Plausible Set Research Articles

Integrating Multi-Cancer Early Detection (MCED) Tests with Standard Cancer Screening: System Dynamics Model Development and Feasibility Testing.

Cancer screening plays a critical role in early disease detection and improving outcomes. In Australia, established screening protocols for colorectal, breast and cervical cancer have significantly contributed to timely cancer detection. However, the recent introduction of multi-cancer early detection (MCED) tests arguably can disrupt current screening, yet the extent to which these tests provide additional benefits remains uncertain. We present the development and initial validation of a system dynamics (SD) model that estimates the additional cancer detections and costs associated with MCED tests. This article describes the development of a simulation model built to evaluate the additional patient diagnoses and the economic impact of incorporating MCED testing alongside Australia's well-established standard of care (SOC) screening programs for colorectal, breast, cervical and lung cancers. The model was designed to estimate the additional number of patients diagnosed at each cancer stage (stage I, II, III, IV, or unknown) and the associated costs. This simulation model allows for the analysis of multiple scenarios under a plausible set of assumptions regarding population-level participation rates. An SD model was developed to represent the existing SOC national cancer screening pathways and to integrate potential clinical pathways that could be introduced by MCED tests. The SD model was built to investigate three scenarios for the use of MCED testing: firstly, to explore the viability of MCED testing as a substitute among individuals who are not opting for SOC screening for any reason; secondly, to implement MCED testing exclusively for individuals ineligible for SOC screening, yet have high-risk characteristics; and thirdly, to employ MCED testing after SOC screening to serve as a triaging/confirmatory tool for individuals receiving inconclusive test results. The three primary scenarios were constructed by varying diagnostic accuracy and uptake rates of MCED tests. The clinical utility and outcomes of MCED testing for screening and early detection still lack comprehensive evidence. Nonetheless, this simulation model facilitates a thorough analysis of MCED tests within the Australian healthcare context, providing insights into potential additional detections and costs to the healthcare system, which may help prioritise future evidence development. The adaptable yet novel SD model presented herein is anticipated to be of considerable interest to industry, policymakers, consumers and clinicians involved in informing clinical and economic decisions regarding integrating MCED tests as cancer screening and early detection tools. The expected results of applying this SD model will determine whether using MCED testing in conjunction with SOC screening offers any potential benefits, possibly guiding policy decisions and clinical practices towards the adoption of MCED tests.

Are shared automated vehicles good for public- or private-transport-oriented cities (or neither)?

Simulation studies suggest that Shared Automated Vehicles (SAVs) could reduce the total vehicle kilometres travelled (VKT) thanks to efficiently pooling multiple users in one vehicle. However, mode choice studies indicate that SAVs would attract mostly public transport users, leading to an increase in VKT. This paper is among the first to combine these operational and behavioural expectations and the first to do so analytically. In our theoretical set-up, travellers choose between car, public transport, and SAVs, depending on their individual valuation of private travel and other attributes of each mode. We find that the introduction of SAVs lead to a VKT change in public-transport-oriented cities ranging from a small decrease to a large increase, where the latter is true for plausible parameter settings and hence is a cautionary point for SAV-introduction policies. Conversely, SAVs would attract only few travellers in private-transport-oriented cities and therefore would not significantly impact VKT.

Zircon U-Pb-Hf isotopes constraints on the petrogenesis of Neoarchean granitic rocks from the Northeastern part of the Eastern Dharwar Craton, Southern India

