Empirical Relationship Research Articles

Spirituality and workplace performance: a theoretical insight

Purpose The primary objective of the study is to explore and elucidate the relationship between spirituality and workplace performance. This study aims to fill a gap in the existing literature by presenting a theoretical–methodological framework that incorporates various aspects and research propositions, differentiating them based on specific mediating variables. Design/methodology/approach This research uses a systematic literature review methodology, analyzing 95 articles published over 20 years (2002–2022). This approach is designed to collate and synthesize evidence supporting the proposed relationship between spirituality and workplace performance and to understand the nuances of spirituality’s influence on performance. Findings The systematic review reveals recurring mediating constructs and various established theoretical–empirical relationships between spirituality and workplace performance throughout the study period. It highlights the significant role of spirituality in enhancing worker well-being, engagement and productivity. Social implications This study addresses the impacts on societal views of work, employee well-being and organizational culture, especially considering the growing discussions around holistic and spiritually inclusive workplaces. Originality/value This paper introduces originality by presenting a theoretical–methodological framework that emphasizes five distinct research propositions. These propositions, rooted in a comprehensive literature review, provide insights into how spirituality might influence workplace performance through various mediating variables.

The cosmological analysis of X-ray cluster surveys. VI. Inference based on analytically simulated observable diagrams

The number density of galaxy clusters across mass and redshift has been established as a powerful cosmological probe, yielding important information on the matter components of the Universe. Cosmological analyses with galaxy clusters traditionally employ scaling relations, which are empirical relationships between cluster masses and their observable properties. However, many challenges arise from this approach as the scaling relations are highly scattered, maybe ill-calibrated, depend on the cosmology, and contain many nuisance parameters with low physical significance. For this paper, we used a simulation-based inference method utilizing artificial neural networks to optimally extract cosmological information from a shallow X-ray survey, solely using count rates, hardness ratios, and redshifts. This procedure enabled us to conduct likelihood-free inference of cosmological parameters $ m $ and $ To achieve this, we analytically generated several datasets of 70\,000 cluster samples with totally random combinations of cosmological and scaling relation parameters. Each sample in our simulation is represented by its galaxy cluster distribution in a count rate (CR) and hardness ratio (HR) space in multiple redshift bins. We trained convolutional neural networks (CNNs) to retrieve the cosmological parameters from these distributions. We then used neural density estimation (NDE) neural networks to predict the posterior probability distribution of $ m $ and $ given an input galaxy cluster sample. Using the survey area as a proxy for the number of clusters detected for fixed cosmological and astrophysical parameters, and hence of the Poissonian noise, we analyze various survey sizes. The 1 sigma errors of our density estimator on one of the target testing simulations are 1\,000\,deg$^2$, 15.2<!PCT!> for $ m $ and 10.0<!PCT!> for $ and 10\,000\,deg$^2$, 9.6<!PCT!> for $ m $ and 5.6<!PCT!> for $ We also compare our results with a traditional Fisher analysis and explore the effect of an additional constraint on the redshift distribution of the simulated samples. We demonstrate, as a proof of concept, that it is possible to calculate cosmological predictions of $ m $ and $ from a galaxy cluster population without explicitly computing cluster masses and even the scaling relation coefficients, thus avoiding potential biases resulting from such a procedure.

Optimization of sound absorption of recycled Nylon fibrous materials

A semi-empirical model for the assessment and an optimization procedure of the sound absorption coefficient of compressed nonwoven fibrous materials made from recycled Nylon fibers (RNF) is developed. In general, the prediction of the sound absorption properties of materials requires the measurement of non-acoustic parameters by specialized characterization tools that are not always within reach of most laboratories. The objective of the proposed model is to establish empirical relationships between these non-acoustic parameters and the bulk density of RNF materials. These empirical relationships are then substituted into a conventional acoustic model for porous materials, namely, the model of Johnson-Champoux-Allard. The proposed model accurately predicts the sound absorption coefficients of compressed RNF materials based solely on bulk density, thickness, and frequency. This prediction is validated through impedance tube measurements. Moreover, the model is used with a proposed optimization producedure to identify the ideal density and thickness for maximum sound absorption at a specific frequency. Impedance tube measurements on optimized configurations confirm the effectiveness of this optimization process.

