Model Assumptions Research Articles

K-depth tests for testing simultaneously independence and other model assumptions in time series

We consider the recently developed K-depth tests for testing simultaneously independence and other model assumptions for univariate time series with a potentially related d-dimensional process of explanatory variables. Since these tests are based only on signs of residuals, they are easy to comprehend. They can be used in a full version and in a simplified version. While former investigations already showed that the full version is appropriate for testing model assumptions, we concentrate here on either testing the independence assumption on its own or on simultaneously testing independence and model assumptions with both types of tests. In an extensive simulation study, we compare these tests with several known independence test such as the runs test, the Durbin-Watson test, and the Von-Neumann-Rank-Ratio test. Finally, we demonstrate how the K-depth tests can be used for improved modeling of crack width time series depending on temperature measurements in a bridge monitoring.

Reaction zone structure of spontaneous reaction wave at steady subsonic and supersonic speeds

The reaction zone structure of spontaneous reaction wave at steady subsonic and supersonic speeds is discussed using numerical simulation and theoretical approaches. The main objective of this study is to develop the mathematical model of the spontaneous reaction wave propagating at a steady speed and to clarify the relationship between the reaction zone structure and non-dimensional parameters. A one-dimensional direct numerical simulation (DNS) of the spontaneous reaction wave propagation is performed, and the modeling assumptions are discussed based on the numerical results. The non-dimensional parameters, the Damköhler number and a parameter related to compressibility defined by the Mach number of the spontaneous reaction wave velocity, are introduced into the modeling. The mathematical model is developed using asymptotic techniques, and the solution of the reaction zone structure is analytically derived using Newton’s method. The relationship between reaction zone structure of spontaneous reaction wave and non-dimensional parameters is discussed based on the analytical solutions.

The Influencing Mechanism of Robustness of Emergency Medical Logistics: Mediating Role of Knowledge Integration

Drawing on the social capital theory, the research examines the impact of network size, network centrality, trust, and regulation on the knowledge integration and robustness of emergency medical logistics. Additionally, the research seeks to provide deeper insight into the link between the variables by studying how knowledge integration mediates the relationship between independent variables and the robustness of emergency medical logistics. The study utilized structural equation modeling to assess the underlying assumptions of the research model. A total of 465 valid questionnaires were collected from government departments, hospitals, social teams, and enterprises. The data processing and analysis were conducted using SPSS 23.0 and AMOS 24.0 software. The study’s outcome indicated that network size and network centrality have indirect effects on the robustness of emergency medical logistics through the intermediate variable of knowledge integration, but neither has a direct effect. Moreover, knowledge integration has a significant positive impact on the robustness of emergency medical logistics. Both trust and regulation have positive effects on the robustness of emergency medical logistics, and they also have positive effects on the robustness of emergency medical logistics through knowledge integration. This study is the inaugural exploration of the correlation between knowledge integration and the robustness of emergency medical logistics. It adds to the literature by providing evidence that knowledge integration is an essential emergency organization’s aide in promoting the robustness of emergency medical logistics. The findings of this study establish a strong theoretical foundation and practical significance for ensuring and improving the level of effectiveness in emergency medical logistics management.

Option Pricing Based on Neural Stochastic Differential Equations

Firstly, based on the Black-Scholes stock price model, the neural stochastic differential equation (NSDE) model was established by parameterizing the asset return rate and volatility as a drift network and a diffusion network, respectively. Secondly, in the empirical analysis, the underlying asset as a single stock option was used as the research object, and real stock data was used for the network training and testing. The experimental results show that the NSDE model can overcome the defects of the constant assumption of the Black-Scholes model. Finally, for the case where the price of the underlying asset of the option was unobservable, we proposed that the price of any target option and the price of a known option could be constrained within the Wasserstein distance of their risk-neutral equivalent martingale measure, and theoretically proved the method.