In the present study, we integrate bulk rock chemistry and in-situ zircon U-Pb-Hf isotopes of high-K Neoarchean granitoids from the northeastern part of the Eastern Dharwar Craton (EDC) to investigate their source, petrogenesis, and plausible tectonic setting. Based on the mineral assemblage, in coherence with their geochemical characteristics, these granitoids are classified as Hornblende-biotite granite (HBG) with Microgranular enclaves (ME), Biotite granite (BTG) and Monzogranite (MG). Field observations and zircon U-Pb ages reveal coeval emplacement of these granitoids between 2.53 and 2.50 Ga. The HBG, including ME, has low silica, metaluminous affinity, and high ferromagnesian element content, consistent with their derivation from a mafic source. Some of the HBG and ME samples are strongly enriched in incompatible elements, similar to the sanukitoids. The geochemical attributes and strongly evolved zircon Hf isotopic compositions (ɛHf(t) = −4.3 to +1.8 and −7.3 to +0.2) of the HBG and ME suggest their derivation from a mantle source metasomatized by subducted sediments. The BTG and MG are compositionally similar, with high silica, low ferromagnesian element content, and moderate peraluminous affinity, suggesting the involvement of felsic crustal sources. The sub-chondritic to chondritic zircon Hf isotopic compositions (ɛHf(t) = −2.7 to +1.4 and −6.9 to +1.9) of these granitoids support the involvement of heterogeneous ancient crustal sources. While all granitoids exhibit similar zircon Hf isotopic compositions, their geochemical attributes suggest distinct sources. The HBG reflects juvenile crustal additions, whereas BTG and MG are products of the crustal reworking. We propose that these granitoids formed during the continent-continent collision between Western and Eastern Dharwar cratons, that took place after the break-off of the eastward subducting slab. The asthenospheric upwelling induced by slab break-off and/or lithospheric delamination of thickened crust led to the genesis of metasomatized mantle derived magma, which drove the crustal reworking. The observed zircon Hf isotopic composition of the EDC granitoids are similar to the present day Phanerozoic Alpine-Himalayan type orogenies supporting subduction followed by continental collision model for the stabilisation of Archean cratons. Evidence for the existence of Paleo- Mesoarchean felsic crust from this part of the EDC warrants further studies to test the three-terrane model for the Dharwar Craton.

Influences of perfect fluid dark matter on coinciding validity of the weak gravity and weak cosmic censorship conjectures for Kerr-Newman black hole

One of the main difficulties in general relativity is the potential conflict between the weak gravity conjecture (WGC) and weak cosmic censorship conjecture (WCCC). Cosmic censorship is a basic assumption that guarantees the coherence of the gravity theory. However, this paper examines the feasibility of harmonizing the WGC and the WCCC by studying the Kerr Newman black hole surrounded by perfect fluid dark matter (PFDM) in asymptotically flat spacetimes. These two conjectures appear to be unrelated, but a recent idea proposed that they have a surprising connection. Specifically, we present a plausible set of for the WCCC in the four-dimensional framework, considering a Kerr-Newman black hole when WGC is active. We show that by applying certain restrictions on the parameters of the metric, the WGC and the WCCC can be consistent. Moreover, we explore the characteristics of the Kerr Newman black hole in the presence of PFDM for Q>M and display some fascinating figures to verify the accuracy of the WGC and the WCCC at the same time. When PFDM is absent (λ=0), the Kerr Newman black hole has either two event horizons if Q2/M2≤1, or none if Q2/M2>1. The latter case leads to a naked singularity, which violates the WCCC. But when PFDM is present (λ≠0), the Kerr Newman black hole has event horizons depending on Q, a, and M. This means that the singularity is always hidden, and the WGC and the WCCC are satisfied. Furthermore, we prove that there is a critical value of λ, denoted by λext, that becomes the extremality Kerr Newman black hole when λ=λext. In this case, the black hole has an event horizon, and the WGC and the WCCC are still satisfied. We conclude that PFDM can make the WGC and the WCCC compatible for the Kerr Newman black hole and that the WGC and the WCCC concur with each other when PFDM is present.

Generating sets of diverse and plausible scenarios through approximated multivariate normal distributions

This article presents a novel and broadly generalizable framework for generating diverse and plausible sets of scenarios. Potential future outcomes are decomposed using a set of uncertainties which are assumed to be multivariate normally distributed, regardless of whether the uncertainties actually present numerically quantifiable phenomena. The optimal scenarios are then chosen along the principal components of the distribution, and the results can be easily interpreted and visualized. Notably, our approach requires a relatively small number of numerical assessments, offering an efficient and practical solution for decision-makers. The framework also provides a testable setting for evaluating its performance and allows users to iteratively improve future-related assumptions and predictions. These findings are relevant for all fields that aim to understand potential future developments, such as, but not limited to, foresight, economics, business strategy and strategic intelligence analysis.

