Lower Estimates Research Articles

Improved Position Sensorless Resonant Frequency Tracking Control Method for Linear Oscillatory Machine

To improve the reliability of control system and obtain the maximum output efficiency, it is very necessary to carry out the position sensorless piston stroke control and the resonance frequency tracking control for linear oscillatory machine (LOM) at the same time. The conventional resonant frequency tracking control method based on model reference adaptive system (MRAS) has the problem of low estimation accuracy caused by inaccurate model parameters. In order to obtain more accurate resonant frequency, an improved position sensorless resonant frequency tracking control method is proposed in this article. In this method, the adjustable model is constructed based on the mechanical dynamics equation of LOM to track the system resonant frequency. A hybrid terminal sliding-mode observer (HTSMO) is designed to replace the conventional reference model, which can obtain more accurate velocity reference signal for adjustable model by introducing the current error feedback link, thereby further improving the resonant frequency tracking accuracy. Moreover, a second-order generalized integrator (SOGI) is introduced to filter the estimated velocity signal of HTSMO. The filtered velocity signal is not only used for the adjustable model to track the resonant frequency, but also used to obtain the smooth piston stroke signal for the stroke closed-loop control. Comprehensive simulation and experimental results have proved the effectiveness and the superiority of the proposed method.

On the Minkowski dimension of some invariant sets of dynamical systems

Abstract. It is well known that a fractal set is not a submanifold of the ambient space. However, fractals arise as invariant subsets even in infinitely smooth conditions and the Minkowski dimension serves in this case as a characteristic of complexity of this scale. For example, when the equilibrium state during the Andronov-Hopf bifurcation losses its stability, the closure of the non-singular trajectory is a parametrically defined curve of the fractal type. In this work the fractal dimension of such curves is calculated. In addition, special two-parameter family of functions is studied such that Minkowski dimension of their graphs varies from 1 to 2. The obtained result allows us to implement a regular dynamic system with an isolated hyperbolic point such that the closure of two-dimensional stable manifold of this point may have Minkowski dimension greater than 2. To calculate the graph dimension, the segment of the argument defining the graph is split into two parts. The dimension of the first part of the graph can be estimated from above by direct calculation of the corresponding curve’s length. The upper estimation of the other part’s dimension is provided by means of the area of rectangle containing this curve. The lower estimation of the Minkowski dimension is based on calculating the cardinality of ε -distinguishable set of graph points.

Sharp Lower Estimations for Invariants Associated with the Ideal of Antiderivatives of Singularities

Sharp Lower Estimations for Invariants Associated with the Ideal of Antiderivatives of Singularities

Flow resistance law in channels with emergent rigid vegetation

AbstractFlow resistance estimate is a challenging topic for establishing flooding propensity of streams, designing river restoration works, and evaluating the use of soil bioengineering practices. In this paper, flume measurements with rigid cylinders set in two arrangements (aligned, staggered) were used to evaluate the effect of rigid emergent vegetation on flow resistance. A well‐known theoretical flow resistance equation was firstly reviewed. Then, it was calibrated and tested by measurements performed for these arrangements with six concentrations (0.53–11.62 stems dm−2). The analysis was conducted using three approaches: (i) distinguishing the experimental runs corresponding to different arrangements and stem concentrations; (ii) using only a scale factor representing the effect of the stem concentration; and (iii) joining all available data. The results demonstrated that the flow resistance equation gives an accurate estimate of the Darcy–Weisbach friction factor f, characterized, for the best approach among the tested ones, by errors less than or equal to ±5% for 95.9% of the examined cases for the aligned arrangement and for the staggered arrangement less than or equal to ±5% for 94.2% of the examined cases. For both arrangements, the measurements demonstrated that, for a given longitudinal distance between vegetation elements, flow resistance increases for decreasing values of the transverse distance and, for a given transverse distance, f decreases for increasing values of the longitudinal distance between elements. Finally, in the range of the investigated stem concentrations, the influence of the arrangement on flow resistance resulted negligible.