Particle transport and deposition in wall-sheared thermal turbulence

We studied the transport and deposition behaviour of point particles in Rayleigh–Bénard convection cells subjected to Couette-type wall shear. Direct numerical simulations (DNSs) are performed for Rayleigh number ( $Ra$ ) in the range $10^{7} \leq Ra \leq ~10^9$ with a fixed Prandtl number $Pr = 0.71$ , while the wall-shear Reynolds number ( $Re_w$ ) is in the range $0 \leq Re_w \leq ~12\,000$ . With the increase of $Re_w$ , the large-scale rolls expanded horizontally, evolving into zonal flow in two-dimensional simulations or streamwise-oriented rolls in three-dimensional simulations. We observed that, for particles with a small Stokes number ( $St$ ), they either circulated within the large-scale rolls when buoyancy dominated or drifted near the walls when shear dominated. For medium $St$ particles, pronounced spatial inhomogeneity and preferential concentration were observed regardless of the prevailing flow state. For large $St$ particles, the turbulent flow structure had a minor influence on the particles’ motion; although clustering still occurred, wall shear had a negligible influence compared with that for medium $St$ particles. We then presented the settling curves to quantify the particle deposition ratio on the walls. Our DNS results aligned well with previous theoretical predictions, which state that small $St$ particles settle with an exponential deposition ratio and large $St$ particles settle with a linear deposition ratio. For medium $St$ particles, where complex particle–turbulence interaction emerges, we developed a new model describing the settling process with an initial linear stage followed by a nonlinear stage. Unknown parameters in our model can be determined either by fitting the settling curves or using empirical relations. Compared with DNS results, our model also accurately predicts the average residence time across a wide range of $St$ for various $Re_w$ .

BSN: The First Photometric Analysis of Contact Binary Systems V1961 Cyg and V0890 Lyr

Abstract We presented the first photometric analysis of the V1961 Cyg and V0890 Lyr binary systems. We observed and analyzed these systems at an observatory in France as part of the Binary Systems of South and North (BSN) Project. We extracted and collected the times of minima from the observations and literature and presented a new ephemeris for each system. Due to the few observations about these systems over the years, both O-C diagrams were fitted linearly. The PHysics Of Eclipsing BinariEs (PHOEBE) Python code and the Markov Chain Monte Carlo (MCMC) method were used to light curve solutions. The light curve solution required a cold starspot on the hotter component in the V1961 Cyg binary system. We compared and have close agreements between our mass ratios' results from the light curve analysis processes and a new method based on the light curve derivative. We estimated the absolute parameters using an empirical relationship between the semi-major axis and orbital period for contact binary systems. The results show that V1961 Cyg and V0890 Lyr are W-type contact binary systems. We displayed stars and systems' positions in the $M-L$, $M-R$, and $logM_{tot}-logJ_0$ diagrams. We also presented a new relationship between mass ratio and luminosity ratio.

Sea surface temperature error under tropical cyclone in the western North Pacific.

Tropical cyclone forecasting relies on accurate sea surface temperature, yet the errors in available sea surface temperature products remain unclear. Here, I evaluate the sea surface temperature errors under tropical cyclones in the western North Pacific based on surface drifters across eight widely-used datasets, including satellite, atmospheric and oceanic analysis-or-reanalysis products, spanning from 2014 to 2023. The ensemble mean bias and root-mean-squared-error are firstly quantified. Both satellite and oceanic analysis sea surface temperatures exhibit a cold bias, while atmospheric analysis-or-reanalysis sea surface temperature shows a warm bias. Specifically, atmospheric analysis-or-reanalysis products consistently show a warm bias in the right-rear quadrant of the tropical cyclone coordinate system. Regarding root-mean-squared-error, for most products, the right side consistently exhibits higher errors than the left side. SST bias significantly impacts tropical cyclone intensity change as indicated by empirical relationship. These results provide direct insights for operational tropical cyclone forecasting and research.

Coda-derived source properties estimated using local earthquakes in the Sea of Marmara, Türkiye

Abstract. Accurate estimates of the moment magnitude of earthquakes that physically measure the earthquake source energy are crucial for improving our understanding of seismic hazard in regions prone to tectonic activity. To address this demand, a method involving coda wave modelling was employed to estimate the moment magnitudes of earthquakes in the Sea of Marmara, northwestern Türkiye. This approach enabled us to model the source displacement spectrum of 303 local earthquakes efficiently recorded at 49 regional seismic stations between 2018 and 2020 in the region. The coda wave traces of individual events were inverted across 12 frequency ranges between 0.3 and 16 Hz. The resultant coda-derived moment magnitudes were found to be in good accordance with the conventional local magnitude estimates. However, the notable move-out between local magnitude and coda-derived moment magnitude estimates for smaller earthquakes less than a magnitude of 3.5 likely occurs due to potential biases arising from incorrect assumptions for anelastic attenuation and/or the finite sampling intervals of seismic recordings. Scaling relations between the total radiated energy and seismic moment imply a non-self-similar behaviour for the earthquakes in the Sea of Marmara. Our findings suggest that larger earthquakes in the study area exhibit distinct rupture dynamics compared to smaller ones, resulting in a more efficient release of seismic energy. Hence, we introduce an empirical relationship obtained from the scatter between local magnitude and coda-derived moment magnitude estimates.