The origin and function of external representations

External representations ( ERs) are objects or performances in the world whose proper function is to communicate about other things in the world. Why and how did we make them, and what do they give us? We outline a simple framework for thinking about ERs grounded in modern machine learning. We propose a minimal set of neural mechanisms needed for open-ended ER production. Our constructivist enactive view contrasts with nativist views which propose specialist neural modules requiring symbolic internal representations. We propose a plausible set of (biological and cultural) evolutionary steps to full Gricean symbolic communication via a set of increasingly complex enactive algorithms for ER production. A pragmatic space of games is defined, which includes not only fully cooperative language games but also science, art, and evolved signal manipulation games. This space is defined by the complexity of learning needed by sender and receiver. We propose that one important step towards open-ended ER use was selection for bush reading, which like mind-reading is an inferential process requiring complex contextual and syntactic understanding of cues about events displaced in space and time. Bush reading pre-adapted receivers to be receptive, competent, and perspicacious interpreters of later intentionally produced signals about hidden topics such as felt mental states. This paved the way for minimally Gricean communication, which subsequently could be bootstrapped into explicit theories of mind, folk psychology narratives, and symbolic language in general. Recent findings in cognitive archaeology are integrated within the framework, and new experiments in machine learning suggested.

Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations.

Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM.

The "elongate chelicera problem": A virtual approach in an extinct pterygotid sea scorpion from a 3D kinematic point of view.

Chelicerae, distinctive feeding appendages in chelicerates, such as spiders, scorpions, or horseshoe crabs, can be classified based on their orientation relative to the body axis simplified as either orthognathous (parallel) or labidognathous (inclined), exhibiting considerable diversity across various taxa. Among extinct chelicerates, sea scorpions belonging to the Pterygotidae represent the only chelicerates possessing markedly elongated chelicerae relative to body length. Despite various hypotheses regarding the potential ecological functions and feeding movements of these structures, no comprehensive 3D kinematic investigation has been conducted yet to test these ideas. In this study, we generated a comprehensive 3D model of the pterygotid Acutiramus, making the elongated right chelicera movable by equipping it with virtual joint axes for conducting Range of Motion analyses. Due to the absence in the fossil record of a clear indication of the chelicerae orientation and their potential lateral or ventral movements (vertical or horizontal insertion of joint axis 1), we explored the Range of Motion analyses under four distinct kinematic settings with two orientation modes (euthygnathous, klinogathous) analogous to the terminology of the terrestrial relatives. The most plausible kinematic setting involved euthygnathous chelicerae being folded ventrally over a horizontal joint axis. This configuration positioned the chelicera closest to the oral opening. Concerning the maximum excursion angle, our analysis revealed that the chela could open up to 70°, while it could be retracted against the basal element to a maximum of 145°. The maximum excursion in the proximal joint varied between 55° and 120° based on the insertion and orientation. Our findings underscore the utility of applying 3D kinematics to fossilized arthropods for addressing inquiries on functional ecology such as prey capture and handling, enabling insights into their possible behavioral patterns. Pterygotidae likely captured and processed their prey using the chelicerae, subsequently transporting it to the oral opening with the assistance of other prosomal appendages.

Assessing the influence of preconception diet on female fertility: a systematic scoping review of observational studies