Global probability distribution structure-sparsity filter pruning for edge fault diagnosis in resource constrained wireless sensor networks

In this paper, a global probability distribution structure-sparsity filter pruning is proposed to address the problem of difficult deployment of diagnostic models in resource constrained wireless sensor networks (WSNs) for edge fault diagnosis. Firstly, local and global weight distributions are analyzed. A global probability distribution weight sparsity method is proposed to obtain the global sparse boundary and the important features of the model. Secondly, according to the distribution of weight amplitude, the problem of uneven weight distribution is disclosed. A computational acceleration sensing method is proposed to reduce the high computational cost caused by small weight amplitude with low importance estimation. Moreover, a novel layer filter clustering pruning scheme is proposed. The intra-layer filters are classified and redundant filters are removed by using the clustering idea according to the predetermined pruning rate. Thus, the structure-sparsity filter pruning is realized. Compared with other advanced filter pruning methods, the proposed method analyzes the global and local model weight distribution and the influence of weight importance on the computational complexity of the model. The proposed method then performs filter pruning on the importance of overall filters for each network layer rather than individual filters. The accuracy of the proposed method on experimental dataset for pruned ResNet8 model under pruning rate at 0.95 is 99.12% with 3.668K parameters and 3.636MFLOPs. The experimental results elucidate that the proposed method is more suitable for deployment in resource-constrained WSNs for fault diagnosis of rotating machinery. This provides a potential solution for practical engineering applications.

Estimates for low Steklov eigenvalues of surfaces with several boundary components

R\'esum\'eIn this article, we give computable lower bounds for the first non-zero Steklov eigenvalue $$\sigma _1$$ σ 1 of a compact connected 2-dimensional Riemannian manifold M with several cylindrical boundary components. These estimates show how the geometry of M away from the boundary affects this eigenvalue. They involve geometric quantities specific to manifolds with boundary such as the extrinsic diameter of the boundary. In a second part, we give lower and upper estimates for the low Steklov eigenvalues of a hyperbolic surface with a geodesic boundary in terms of the length of some families of geodesics. This result is similar to a well known result of Schoen, Wolpert and Yau for Laplace eigenvalues on a closed hyperbolic surface.

Reverse calculation and quantitative estimation of JRC3D for rough rock fracture surfaces in various shear directions

The quantitative evaluation of the three-dimensional roughness feature of natural rock fracture surface is essential for predicting shear strength. This article presents an effective approach to estimate the three-dimensional roughness of natural fracture surfaces from the two-dimensional roughness of fracture profile. Firstly, four types of rough fracture samples were created using rock-like materials, followed by conducting direct shear tests of the fracture surfaces under 4 different normal pressures and 4 shear directions. The results of the shear strength tests exhibited a distinct discrete pattern and consistently increased with higher normal pressures. Furthermore, the distribution of the damage area on the fracture surface after shear was significantly impacted by the distribution and size of asperities, as well as the shear direction. The three-dimensional roughness of four fracture surfaces in different directions was first reverse calculated using the shear strength model. Using the weighted positive angle, the estimation of the three-dimensional roughness in different directions of the fracture surface was then determined from the two-dimensional roughness of fracture profiles using both the arithmetic mean method and the weighted average method. The weighted average method effectively captures the contribution of the two-dimensional roughness of fracture profiles to the three-dimensional roughness of fracture surfaces, and exhibits a lower estimation error compared to the arithmetic mean method. Compared to other roughness indicators, the three-dimensional roughness evaluated through the weighted positive angle indicator are closest to the experimental result. Finally, the influence of transverse spacing on the estimated three-dimensional roughness was discussed.

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees

Identifying safe areas is a key point to guarantee trust for systems that are based on Deep Neural Networks (DNNs). To this end, we introduce the AllDNN-Verification problem: given a safety property and a DNN, enumerate the set of all the regions of the property input domain which are safe, i.e., where the property does hold. Due to the #P-hardness of the problem, we propose an efficient approximation method called ε-ProVe. Our approach exploits a controllable underestimation of the output reachable sets obtained via statistical prediction of tolerance limits, and can provide a tight —with provable probabilistic guarantees— lower estimate of the safe areas. Our empirical evaluation on different standard benchmarks shows the scalability and effectiveness of our method, offering valuable insights for this new type of verification of DNNs.