Detection of genomic alterations in liquid biopsies from patients with non-small cell lung cancer using FoundationOne Liquid CDx: a cost-effectiveness analysis

Objective Liquid biopsy (LB) is a non-invasive technique to detect genetic alterations by next-generation sequencing (NGS) when tissue biopsy is not available. This study aims to estimate in the Spanish setting, the cost-effectiveness of using FoundationOne Liquid CDx (F1L CDx), a novel blood-derived LB test based on NGS, versus non-molecular diagnosis (non-mDx) in patients with advanced non-small cell lung cancer (NSCLC) in whom tissue sampling is not feasible. Methods A joint model was developed combining a decision-tree with partitioned survival models to calculate the costs and health outcomes over a lifetime horizon, comparing F1L CDx in LB versus non-mDx. Only direct costs (expressed in €of 2023) were included and a 3% discount rate for future costs and effects was considered. Health outcomes were expressed in Life Years (LYs) and Quality-Adjusted Life Years (QALYs). Utilities and treatment efficacy were obtained from the literature. An expert panel of 11 Spanish oncologists determined the treatment allocation and validated all model inputs and assumptions. Several sensitivity analyses were performed to assess the robustness of the results. Results In a hypothetical cohort of 1,000 patients, LB using F1L CDx would detect 386 alterations, so those patients could be treated with targeted therapies or enrolled in clinical trials. Cost-effectiveness results showed that F1L CDx provides greater effectiveness than non-mDx (+383.95 LYs and +305.94 QALYs), with an additional cost of €2,898,308. The incremental cost-utility ratio was €9,473/QALY gained. The probabilistic sensitivity analysis confirmed the robustness of the cost-effectiveness results. Limitations Various limitations inherent to cost-effectiveness analyses were described. Conclusion LB with F1L CDx test is a cost-effective strategy in Spain for patients with advanced NSCLC without tissue sample available for molecular diagnosis, improving the personalized treatment of these patients.

Liquid Rocket Engine Performance Characterization Using Computational Modeling: Preliminary Analysis and Validation

The need to refuel future missions to Mars and the Moon via in situ resource utilization (ISRU) requires the development of LOX/LCH4 engines, which are complex and expensive to develop and improve. This paper discusses how the use of digital engineering—specifically physics-based modeling (PBM)—can aid in developing, testing, and validating a LOX/LCH4 engine. The model, which focuses on propulsion performance and heat transfer through the engine walls, was created using Siemens’ STAR-CCM+ CFD tool. Key features of the model include Eulerian multiphase physics (EMP), complex chemistry (CC) using the eddy dissipation concept (EDC), and segregated solid energy (SSE) for heat transfer. A comparison between the complete GRI 3.0 and Lu’s reduced combustion mechanisms was performed, with Lu’s mechanism being chosen for its cost-effectiveness and similar output to the GRI mechanism. The model’s geometry represents 1/8th of the engine’s volume, with a symmetric rotational boundary. The performance of this engine was investigated using NASA’s chemical equilibrium analysis (CEA) and STAR-CCM+ simulations, focusing on thrust levels of 125 lbf and 500 lbf. Discrepancies between theoretical predictions and simulations ranged from 1.4% to 28.5%, largely due to differences in modeling assumptions. While NASA CEA has a zero-dimensional, steady-state approach based on idealized conditions, STAR-CCM+ accounts for real-world factors such as multiphase flow, turbulence, and heat loss. For the 125 lbf case, a 9.2% deviation in combustion chamber temperature and a 15.0% difference in thrust were noted, with simulations yielding 113.48 lbf compared to the CEA’s 133.52 lbf. In the 500 lbf case, thrust reached 488 lbf, showing a 2.4% deviation from the design target and an 8.6% increase over CEA predictions. Temperature and pressure deviations were also observed, with the highest engine wall temperature at the nozzle throat. Monte Carlo simulations revealed that substituting LNG for LCH4 affects combustion dynamics. The findings emphasize the need for advanced modeling approaches to enhance the prediction accuracy of rocket engine performance, aiding in the development of digital twins for the CROME.