Easy yield mapping for precision agriculture

ABSTRACT Within precision agriculture, yield mapping is important in the evaluation of crop management and delineation of management zones. It can also be used to assess within-field yield potential, in order to guide different precision agriculture practices. However, some farmers do not have a yield monitoring system, and some who do may obtain incomplete or erroneous yield data. This study examined the accuracy with which winter wheat (Triticum aestivum L.) yield could be mapped in 18 fields in southern Sweden using a simple empirical relationship between Sentinel-2 (ESA, Paris, France) data, vegetation index (VI) maps and combined harvester data collected in nearby fields. The results showed that a decrease in map resolution to 40 m reduced the error in the yield maps obtained. Normalised difference water index (NDWI) was the most efficient VI, while a combination of satellite data from earlier and later plant development (booting and milk development stages) performed slightly better than data for other development stages and combinations. The best-performing model at a within-field scale (40-m resolution) had an average mean absolute error (MAE) of 0.40 tonnes ha−1 in a leave-one-field-out cross validation. When the prediction model at field-means scale was applied on 69 farms in a 1055 km2 area, MAE was 0.75 tonnes ha−1 when comparing predictions with mean yields reported by farmers in a phone survey. Therefore, if adequate combined harvester and/or mean yield data are available, a modelling framework that translates satellite imagery into yield maps on-the-fly could be made available for different stakeholders via decision support systems for precision agriculture.

Examining the Energy-Growth Dynamics in Saudi Arabia: Insights and Policy Implications

The empirical relationship between energy consumption and economic growth is complex and varies by country and model specification. This study focuses on Saudi Arabia, one of the largest producers and exporters of crude oil, to explore this relationship. Our analysis refutes the Energy-Kuznets Curve hypothesis for Saudi Arabia, finding neither a linear nor a curvilinear relationship between economic growth and energy consumption. Instead, we observe an asymmetric impact of economic growth on energy consumption: the rate of increase in energy consumption with rising per capita income differs from the rate of decrease when per capita income falls. Additionally, the study reveals a positive impact of investment on energy consumption, indicating a dynamic interplay between economic growth, industrial activity, and improved energy access. These findings suggest that energy consumption patterns in Saudi Arabia are intricately linked to economic fluctuations but are not uniformly predictable. Policy recommendations are provided to address these complexities and promote sustainable growth.

Modeling Nonspherical Hailstones

Abstract Hail research and forecasting models necessarily involve explicit or implicit—and uncertain—physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer. Whereas most models assume spherical hailstones, we relax this assumption by using hailstone shape data from field observations to establish empirical size–shape relationships with reasonable degrees of randomness considering hailstones’ natural shape variability, capturing the observed distribution of triaxial ellipsoidal shapes. We also incorporate explicit, random tumbling of individual hailstones during their growth to simulate their free-falling behavior and the resultant changes in cross-sectional area (which affects growth by hydrometeor collection). These physical attributes are incorporated in calculating hailstones’ fall speeds, using either empirical relationships or analytical relationships based on each hailstone’s Best and Reynolds numbers. Options for drag coefficient modification are added to emulate hailstones’ rough surfaces (lobes), which then modifies their thermal energy and vapor exchange with the environment. We investigate how applying these physical assumptions about nonspherical hail to the Penn State hail growth trajectory model, coupled with Cloud Model 1 supercell simulations, impacts hail production and examine the reasons behind the resulting variability in hail statistics. The choice of hailstone size–mass relation and fall speed scheme have the strongest influence on hail sizes. Using nonspherical, tumbling hailstones reduces the number of large hailstones produced. Applying shape-specific thermal energy transfer coefficients subtly increases sizes; the effects of lobes vary depending on the fall speed scheme used. These physical assumptions, although adding complexity to modeling, can be parameterized efficiently and potentially used in microphysics schemes. Significance Statement In numerical modeling of hailstorms, we usually consider hailstones to be spherical to simplify calculations, but in nature, hailstones generally are not spheres and can be rather lumpy and have spikes. The purpose of this study is to examine how the model result would change when nonspherical hailstone shape is implemented. We examine the relationship between hailstone shape and physical processes during hail growth in effort to explain why these changes occur and offer insights on how nonspherical hailstone shape may be parameterized in bulk microphysics schemes.

Photothermal AFM-IR Depth Sensitivity: An Original Pathway to Tomographic Reconstruction.

Photothermal atomic force microscopy-infrared (AFM-IR) enables label-free chemical imaging and spectroscopy with nanometer-scale spatial resolution through the integration of atomic force microscopy (AFM) and infrared radiation. The capability for subsurface and three-dimensional (3D) tomographic material analysis remains, however, largely unexplored. Here, we establish a simple and robust empirical relationship between the probing depth and laser repetition rate for three important modes of AFM-IR operation: resonance-enhanced, tapping, and surface-sensitive AFM-IR. Using this empirical relationship, we demonstrate, based on the example of resonance-enhanced operation, how photothermal AFM-IR of thin surface/subsurface layers of polystyrene domains in the poly(methyl methacrylate) matrix can result in 3D representations revealing the size and thickness of small polystyrene domains in the poly(methyl methacrylate) matrix with nanometer-scale resolution. Experimental findings are confirmed by analytical models.