Productivity costs of schizophrenia spectrum and other psychotic disorders by friction cost and human capital methods: The Northern Finland Birth Cohort 1966

PurposePsychotic disorders are associated with substantial productivity costs; however no previous studies have compared these between schizophrenia spectrum (SSD) and other psychotic disorders (OP). The human capital method (HCM) and the friction cost method (FCM) are the two most common approaches to assess productivity costs. The HCM focuses on employees’ perspectives on the costs, whereas the FCM demonstrates employers’ perspectives. Studies comparing these methods when estimating the productivity costs of psychoses are lacking.MethodsUtilizing the Northern Finland Birth Cohort 1966 with linkages to national registers, we compared the adjusted productivity costs of SSD (n = 216) and OP (n = 217). The productivity costs were estimated from ages 18 to 53 including projections to statutory retirement age using the FCM and HCM.ResultsWhen estimated via the HCM, productivity losses were higher for SSD (€193,940) than for OP (€163,080). However, when assessed using the FCM, costs were significantly lower for SSD (€2,720) than for OP (€4,430). Productivity costs varied by sex and various clinical and occupational factors.ConclusionThis study highlights how productivity costs vary by psychosis diagnosis. These differences should be noted when planning interventions. The low FCM estimates indicate the need of interventions before or during the early phases of psychoses. From a societal perspective, interventions are needed, particularly for those with highest HCM productivity losses, such as males with SSD. Besides psychiatric services, the roles of social services, employment agencies and occupational health care should be considered when helping individuals with psychoses to working life.

Risk assessment on the impact of Non-Darcy flow on unconventional well performance.

Nano-pores in unconventional reservoirs can cause deviations from Darcy's law where permeability becomes a strong function of pore size and pore pressure. As pores become smaller, the interaction of gas molecules with the pore walls becomes increasingly dominant compared to interactions between gas molecules. This increases gas mobility leading permeabilities measured in the lab not to be accurate at reservoir conditions. Thus, corrections to Darcy flow may be needed when analyzing well production behavior. This paper demonstrates a novel workflow for modeling the impact of non-Darcy flow regimes (i.e., gas slippage, transition flow and Knudsen diffusion) from pore scale characterization to reservoir scale flow simulation. A stochastic approach is used for uncertainty assessment on non-Darcy corrections needed for methane mobility as pore pressure depletes based on reservoir properties, pore sizes, rock compressibility and compaction. Flow simulations are conducted for a range of scenarios to test the impact on the recovery of an unconventional well. Study is conducted using a commercial simulator since workflow modifies the input to the simulator and does not need a new code development. The workflow is demonstrated using field data and shows that non-Darcy flow regimes can have significant impact by increasing gas mobility at low pore pressures near hydraulic fractures. For the field under study, ignoring non-Darcy flow risks up to 20% lower estimations in cumulative gas production under certain scenarios.

Defining Incidental Versus Non-incidental COVID-19 Hospitalizations.

Background Rates of COVID-19 hospitalization are an important measure of the health system burden of severe COVID-19 disease and have been closely followed throughout the pandemic. The highly transmittable, but often less severe, Omicron COVID-19 variant has led to an increase in hospitalizations with incidental COVID-19 diagnoses where COVID-19 is not the primary reason for admission. There is a strong public health need for a measure that is implementable at low cost with standard electronic health record (EHR) datasetsthat can separate these incidental hospitalizations from non-incidental hospitalizations where COVID-19 is the primary cause or an important contributor. Two crude metrics are in common use. The first uses in-hospital administration of dexamethasone as a marker of non-incidental COVID-19 hospitalizations. The second, used by the United States (US) CDC, relies on a limited set of COVID-19-related diagnoses (i.e., respiratory failure, pneumonia). Both measures likely undercount non-incidental COVID-19 hospitalizations. We therefore developed an improved EHR-based measurethat is better able to capture the full range of COVID-19 hospitalizations. Methods We conducted a retrospective study of EDvisit data from a national emergency medicine group from April 2020 to August 2023. We assessed the CDC approach, the dexamethasone-based measure, and alternative approaches that rely on co-diagnoses likely to be related to COVID-19, to determine the proportion of non-incidental COVID-19 hospitalizations. Results Of the 153,325 patients diagnosed with COVID-19 at 112 general EDs in 17 US states, and admitted or transferred, our preferred measure classified 108,243 (70.6%) as non-incidental, compared to 71,066 (46.3%) using the dexamethasone measure and 77,399 (50.5%) using the CDC measure. Conclusions Identifying non-incidental COVID-19 hospitalizations using ED administration of dexamethasone or the CDC measure provides substantially lower estimates than our preferred measure.