Sampling Confined Fission Tracks for Constraining Geological Thermal Histories

Fission-track modeling rests on etching, counting and measuring the lattice damage trails from uranium fission. The tools for interpreting fission-track data are advanced but the results are never better than the data. Confined-track samples must be an adequate size for statistical analysis, representative of the track population and consistent with the model assumptions and with the calibration data. Geometrical and measurement biases are understood and can be dealt with up to a point. However, the interrelated issues of etching protocol and track selection are more difficult to untangle. Our investigation favors a two-step protocol. The duration of the first step is inversely proportional to the apatite etch rate so that different apatites etch to the same Dpar. A long immersion reveals many more confined tracks, terminated by basal and prism faces. This allows consistent length measurements and permits orienting each track relative to the c-axis. Long immersion times combined with deep ion irradiation reveal confined tracks deep inside the grains. Provided it is long enough, the precise immersion time is not important if the effective etch times of the selected tracks are calculated from their measured widths. Then, whether the sample is mono- or multi-compositional, we can, post hoc, select tracks with the desired properties. The second part of the protocol has to do with the fact that fossil tracks in geological samples appear to be under-etched compared to induced tracks etched under the same conditions. This should be assumed if the semi-axes of a fitted ellipse plot above the induced-track line. In that case, an additional etch can increase the track lengths to a point where they are consistent with the model based on lab-annealing of induced tracks, a condition for valid thermal histories. Here too, it is possible to select a subset of tracks with effective etch times consistent with the model if the widths of confined tracks are measured along with their lengths and orientations.

Validation study on road traffic noise: assessing various traffic scenarios

TraNQuIL2 is an epidemiological research project, which addresses the relation of acute and long-term health effects from transportation noise and the benefit of different mitigation strategies. Within this project, a small validation study on the exposure modelling for various road traffic noise situations in both rural and urban areas of Switzerland was carried out. The study focuses on evaluating the accuracy of the emission and the sound propagation modelling to nearby buildings and aims at identifying potential exposure misclassifications. Results indicate a tendency of the model to overestimate actual source emissions (mean: +1.5 dB), which might be explained by lower actual travelling speeds or different pavement properties compared to model assumptions. As the sound propagation modelling yielded accurate results, this leads to a corresponding overestimation at exposed facades. However at facades facing away from the street, larger uncertainties in the propagation calculation and a tendency to overestimate the attenuation was observed, highlighting the complex nature of sound propagation in such situations. These findings emphasize the importance of using refined emission and sound propagation models and accurate input data for noise effect studies.

Dental arch shape in twins: A morphometric study of genetic influences

The objective of this study was to assess the relative contribution of genes to shape variation in the permanent dental arches in individuals of Western European descent. The dental casts from 64 monozygotic and 38 dizygotic twins, housed in the Adelaide Dental School's twin record collection, Australia, were assessed. The subjects were of Western European descent, with a mean age of 19.4 ± 5.4 years. Dental casts were scanned using a 3-dimensional scanner (3Shape E4, 3Shape, Copenhagen, Denmark), and landmarks were placed on incisal edges and cusp tips of canines, premolars, and molars. Procrustes superimposition and principal components analysis were applied to examine shape variation. Two-block partial least-squares analysis was used to assess shape covariation between arches. Structural equation modeling was utilized to decompose observed shape variation into genetic and environmental components using the normal assumptions of the twin model. The first 3 principal components (PCs) of the maxillary and mandibular arch were meaningful, accounting for 53% and 50% of the variation in shape space, respectively. The PCs represented shape variability as follows: PC1 - arch depth-width ratio, PC2 - arch taper, canine position (and first premolar rotation for the mandibular arch), and PC3 - incisor displacement and rotation. Genetic modeling indicated that a model incorporating additive genetic and unique environmental factors optimally explained the observed variation for all meaningful PCs. Within shape space, most of the variation in maxillary and mandibular arches exhibited moderate to high heritability (h2= 0.61-0.74). Maxillary and mandibular dental arches had strong and significant shape covariation, with high heritability in their reciprocal influences on shape (h2= 0.72-0.74; rpls coefficient= 0.87; P<0.05). In this cohort, dental arch shape variation was predominantly influenced by genetic factors. High covariation and heritability were observed between the maxillary and mandibular dental arches. This information may help inform decisions around orthodontic intervention.