Preconception diet is a proposed modifiable risk factor for infertility(1). However, there is no official guidance for women in the preconception period as to which dietary approaches may improve fertility. A comprehensive synthesis of the relevant evidence is key to determine the potentially effective dietary patterns and components as well as evidence gaps, and to provide information for nutritional recommendations for couples planning a pregnancy. In this systematic scoping review, four electronic databases (Medline and EMBASE via Ovid processing, CAB Direct, and CINAHL via EBSCO) were searched for observational studies (prospective and retrospective cohort, cross-sectional, and case–control studies) from inception to 27 September 2021. Eligible studies included women of reproductive age during the preconception period, and evaluated exposures related to preconception diet and outcomes related to fertility. Results were synthesised using a descriptive approach. A total of 36 studies were eligible for inclusion (31 prospective, 3 cross-sectional, and 2 case–control studies) and were published between 2007 and 2022. Of the assessed dietary exposures, increased adherence to the Mediterranean diet displayed the strongest and most consistent association with improved clinical pregnancy rates. Reducing trans fatty acids (TFAs), saturated fatty acids, and discretionary food intake (fast food and sugar-sweetened beverages) were associated with improvements in live birth, clinical pregnancy rates, and related ART outcomes. The dietary components of seafood, dairy, and soy demonstrated inconsistent findings across the few included studies. Due to heterogeneity and the limited available literature on most exposures, there is insufficient evidence to support any specific dietary approach for improving fertility. However, following some of the dietary approaches outlined in this review (anti-inflammatory diets, reducing TFA, and discretionary food intake) are consistent with broad healthy eating guidelines, have little to no associated risk, and offer a plausible set of possible benefits. This warrants further exploration in randomised controlled trials.

Learning Location From Shared Elevation Profiles in Fitness Apps: A Privacy Perspective

The extensive use of smartphones and wearable devices has facilitated many useful applications. For example, with Global Positioning System (GPS)-equipped smart and wearable devices, many applications can gather, process, and share rich metadata, such as geolocation, trajectories, elevation, and time. For example, fitness applications, such as Runkeeper and Strava, utilize the information for activity tracking and have recently witnessed a boom in popularity. Those fitness tracker applications have their own web platforms and allow users to share activities on such platforms or even with other social network platforms. To preserve the privacy of users while allowing sharing, several of those platforms may allow users to disclose partial information, such as the elevation profile for an activity, which supposedly would not leak the location of the users. In this work, and as a cautionary tale, we create a proof of concept where we examine the extent to which elevation profiles can be used to predict the location of users. To tackle this problem, we devise three plausible threat settings under which the city or borough of the targets can be predicted. Those threat settings define the amount of information available to the adversary to launch the prediction attacks. Establishing that simple features of elevation profiles, e.g., spectral features, are insufficient, we devise both natural language processing (NLP)-inspired text-like representation and computer vision-inspired image-like representation of elevation profiles, and we convert the problem at hand into text and image classification problem. We use both traditional machine learning- and deep learning-based techniques and achieve a prediction success rate ranging from 59.59% to 99.80%. The findings are alarming, highlighting that sharing elevation information may have significant location privacy risks.

Economic activity and suicides: Causal evidence from macroeconomic shocks in England and Wales

The relationship between economic activity and suicides has been the subject of much scrutiny, but the focus in the extant literature has been almost exclusively on estimating associations rather than causal effects. In this paper, using data from England and Wales between January 1, 1997 and December 31, 2017, we propose a plausible set of assumptions to estimate the causal impacts of well-known macroeconomic variables on the daily suicide rate. Our identification strategy relies on scheduled macroeconomic announcements and professional economic forecasts. An important advantage of using these variables to model suicide rates is that they can efficiently capture the elements of ‘surprise or shock’ via the observed difference between how the economy actually performed and how it was expected to perform. Provided that professional forecasts are unbiased and efficient, the estimated ‘surprises or shocks’ are ‘as good as random’, and therefore are exogenous. We employ time series regressions and present robust evidence that these exogenous macroeconomic shocks affect the suicide rate. Overall, our results are consistent with economic theory that shocks that reduce estimated permanent income, and therefore expected lifetime utility, can propel suicide rates. Specifically, at the population level, negative shocks to consumer confidence and house prices accelerate the suicide rate. However, there is evidence of behavioural heterogeneity between sexes, states of the economy, and levels of public trust in government. Negative shocks to the retail price index (RPI) raise the suicide rate for males. Negative shocks to the growth rate in gross domestic product (GDP) raise the population suicide rate when the economy is doing poorly. When public trust in government is low, increases in the unemployment rate increase the suicide rate for females.