Barriers to COVID-19 Vaccination in a Troop of Fleet Antiterrorism Security Team Marines: Observational Study.

In 2019, the World Health Organization declared the reluctance to vaccinate despite the availability of vaccination services as one of the top 10 threats to global health. In early 2021, self-reported reluctance to vaccinate among military personnel might have been considered a significant threat to national security. Having a choice architecture that made COVID-19 vaccination optional rather than required for military personnel could have inadvertently undermined military readiness if vaccination uptake did not reach an acceptable threshold. The purpose of this observational study was to examine Marines' self-reported reasons for planning to decline the COVID-19 vaccine to understand their barriers to vaccination. As the vaccination became available to 1 company of Fleet Antiterrorism Security Team (FAST) Marines in early 2021, company command required those planning to decline vaccination to write an essay with up to 5 reasons for their choice. These essays provided the data for this study. Qualitative descriptive analysis with elements from grounded theory was used to thematically categorize FAST Marines' written reasons for planning to decline the COVID-19 vaccine into a codebook describing 8 key behavioral determinants. Interrater agreement among 2 qualitatively trained researchers was very good (κ=0.81). A troop of 47 Marines provided 235 reasons why they planned to decline the COVID-19 vaccine. The most frequent reasons were difficulty understanding health information (105/235, 45%), low estimates of risk (33/235, 14%), and fear of physical discomfort (29/235, 12%). Resulting interventions directly targeted Marines' self-reported reasons by reducing barriers (eg, normalized getting the vaccine), increasing vaccine benefits (eg, improved access to base gyms and recreational facilities), and increasing nonvaccine friction (eg, required in writing 5 reasons for declining the vaccine). Understanding the barriers military personnel experience toward COVID-19 vaccination remains critical as vaccine acquisition and availability continue to protect military personnel. Insights from subpopulations like FAST Marines can enhance our ability to identify barriers and appropriate intervention techniques to influence COVID-19 vaccination behaviors.

Lower average estimate for the minimum modulus on circles foran entire function of genus zero

The article was written based on the materials of the joint report of the authors, made by them at the Sixth International Conference “Functional spaces. Differential operators. Problems of mathematical education,” dedicated to the centenary of the birth of Corresponding Member of the Russian Academy of Sciences, Academician of the European Academy of Sciences L.D.Kudryavtsev. For an entire function represented by a canonical product of genus zero with positive roots, the following result is proved. For any \(\delta\in(0,1/3]\), the minimum modulus of such a function exceeds on average the maximum of its modulus raised to the power \(-1-\delta,\) on any segment whose end ratio is equal to \(\exp(
 2/\delta).\) The main theorem is illustrated by two examples. The first of them shows that instead of the exponent \(-1-\delta\) it is impossible to take \(-1.\) The second example demonstrates the impossibility of replacing the value \(\exp(2/\delta)\) by the value\(28/(15\delta)\) in the theorem for small \(\delta.\)

Deaths and cardiopulmonary events following colorectal cancer screening-A systematic review with meta-analyses.

Colorectal cancer screening programmes (CRCSPs) are implemented worldwide despite recent evidence indicating more physical harm occurring during CRCSPs than previously thought. Therefore, we aimed to review the evidence on physical harms associated with endoscopic diagnostic procedures during CRCSPs and, when possible, to quantify the risk of the most serious types of physical harm during CRCSPs, i.e. deaths and cardiopulmonary events (CPEs). Systematic review with descriptive statistics and random-effects meta-analyses of studies investigating physical harms following CRCSPs. We conducted a systematic search in the literature and assessed the risk of bias and the certainty of the evidence. We included 134 studies for review, reporting findings from 151 unique populations when accounting for multiple screening interventions per study. Physical harm can be categorized into 17 types of harm. The evidence was very heterogeneous with inadequate measurement and reporting of harms. The risk of bias was serious or critical in 95% of assessments of deaths and CPEs, and the certainty of the evidence was very low in all analyses. The risk of death was assessed for 57 populations with large variation across studies. Meta-analyses indicated that 3 to 23 deaths occur during CRCSPs per 100,000 people screened. Cardiopulmonary events were assessed for 55 populations. Despite our efforts to subcategorize CPEs into 17 distinct subtypes, 41% of CPE assessments were too poorly measured or reported to allow quantification. We found a tendency towards lower estimates of deaths and CPEs in studies with a critical risk of bias. Deaths and CPEs during CRCSPs are rare, yet they do occur during CRCSPs. We believe that our findings are conservative due to the heterogeneity and low quality of the evidence. A standardized system for the measurement and reporting of the harms of screening is warranted. PROSPERO Registration number CRD42017058844.