On network deconvolution for undirected graphs.

Network deconvolution (ND) is a method to reconstruct a direct-effect network describing direct (or conditional) effects (or associations) between any two nodes from a given network depicting total (or marginal) effects (or associations). Its key idea is that, in a directed graph, a total effect can be decomposed into the sum of a direct and an indirect effects, with the latter further decomposed as the sum of various products of direct effects. This yields a simple closed-form solution for the direct-effect network, facilitating its important applications to distinguish direct and indirect effects. Despite its application to undirected graphs, it is not well known why the method works, leaving it with skepticism. We first clarify the implicit linear model assumption underlying ND, then derive a surprisingly simple result on the equivalence between ND and use of precision matrices, offering insightful justification and interpretation for the application of ND to undirected graphs. We also establish a formal result to characterize the effect of scaling a total-effect graph. Finally, leveraging large-scale genome-wide association study data, we show a novel application of ND to contrast marginal versus conditional genetic correlations between body height and risk of coronary artery disease; the results align with an inferred causal directed graph using ND. We conclude that ND is a promising approach with its easy and wide applicability to both directed and undirected graphs.

Improving analysis of cognitive outcomes in cardiovascular trials using different statistical approaches

BackgroundThe Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) questionnaires are commonly used to measure global cognition in clinical trials. Because these scales are discrete and bounded with ceiling and floor effects and highly skewed, their analysis as continuous outcomes presents challenges. Normality assumptions of linear regression models are usually violated, which may result in failure to detect associations with variables of interest.MethodsAlternative approaches to analyzing the results of these cognitive batteries include transformations (standardization, square root, or log transformation) of the scores in the multivariate linear regression (MLR) model, the use of nonlinear beta-binomial regression (which is not dependent on the assumption of normality), or Tobit regression, which adds a latent variable to account for bounded data. We aim to empirically compare the model performance of all proposed approaches using four large randomized controlled trials (ORIGIN, TRANSCEND, COMPASS, and NAVIGATE-ESUS), and using as metrics the Akaike information criterion (AIC). We also compared the treatment effects for the methods that have the same unit of measure (i.e., untransformed MLR, beta-binomial, and Tobit).ResultsThe beta-binomial consistently demonstrated superior model performance, with the lowest AIC values among nearly all the approaches considered, followed by the MLR with square root and log transformations across all four studies. Notably, in ORIGIN, a substantial AIC reduction was observed when comparing the untransformed MLR to the beta-binomial, whereas other studies had relatively small AIC reductions. The beta-binomial model also resulted in a significant treatment effect in ORIGIN, while the untransformed MLR and Tobit regression showed no significance. The other three studies had similar and insignificant treatment effects among the three approaches.ConclusionWhen analyzing discrete and bounded outcomes, such as cognitive scores, as continuous variables, a beta-binomial regression model improves model performance, avoids spurious significance, and allows for a direct interpretation of the actual cognitive measure.Trials registrationORIGIN (NCT00069784). Registered on October 1, 2003; TRANSCEND (NCT00153101). Registered on September 9, 2005; COMPASS (NCT01776424). Registered on January 24, 2013; NAVIGATE-ESUS (NCT02313909). Registered on December 8, 2014.