Magmatism during late Ordovician-early Silurian accretion of the Caledonides of Arctic Scandinavia: the Halti–Guolasjávri area revisited

In the Scandinavian Caledonides, evidence of syn-collisional magmatism related to extensional basin development immediately prior to late Silurian Baltica–Laurentia collision was considered restricted to exotic terranes until late Silurian ages were obtained from the Halti Igneous Complex (HIC), hosted by a thrust sheet (Corrovarre Nappe, CN) of continental affinity. Various orogenic models for the extension and magmatism, a. o. subduction flip, slab roll-back, and ridge subduction have been proposed. Crucial factors include the affinity (Baltican or exotic) of the CN, and the nature of the debated unconformity at the base of the overlying exotic Vaddas Nappe (Köli). This study reexamines a critical tectonostratigraphic section and reports U–Pb zircon ages (441–436 Ma) of palingenetic granitic dykes generated by the HIC. We reinterpret the CN as a slice of the continental margin and accreted with some other nappes of the Seve Nappe Complex (SNC) which decoupled from the continent-ocean transition (COT) at an early stage of subduction of the margin. The lower part of the bipartite Vaddas Nappe, composed of a very dense dolerite dyke swarm with screens of quartzite, marble and subordinate black schist, is reinterpreted as a continuation northwards of the uppermost nappe of the SNC in Indre Troms, derived from the Ediacaran outermost continental margin. The contact with the overlying telescoped succession of conglomerates, marbles, volcanics and turbidites of the Vaddas Nappe is tentatively interpreted as a tectonised unconformity. To a classical model of back-arc spreading outboard of Laurentia during closure of the Iapetus Ocean, we add the arrival of Baltica, with a prism of decoupled slices of the COT and exhumed/exhuming UHP nappes. The spreading centre of the basin provides a plausible setting for gabbros and pillow lavas of the Vaddas Nappe, and the shores of the basin for a Seve–Köli unconformity. Future PTt studies are required in order to be able to relate the proposed shallow, syn-exhumation HIC magmatism to the tectonometamorphic evolution of the HP–UHP nappes of the SNC.

Bayesian optimization approach to quantify the effect of input parameter uncertainty on predictions of numerical physics simulations

An understanding of how input parameter uncertainty in the numerical simulation of physical models leads to simulation output uncertainty is a challenging task. Common methods for quantifying output uncertainty, such as performing a grid or random search over the model input space, are computationally intractable for a large number of input parameters represented by a high-dimensional input space. It is, therefore, generally unclear as to whether a numerical simulation can reproduce a particular outcome (e.g., a set of experimental results) with a plausible set of model input parameters. Here, we present a method for efficiently searching the input space using Bayesian optimization to minimize the difference between the simulation output and a set of experimental results. Our method allows explicit evaluation of the probability that the simulation can reproduce the measured experimental results in the region of input space defined by the uncertainty in each input parameter. We apply this method to the simulation of charge-carrier dynamics in the perovskite semiconductor methyl-ammonium lead iodide (MAPbI3), which has attracted attention as a light harvesting material in solar cells. From our analysis, we conclude that the formation of large polarons, quasiparticles created by the coupling of excess electrons or holes with ionic vibrations, cannot explain the experimentally observed temperature dependence of electron mobility.

Move up or move over: mapping opportunities for climate adaptation in Pakistan’s Indus plains

The 2022 Indus floods in Pakistan underscore the urgency of adapting to more frequent and severe natural disasters in a warming world. Post-disaster reconstruction offers a chance to built-in adaptation measures, but identifying feasible and cost-effective adaptation options is challenging, especially in data-scarce regions. Here we employ a high-resolution rapid assessment of flood stages combined with demographic data to identify adaptation opportunities and costs for the Indus floodplains. Under a plausible set of assumptions, we find that rebuilding houses in a flood-proof, elevated manner (‘moving up’) or (temporary) relocation (‘moving over’) could have protected 13%, respectively 16% of people affected during the 2022 floods, while the remaining 70% of people were exposed to shallow water levels that could have been addressed with low-cost adaptation. Implementing these measures during ongoing reconstruction could be an effective adaptation to future floods but will come with substantial costs. Rebuilding in a flood-proofed manner (‘moving up’) alone would already increase costs by 26%–63% ($1.5bn–$3.6bn) compared to estimated reconstruction costs without adaptation ($5.8bn). Additional costs would be incurred by relocation and adaptation of other infrastructure. The absence of local flood stage and socio-economic data creates uncertainty and points to future research avenues. Yet, our prototype approach demonstrates the value of rapid assessments for guiding post-disaster adaptation of livelihoods to future floods.