Highly flexible copper tape decorated with Ag nanoarrays as ultrasensitive SERS platforms for multi-hazardous pollutant sensing.

Ahighly flexible and cost-effective copper tape decorated with silver nanoparticles (Cu-TAg) has been developed for surface-enhanced Raman spectroscopy (SERS) sensing of multi-hazardous environmental pollutants. Highly ordered and spherical-shaped silver nanoarrays have been fabricated using a low-cost thermal evaporation method. The structural, morphological, and optical properties of Cu-TAg sensors have been studied and correlated to the corresponding SERS performances. The size of nanoparticles has been successively tuned by varying the deposition time from 5 to 25s. The nanoparticle sizes were enhanced with an increase in the evaporation time. SERS investigations have revealed that the sensing potential is subsequently improved with an increase in deposition time up to 10s and then deteriorates with further increase in Ag deposition. The highest SERS activity was acquired for an optimum size of ~ 37nm; further simulation studies confirmed this observation. Moreover, Cu-TAg sensors exhibited high sensitivity, reproducibility, and recycling characteristics to be used as excellent chemo-sensors. The lower detection limit estimation revealed that it can sense even in the pico-molar range for sensing of rhodamine 6G and methylene blue. The estimated enhancement factor of the sensor is found to be 9.4 × 107. Molecular-specific sensing of a wide range of pollutants such as rhodamine 6G, alizarin red, methylene blue, butylated hydroxy anisole, and penicillin-streptomycin is demonstrated with high efficiencies for micromolar spiked samples. Copper tape functionalized with Ag arrays thus demonstrated to be a promising candidate for low-cost and reusable chemo-sensors for environmental remediation applications.

Think global act local: The dependency of global lithium-ion battery emissions on production location and material sources

The pursuit of low-carbon transport has significantly increased demand for lithium-ion batteries. However, the rapid increase in battery manufacturing, without adequate consideration of the carbon emissions associated with their production and material demands, poses the threat of shifting the bulk of emissions upstream. In this article, a life cycle assessment (LCA) model is developed to account for the cradle-to-gate carbon footprint of lithium-ion batteries across 26 Chinese provinces, 20 North American locations and 19 countries in Europe and Asia. Analysis of published LCA data reveals significant uncertainty associated with the carbon emissions of key battery materials; their overall contribution to the carbon footprint of a LIB varies by a factor of ca. 4 depending on production route and source. The links between production location and the gate-to-gate carbon footprint of battery manufacturing are explored, with predicted median values ranging between 0.1 and 69.5 kg CO2-eq kWh−1. Leading western-world battery manufacturing locations in the US and Europe, such as Kentucky and Poland are found to have comparable carbon emissions to Chinese rivals, even exceeding the carbon emissions of battery manufacturing in several Chinese provinces. Such resolution on material and energy contributions to the carbon footprint of LIBs is essential to inform policy- and decision-making to minimise the carbon emissions of the battery value chain. Given the current status quo, the global carbon footprint of the lithium-ion battery industry is projected to reach up to 1.0 Gt CO2-eq per year within the next decade. With material supply chain decarbonisation and energy savings in battery manufacturing, a lower estimate of 0.5 Gt CO2-eq per year is possible.

Methodological moderators of average outdegree centrality: A meta-analysis of child and adolescent friendship networks

AbstractEmpirical articles vary considerably in how they measure child and adolescent friendship networks. This meta-analysis examines four methodological moderators of children’s and adolescents’ average outdegree centrality in friendship networks: boundary specification, operational definition of friendship, unlimited vs. fixed choice design, and roster vs. free recall design. Specifically, multi-level random effects models were conducted using 261 average outdegree centrality estimates from 71 English-language peer-reviewed articles and 55 unique datasets. There were no significant differences in average outdegree centrality for child and adolescent friendship networks bounded at the classroom, grade, and school-levels. Using a name generator focused on best/close friends yielded significantly lower average outdegree centrality estimates than using a name generator focused on friends. Fixed choice designs with under 10 nominations were associated with significantly lower estimates of average outdegree centrality while fixed choice designs with 10 or more nominations were associated with significantly higher estimates of average outdegree centrality than unlimited choice designs. Free recall designs were associated with significantly lower estimates of average outdegree centrality than roster designs. Results are discussed within the context of their implications for the future measurement of child and adolescent friendship networks.