Prospects for a survey of the galactic plane with the Cherenkov Telescope Array

Approximately one hundred sources of very-high-energy (VHE) gamma rays are known in the Milky Way, detected with a combination of targeted observations and surveys. A survey of the entire Galactic Plane in the energy range from a few tens of GeV to a few hundred TeV has been proposed as a Key Science Project for the upcoming Cherenkov Telescope Array Observatory (CTAO). This article presents the status of the studies towards the Galactic Plane Survey (GPS). We build and make publicly available a sky model that combines data from recent observations of known gamma-ray emitters with state-of-the-art physically-driven models of synthetic populations of the three main classes of established Galactic VHE sources (pulsar wind nebulae, young and interacting supernova remnants, and compact binary systems), as well as of interstellar emission from cosmic-ray interactions in the Milky Way. We also perform an optimisation of the observation strategy (pointing pattern and scheduling) based on recent estimations of the instrument performance. We use the improved sky model and observation strategy to simulate GPS data corresponding to a total observation time of 1620 hours spread over ten years. Data are then analysed using the methods and software tools under development for real data. Under our model assumptions and for the realisation considered, we show that the GPS has the potential to increase the number of known Galactic VHE emitters by almost a factor of five. This corresponds to the detection of more than two hundred pulsar wind nebulae and a few tens of supernova remnants at average integral fluxes one order of magnitude lower than in the existing sample above 1 TeV, therefore opening the possibility to perform unprecedented population studies. The GPS also has the potential to provide new VHE detections of binary systems and pulsars, to confirm the existence of a hypothetical population of gamma-ray pulsars with an additional TeV emission component, and to detect bright sources capable of accelerating particles to PeV energies (PeVatrons). Furthermore, the GPS will constitute a pathfinder for deeper follow-up observations of these source classes. Finally, we show that we can extract from GPS data an estimate of the contribution to diffuse emission from unresolved sources, and that there are good prospects of detecting interstellar emission and statistically distinguishing different scenarios.Thus, a survey of the entire Galactic plane carried out from both hemispheres with CTAO will ensure a transformational advance in our knowledge of Galactic VHE source populations and interstellar emission.

Catastrophic fires, human displacement, and real estate prices in California

Millions of people are displaced by natural disasters each year, yet little is known about how evacuees affect host communities. We analyze the migratory effects of the most destructive fire in California history, the 2018 Camp Fire, which destroyed over 18,000 structures and displaced roughly 50,000 people. By merging geospatial information on the fire’s footprint with Zillow’s housing transaction data, we estimate both the spatial and temporal effects of the fire on real estate prices at a granular level. A number of important insights emerge. First, within 25 miles of the fire’s footprint, home prices increased by 13 percent in the six-week aftermath of the fire. Effects decay with distance and are statistically insignificant beyond 100 miles. Second, effects are detected within two weeks of the fire, fully materialize within four weeks, and are persistent up to ten months (which exhausts our period of consideration). Results are consistent with the relocation decisions of evacuees and are robust to a variety of specifications and modeling assumptions.

Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient.

Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO2 and CH4 porewater variations. Our study showcases insights gained by using feature-level data and microorganism-metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.

Coherence of Multidimensional Pair Production Discharges in Polar Caps of Pulsars

We report on the first self-consistent multidimensional particle-in-cell numerical simulations of nonhomogeneous pair discharges in polar caps of rotation-powered pulsars. By introducing strong inhomogeneities in the initial plasma distribution in our simulations, we analyze the degree of self-consistently emerging coherence of discharges across magnetic field lines. In 2D, we study discharge evolution for a wide range of physical parameters and boundary conditions corresponding to both the absent and free escape of charged particles from the surface of a neutron star. We also present the results of the first 3D simulations of discharges in a polar cap with a distribution of the global magnetospheric current appropriate for a pulsar with 60° inclination angle. For all parameters, we find the coherence scale of pair discharges across magnetic field lines to be of the order of the gap height. We also demonstrate that the popular “spark” model of pair discharges is incompatible with the universally adopted force-free magnetosphere model: intermittent discharges fill the entire zone of the polar cap that allows pair cascades, leaving no space for discharge-free regions. Our findings disprove the key assumption of the spark model about the existence of isolated distinct discharge columns.

Genome-Wide Association Study Identifies Genetic Polymorphisms for Folate-Related Biomarkers in Chinese Preconception Women