Benchmarking Standard and Micromechanical Models for Creep and Shrinkage of Concrete Relevant for Nuclear Power Plants.

The creep and shrinkage of concrete play important roles for many nuclear power plant (NPP) and engineering structures. This paper benchmarks the standard and micromechanical models using a revamped and appended Northwestern University database of laboratory creep and shrinkage data with 4663 data sets. The benchmarking takes into account relevant concretes and conditions for NPPs using 781 plausible data sets and 1417 problematic data sets, which cover together 47% of the experimental data sets in the database. The B3, B4, and EC2 models were compared using the coefficient of variation of error (CoV) adjusted for the same significance for short-term and long-term measurements. The B4 model shows the lowest variations for autogenous shrinkage and basic and total creep, while the EC2 model performs slightly better for drying and total shrinkage. In addition, confidence levels at 5, 10, 90, and 95% are quantified in every decade. Two micromechanical models, Vi(CA)2T and SCK CEN, use continuum micromechanics for the mean field homogenization and thermodynamics of the water-pore structure interaction. Validations are carried out for the 28-day Young's modulus of concrete, basic creep compliance, and drying shrinkage of paste and concrete. The Vi(CA)2T model is the second best model for the 28-day Young's modulus and the basic creep problematic data sets. The SCK CEN micromechanical model provides good prediction for drying shrinkage.

Bimodal unsaturated hydraulic conductivity derived from water retention parameters by accounting for clay-water interactions: Deriving a plausible set of hydraulic parameters

We developed a novel, lognormal, pore-scale, unsaturated hydraulic conductivity model, K(ψ)Model, which does not require saturated hydraulic conductivity, Ks, as an input parameter. K(ψ)Model is derived solely from hydraulic parameters describing a bimodal, lognormal, pore-scale, soil water retention curve θ(ψ).The K(ψ)Model is based on the Hagen-Poiseuille equation, which represents the soil as a bundle of parallel, non-intersecting capillary tubes. To improve the modelling of fine-textured soils we introduced a novel model to consider the clay-water interaction. This model assumes that clay-water interaction occurs for soils having more than 30% of clay and an effective matrix porosity greater than 35%.Compared to previously developed models, the K(ψ)Model does not require the use of integrals and can be computed from a spreadsheet and distinguishes between macropore (non-equilibrium) and matrix (equilibrium) flows.The K(ψ)Model gives improved results when the hydraulic parameters are dynamically constrained and when θ(ψ) describes a bimodal, lognormal distribution.

Monte Carlo samplers for efficient network inference.

Accessing information on an underlying network driving a biological process often involves interrupting the process and collecting snapshot data. When snapshot data are stochastic, the data's structure necessitates a probabilistic description to infer underlying reaction networks. As an example, we may imagine wanting to learn gene state networks from the type of data collected in single molecule RNA fluorescence in situ hybridization (RNA-FISH). In the networks we consider, nodes represent network states, and edges represent biochemical reaction rates linking states. Simultaneously estimating the number of nodes and constituent parameters from snapshot data remains a challenging task in part on account of data uncertainty and timescale separations between kinetic parameters mediating the network. While parametric Bayesian methods learn parameters given a network structure (with known node numbers) with rigorously propagated measurement uncertainty, learning the number of nodes and parameters with potentially large timescale separations remain open questions. Here, we propose a Bayesian nonparametric framework and describe a hybrid Bayesian Markov Chain Monte Carlo (MCMC) sampler directly addressing these challenges. In particular, in our hybrid method, Hamiltonian Monte Carlo (HMC) leverages local posterior geometries in inference to explore the parameter space; Adaptive Metropolis Hastings (AMH) learns correlations between plausible parameter sets to efficiently propose probable models; and Parallel Tempering takes into account multiple models simultaneously with tempered information content to augment sampling efficiency. We apply our method to synthetic data mimicking single molecule RNA-FISH, a popular snapshot method in probing transcriptional networks to illustrate the identified challenges inherent to learning dynamical models from these snapshots and how our method addresses them.