A Fast Calibration Method for an sEMG-Based Lower Limb Joint Torque Estimation Model

The joint torque estimation model based on surface electromyography (sEMG) signals needs to recalibrate the model parameters when used for joint torque estimation at different volunteers. However, the feature transferability drops significantly in higher task-specific layers, which reduce the performance of the model. The generalization of joint torque estimation models among different volunteers has become a challenge. In this paper, a fast calibration method based on a deep adaptive regression network is proposed to reduce the frequency and time of model recalibration when volunteers change. The proposed method associates source domain (SD) data with target domain (TD) data through migration learning. The maximum mean difference (MMD) adaptive method is used to migrate the model trained in the SD dataset to the TD dataset, which avoids the recalibration required in the joint torque estimation model. The experimental results show that the proposed method can improve the migration ability of the model used for estimating joint torque and achieve the generalization application of the model on different volunteer datasets. Moreover, the proposed method can reduce the calibration operations and iterations of the model caused by volunteer changes and improve the speed of joint torque estimation. The optimal normalized root mean square error (NRMSE) and Pearson correlation coefficient (ρ) of knee extension/flexion joint torque estimation reached 0.02198/0.02565 and 0.9892/0.9839, respectively.

Market-based Estimation of Average Electricity Outage Costs in the United States

Electricity outage cost (EOC) estimates ($ per kWh unserved) are essential input data for optimal reliability planning and efficient pricing of electricity services. Based on the 2019-2020 market data published by two US government agencies for the lower 48 states, this paper’s EOC estimates by census region and year are median values of $1.39 to $2.93 per kWh unserved, well below the estimate of $9 per kWh unserved adopted by Texas for optimal reliability planning. The policy implications of adopting our lower EOC estimate are (a) a reduction in an electric grid’s optimal planning reserve to improve the grid’s cost efficiency; and (b) a decline in the grid’s marginal cost-based retail price to encourage welfare-enhancing end-use consumption.

Genome-wide analysis of population structure, effective population size and inbreeding in Iranian and exotic horses.

Population structure and genetic diversity are the key parameters to study the breeding history of animals. This research aimed to provide a characterization of the population structure and to compare the effective population size (Ne), LD decay, genetic diversity, and genomic inbreeding in Iranian native Caspian (n = 38), Turkmen (n = 24) and Kurdish (n = 29) breeds and some other exotic horses consisting of Arabian (n = 24), Fell pony (n = 21) and Akhal-Teke (n = 20). A variety of statistical population analysis techniques, such as principal component analysis (PCA), discriminant analysis of principal component (DAPC) and model-based method (STRUCTURE) were employed. The results of the population analysis clearly demonstrated a distinct separation of native and exotic horse breeds and clarified the relationships between studied breeds. The effective population size (Ne) for the last six generations was estimated 54, 49, 37, 35, 27 and 26 for the Caspian, Kurdish, Arabian, Turkmen, Akhal-Teke and Fell pony breeds, respectively. The Caspian breed showed the lowest LD with an average r2 value of 0.079, while the highest was observed in Fell pony (0.148). The highest and lowest average observed heterozygosity were found in the Kurdish breeds (0.346) and Fell pony (0.290) breeds, respectively. The lowest genomic inbreeding coefficient based on run of homozygosity (FROH) and excess of homozygosity (FHOM) was in the Caspian and Kurdish breeds, respectively, while based on genomic relationship matrix) FGRM) and correlation between uniting gametes) FUNI) the lowest genomic inbreeding coefficient was found in the Kurdish breed. The estimation of genomic inbreeding rates in the six breeds revealed that FROH yielded lower estimates compared to the other three methods. Additionally, the Iranian breeds displayed lower levels of inbreeding compared to the exotic breeds. Overall, the findings of this study provide valuable insights for the development of effective breeding management strategies aimed at preserving these horse breeds.