BackgroundSingle-nucleotide polymorphism (SNP) allele frequencies, dietary habits, and folate status and their associations vary across ethnic populations. Little is known about the SNPs accounting for variations of folate-related biomarkers for Chinese preparing-for-pregnant females. ObjectivesWe aimed to identify SNPs contributing to RBC and serum folate, vitamin B-12, and homocysteine concentrations in Chinese female preconception population. MethodsA genome-wide association study was conducted on 1000 randomly selected preconception Chinese women from the Shanghai Preconception Cohort. SNPs were genotyped using Illumina chips, and associations with biomarkers were assessed using simple linear regression models under the assumption of an additive genetic model. Genome-wide significance was considered at P < 10−7. ResultsThe MTHFR rs1801133 was the major genetic coding variant contributing to RBC folate, serum folate, and homocysteine concentrations (P = 2.28 × 10−16; P = 8.85 × 10−8, and P = 2.46 × 10−13, repsectively). It is associated with increased RBC folate (β: 0.154 per additional risk allele after log transform), decreased serum folate (β: −0.951 per additional risk allele), and increased serum homocysteine concentrations (β: 1.153 per additional risk allele). The predominant SNP associated with serum folate was rs147162222 in NTRK2 (P = 2.55 × 10−8), although that associated with homocysteine was rs77025184 located between PDE7B and LINC00271 (P = 4.91 × 10−17). For vitamin B-12, FUT2 rs1047781 was the dominant genetic variant (P = 1.59 × 10−10). The numbers of signals with a P value of <10−7 for RBC folate, serum folate, vitamin B-12, and homocysteine were 12, 18, 8, and 614, respectively. ConclusionsThis study represents the first genome-wide association study focusing on folate-related biomarkers in a Chinese preparing-for-pregnant female population. The contributions of dominent SNPs to each biomarker are partly different from other populations. The rs1801133 (C677T) in MTHFR is the predominant genetic variant contributing to RBC folate and rs1047781 (A385T) in FUT2 as the primary one explaining vitamin B-12. Notably, the intronic rs147162222 and noncoding rs77025184 are the predominant SNPs for serum folate and homocysteine, respectively.

Galaxy shapes in Magneticum

Context. Despite being one of the most fundamental properties of galaxies that dictate the form of the potential, the 3D shapes are intrinsically difficult to determine from observations. The improving quality of triaxial modeling methods in recent years has made it possible to measure these shapes more accurately. Aims. This study provides a comprehensive understanding of the stellar and dark matter (DM) shapes of galaxies and the connection between them. As these shapes are the result of the formation history of a galaxy, we investigate which galaxy properties they are correlated with, which will be especially useful for interpreting the results from dynamical modeling. Methods. Using the hydrodynamical cosmological simulation Magneticum Pathfinder Box4 (uhr), we computed the stellar and DM intrinsic shapes of 690 simulated galaxies with stellar masses above 2 × 1010 M⊙ at three different radii with an iterative unweighted method. We also determined their morphologies, their projected morphological and kinematic parameters, and their fractions of in situ formed stars. Results. The DM follows the stellar component in shape and orientation at three half-mass radii, indicating that DM is heavily influenced by the baryonic potential in the inner parts of the halo. The outer DM halo is independent of the inner properties such as the DM shape or galaxy morphology, however, and is more closely related to the large-scale anisotropy of the gas inflow. Overall, DM halo shapes are prolate, consistent with previous literature. The stellar shapes of galaxies are correlated with their morphology, with early-type galaxies featuring more spherical and prolate shapes than late-type galaxies out to 3 R1/2. Galaxies with more rotational support are flatter, and the stellar shapes are connected to the mass distribution, though not to the mass itself. In particular, more extended early-type galaxies have larger triaxialities at a given mass. Finally, the shapes can be used to better constrain the in situ fraction of stars when combined with the stellar mass. Conclusions. The relations between shape, mass distribution, and in situ formed star fraction of galaxies show that the shapes depend on the details of the accretion history through which the galaxies are formed. The similarities between DM and stellar shapes in the inner regions of galaxy halos signal the importance of baryonic matter for the behavior of DM in galaxies and will be of use for improving the underlying assumptions of dynamical models for galaxies in the future. However, at large radii the shapes of the DM are completely decoupled from the central galaxy, and their shapes and spin are coupled more to the large scale inflow than to the galaxy in the center.

