed, where the crack path is realized by techniques from shape optimization. This approach requires the shape derivative, which is derived in a continuous sense and used for a gradient-based algorithm to minimize the energy of the system. In this paper, the novel approach based on shape optimization is presented, followed by an assessment of the predicted crack path in both isotropic and anisotropic brittle material using numerical calculations from a phase-field model.

Two shell- and wing-shaped supernova remnants

Supernova remnants (SNRs) are profoundly affected by their ambient medium. In particular, SNRs with a mixed morphology (characterised by a shell-like radio morphology and centrally filled X-ray emission) are thought to be the result of the interaction of a supernova explosion with a dense environment. In this work, we present carbon monoxide (CO) observations around two mixed morphology SNRs, VRO 42.05.01 and G 350.0-2.0, that look remarkably similar in continuum radio emission, showing what we refer to as a shell and wing shape. It has been proposed that the shell and wing shape is the result of environmental effects, in the form of a sharp density gradient or discontinuity. Therefore, our motivation for studying these two sources jointly is that if the dense molecular environment causes the development of these sources’ shell and wing shape, then these two sources’ environments must be similar. This is contrary to what we observe. In the case of VRO 42.05.01, we have found direct evidence of an interaction with its molecular environment, in the form of broadened 12CO line profiles, high 12CO (J = 2−1) to 12CO (J = 1−0) line ratios, and arc features in position-velocity space. We interpret some of these features to be associated with the SNR shock, and some of them to be due to the presence of a pre-supernova stellar wind. We have found no such features in the abundant molecular gas surrounding G 350.02.0. In addition to the spectral line analysis, we have used radio continuum data to make a spectral index map of G 350.0-2.0, and we see that the radio spectrum of G 350.0-2.0 steepens significantly at frequencies &lt;200 MHz, much like that of VRO 42.05.01. In spite of their spectral and morphological similarities, these two sources look substantially different in their observed optical and infrared emission. The lack of large-scale correspondence between the radio continuum and the molecular material, in either case, as well as the differences in the excitation and morphological properties of the molecular gas surrounding both sources, lead us to conclude that the shell and wing morphology of these two sources is not due to interactions with a similar ambient molecular interstellar medium.

Association of the fat mass index with hepatic steatosis and fibrosis: evidence from NHANES 2017–2018

Limited population-based studies discuss the association between fat mass index (FMI) and the risk of liver diseases. This investigation utilized data from the National Health and Nutrition Examination Survey (NHANES) to examine the linkage between the FMI and liver conditions, specifically steatosis and fibrosis. The study leveraged data from NHANES’s 2017–2018 cross-sectional study, employing an oversampling technique to deal with sample imbalance. Hepatic steatosis and fibrosis were identified by vibration-controlled transient elastography. Receiver operating curve was used to assess the relationship of anthropometric indicators, e.g., the FMI, body mass index (BMI), weight-adjusted-waist index (WWI), percentage of body fat (BF%), waist-to-hip ratio (WHR), and appendicular skeletal muscle index (ASMI), with hepatic steatosis and fibrosis. In this study, which included 2260 participants, multivariate logistic regression models, stratified analyses, restricted cubic spline (RCS), and sharp regression discontinuity analyses were utilized. The results indicated that the WHR and the FMI achieved the highest area under the curve for identifying hepatic steatosis and fibrosis, respectively (0.720 and 0.726). Notably, the FMI presented the highest adjusted odds ratio for both hepatic steatosis (6.40 [4.91–8.38], p = 2.34e−42) and fibrosis (6.06 [5.00, 7.37], p = 5.88e−74). Additionally, potential interaction effects were observed between the FMI and variables such as the family income-to-poverty ratio, smoking status, and hypertension, all of which correlated with the presence of liver fibrosis (p for interaction < 0.05). The RCS models further confirmed a significant positive correlation of the FMI with the controlled attenuation parameter and liver stiffness measurements. Overall, the findings underscore the strong link between the FMI and liver conditions, proposing the FMI as a potential straightforward marker for identifying liver diseases.

Assessment of the 2021 AASLD Practice Guidance for Albumin Infusion in Elective Therapeutic Paracentesis: A Regression Discontinuity Design.

The 2021 American Association for the Study of Liver Disease (AASLD) Practice Guidance recommends albumin infusion when removing ≥5 L of ascites to prevent post-paracentesis circulatory dysfunction. However, the optimal criteria and scenarios for initiating albumin infusion subsequent to therapeutic paracentesis (TP) have been subject to limited scientific inquiry. We conducted a retrospective cohort study at a US academic healthcare center. Participants received elective, outpatient TP between July 2019 and December 2022. Patients with spontaneous bacterial peritonitis, post-TP clinical adjustments, and/or hospitalization were excluded. The institution strictly followed the AASLD Guidance. We used a sharp regression discontinuity (RD) design to estimate the effect of albumin infusion at the AASLD Guidance-recommended cutoff of 5 L on serum creatinine and sodium trajectory after TP. Over the study period, 1,457 elective TPs were performed on 235 unique patients. Albumin infusion at the threshold of 5 L of ascites removal reduced serum creatinine levels by 0.046 mg/dL/d (95% confidence interval 0.003-0.116, P = 0.037) and increased serum sodium levels by 0.35 mEq/L/d (95% confidence interval 0.15-0.55, P = 0.001) compared with those who did not receive albumin infusion. The RD plots indicated worsened serum creatine/sodium levels after draining 3 L of fluid, approaching levels similar to or worse than with albumin infusion at 5 L or more. Our RD models supported the 2021 AASLD Guidance with robust estimation of causal effect sizes at the cutoff level of 5 L. Nevertheless, the findings also highlight the need to further evaluate the efficacy of albumin infusion in patients who undergo elective TP and have 3-5 L of ascites removed.