Do Financial Analysts Herd?

ABSTRACT Financial analysts may have strategic incentives to herd or to anti-herd when issuing forecasts of firms' earnings. This paper develops and implements a new test to examine whether such incentives exist and to identify the form of strategic behaviour. We use the equilibrium property of the finite-player forecasting game of Kim and Shim [2019. “Forecast Dispersion in Finite-Player Forecasting Games.” The B.E. Journal of Theoretical Economics 19 (1).] that forecast dispersion decreases (resp. increases) as the number of forecasters increases if and only if there is strategic complementarity (resp. substitutability) in their forecasts. Using the I/B/E/S database, we find strong evidence that supports strategic herding incentive of financial analysts through a plausible natural experiment setting of brokerage house mergers. We show further that this finding is robust to different forecast horizons and is more pronounced for firms with low initial coverage.

Inevitable manifestation of wiggles in the expansion of the late Universe

Using the fact that the comoving angular diameter distance to the last scattering surface is strictly constrained almost model independently, we show that, for any model agreeing with the standard $\mathrm{\ensuremath{\Lambda}}$CDM model on its background dynamics at $z\ensuremath{\sim}0$ and size of the comoving sound horizon at last scattering, the deviations of the Hubble radius from the one of the standard $\mathrm{\ensuremath{\Lambda}}$CDM model must be a member of the set of admissible wavelets. The family of models characterized by this framework also offers nontrivial oscillatory behaviors in various functions that define the kinematics of the Universe, even when the wavelets themselves are very simple. We also discuss the consequences of attributing these kinematics to, first, dark energy, and second, varying gravitational coupling strength. Utilizing some simplest wavelets, we demonstrate the competence of this framework in describing the baryon acoustic oscillation (BAO) data without any modifications to the agreement with cosmic microwave background measurements. This framework also provides a natural explanation for the bumps found in nonparametric observational reconstructions of the Hubble parameter and dark energy density as compensations of the dips suggested by some BAO data, and questions the physical reality of their existence. We note that utilizing this framework on top of the models that agree with both the cosmic microwave background and local ${H}_{0}$ measurements but are held back by BAO data, one may resurrect these models through the wiggly nature of wavelets that can naturally accommodate the BAO data. Finally, we also suggest narrowing the plausible set of admissible wavelets to further improve our framework by imposing conditions from expected kinematics of a viable cosmological model or first principle fundamental physics such as energy conditions.

Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions

Introducing additional information sources, such as hydrochemical signatures and water isotopes, into the model calibration has shown to be useful to enhance model robustness by increasing parameter identifiability and maintaining simulation reliability. Our study explores the added value of discharge young water fractions (Fyw, derived from the volume-weighted δ18O concentrations) on the model reliability as a calibration constraint. For this, we coupled a karst hydrological model (VarKarst) with a catchment-scale transport model (StorAge Selection (SAS) function approach) to simulate discharge δ18O concentration (δ18OQ) and corresponding Fyw. We performed a multi-variable calibration scheme by simultaneously constraining a large model ensemble (1x106 realizations) with respect to the model performance on discharge and Fyw. By searching a model output space in which the model performance on discharge and model performance on Fyw provides an optimal trade-off, we extracted hydrologically more informative model realizations. We tested our calibration approach at the Wasseralm spring, which supplies drinking water to the city of Vienna, Austria. The contribution of the information content of Fyw to the model robustness was assessed by the degree of reduction in the parameter and simulation uncertainties. Our results indicate that the inclusion of Fyw notably reduced the uncertainty in model parameters (6 parameters out of 8), simulations (14 % vs. 10 % by δ18OQ), and water balance components for the model internal states (around 40 %). Our findings reveal that Fyw confirms the model reliability (KGE: 0.71 ± 0.01 in validation) in that it mainly reduces the parameter equifinality by providing physically more plausible and identifiable parameter sets. Therefore, Fyw is a potentially useful metric to better constrain the model outputs, thereby limiting the model uncertainty.