Particle damping equivalent method based on force chain for high frequency vibration reduction: Mechanism analysis and experimental verification

A particle damping equivalent method based on force chain is newly proposed for simulating the behavior of particle damper (PD) with higher accuracy. Compared with other existing equivalent methods, this method considers the contact between particles and evaluates the particle motion state. Firstly, the particle damping equivalent method based on the theory of force chain and contact model is proposed, and the simulation process of the equivalent method is described. Then, this equivalent method is adopted to simulate the high frequency vibration of pipe installed with PD using SAP2000 software. The simulated vibration response exhibits excellent agreement with experimental results, validating the effectiveness of the proposed equivalent method. Finally, based on the calculation results, it is observed that the particle motion state of the PD in the experiment is quasi-static. This further shows that the particle chain in the damper under high frequency vibration can ignore the wave propagation behavior, which aligns with the assumption of the particle contact model.

Estimating the Effective Size of European Wolf Populations.

Molecular methods are routinely used to estimate the effective size of populations (N e). However, underlying model assumptions are frequently violated to an unknown extent. Although simulations can detect sources of bias and help to adjust sampling strategies and analyses methods, additional information from empirical data can also be used to calibrate methods and improve molecular N e estimation methods. Here, we take advantage of long-term genetic and ecological monitoring data of the grey wolf (Canis lupus) in Germany, and detailed population genetic studies in Poland, Spain and Portugal to improve N e estimation strategies in this species, and species with similar life history traits. We first calculated N e from average lifetime reproductive success and detailed census data from the German population, which served as a baseline to compare to molecular estimates based on linkage disequilibrium and sibship frequency. This yielded a robust N e/N c estimation that we used to calibrate molecular estimates of German, Polish and Iberian wolf populations. The linkage disequilibrium method was strongly influenced by spatial genetic structure, much more than the sibship frequency method. When N e was estimated in local neighbourhoods, both methods yielded comparable results. Estimates of the metapopulation effective size seemed to correspond generally well with the sum of the estimates of local neighbourhoods. Overall, we found that the number of packs is a good proxy of the effective population size. Using this as a rule of thumb, we evaluated for all European wolf populations the N e 500 indicator and concluded that half of the European wolf populations do not yet fulfil this criterion.

A systematic review of cost-effectiveness analyses of gene therapy for hemophilia type A and B.

In 2022-2023, the US Food and Drug Administration approved 2 novel gene therapies, valoctocogene roxaparvovec and etranacogene dezaparavovec, for hemophilia A and B, respectively. These one-time-administered gene therapies have been marketed at prices that create financial challenges for payers and patients. Understanding the magnitude and uncertainties around the long-term value of these therapies and how they can potentially relate to managed care practices is of high interest to the payer and patient community. To conduct a systematic review of cost-effectiveness analysis (CEA) studies to assess (1) the long-term value of valoctocogene roxaparvovec and etranacogene dezaparavovec and (2) the relevance and validity of the underlying data and assumptions used in the CEA models and discuss how they relate to the challenges identified for CEAs of gene therapies. A systematic review of cost-effectiveness studies of novel hemophilia A and B gene therapy was conducted. PubMed and Embase were searched for published studies from inception to January 12, 2024. Original research articles published in English that conducted a CEA on gene therapy treatments for hemophilia A and B, with a comparison of incremental costs and health effects, were considered. Critical appraisal of the quality of reporting and the underlying modeling assumptions were conducted to assess the relevance and validity of the results. Two hundred thirty-eight studies were identified, of which 4 met the inclusion criteria. Three studies were conducted from a US health care perspective and 1 from a Dutch societal perspective. Despite the high upfront costs of the gene therapies, all included studies' (3 hemophilia A and 1 hemophilia B) modeled results showed that gene therapies had lower overall costs and better health outcomes compared with factor concentrate replacement therapies and emicizumab. The results were driven by the assumption that gene therapies will have a durable effect of at least 10 years and offset the high cost of the current standard of care. The modeled health improvements varied substantially across studies, showing that the long-term value is sensitive to varying clinical and economic assumptions. The novel hemophilia gene therapy treatments can potentially be a cost-effective use of treatment resources if the treatment effects are durable over time. To reduce the risk for payers while still facilitating patient access, outcomes-based agreements similar to what has recently been proposed by the Centers for Medicare & Medicaid Services for sickle-cell therapies are well supported.