Fast Radio Bursts as Standard Candles for Cosmology

Recently, fast radio bursts (FRBs) have become a thriving field in astronomy and cosmology. Due to their extragalactic and cosmological origin, they are useful to study the cosmic expansion and the intergalactic medium (IGM). In the literature, the dispersion measure (DM) of FRB has been considered extensively. It could be used as an indirect proxy of the luminosity distance dL of FRB. The observed DM contains the contributions from the Milky Way (MW), the MW halo, IGM, and the host galaxy. Unfortunately, IGM and the host galaxy of FRB are poorly known to date, and hence the large uncertainties of DMIGM and DMhost in DM plague the FRB cosmology. Could we avoid DM in studying cosmology? Could we instead consider the luminosity distance dL directly in the FRB cosmology? We are interested to find a way out for this problem in the present work. From the lessons of calibrating type Ia supernovae (SNIa) or long gamma-ray bursts (GRBs) as standard candles, we consider a universal subclassification scheme for FRBs, and there are some empirical relations for them. In the present work, we propose to calibrate type Ib FRBs as standard candles by using a tight empirical relation without DM. The calibrated type Ib FRBs at high redshifts can be used like SNIa to constrain the cosmological models. We also test the key factors affecting the calibration and the cosmological constraints. Notice that the results are speculative, since they are based on simulations for the future (instead of now). We stress that the point in the present work is just to propose a viable method and a workable pipeline using type Ib FRBs as standard candles for cosmology in the future.

Interface compatibility and hysteresis in shape memory materials are affected by lattice distortions from applied stresses

Significant effort has been put into designing shape-memory materials that can survive many cycles without functional or structural fatigue. A component of the design process is the condition defining perfect interface compatibility between the austenite and martensite lattices (λ2=1). In this paper, we evaluate the traditional mathematical theories of martensite under applied stresses, which distort the lattice compatibility through elastic strains. In NiTi we find that elastic distortions resulting from applied stresses influence the interface compatibility to a degree of impacting the material's functional abilities. Combining our results with empirical relationships connecting interface compatibility to transformation hysteresis we show that the model matches reasonably to a number of experimental results in the literature in which hysteresis changes under applied loads. We also apply these theories to a shape-memory ceramic (zirconia), which suggests a large orientation-dependence and asymmetric behavior in tension and compression. In both systems, we find that variant selection plays a large role in whether interface compatibility will improve or worsen under stress.

Charge radii of 11−16C, 13−17N and 15−18O determined from their charge-changing cross-sections and the mirror-difference charge radii

Charge-changing cross-sections (CCCSs) of 11−16C, 13−17N and 15−18O on a carbon target have been determined at energies around 300 MeV/nucleon. A nucleon separation energy-dependent correction factor has been introduced to the Glauber model calculation for extracting the nuclear charge radii from the experimental CCCSs. The charge radii of 11C, 13,16N and 15O thus were determined for the first time. With the new radii, we studied the experimental mirror-difference charge radii (ΔRchmirror) of 11B-11C, 13C-13N, 15N-15O, 17N-17Ne pairs for the first time. We find that the ΔRchmirror values of 13C-13N and 15N-15O pairs follow well the empirical relation to the isospin asymmetry predicted by the abinitio calculations, while ΔRchmirror of 11B-11C and 17N-17Ne pairs deviate from such relation by more than two standard deviations.

How Long Will the Quasar UV/Optical Flickering Be Damped? II. The Observational Test

The characteristic timescale at which the variability of active galactic nuclei (AGNs) turns from red noise to white noise can probe the accretion physics around supermassive black holes (SMBHs). A number of works have studied the characteristic timescale of quasars and obtained quite different scaling relations between the timescale and quasar physical properties. One possible reason for the discrepancies is that the characteristic timescale can be easily underestimated if the light curves are not long enough. In this work, we construct well-defined AGN samples to observationally test the relationships between the characteristic timescale and AGN properties obtained by previous works. Our samples eliminate the effects of insufficient light-curve lengths. We confirm that the timescale predictions of the Corona Heated Accretion disk Reprocessing model are consistent with our timescale measurements. The timescale predictions by empirical relations are systematically smaller than our measured ones. Our results provide further evidence that AGN variability is driven by thermal fluctuations in SMBH accretion disks. Future flagship time-domain surveys can critically test our conclusions and reveal the physical nature of AGN variability.

OPTIMIZATION OF HEAT TREATMENT REGIME FOR A NEW BIODEGRADABLE Mg-Zr-Nd ALLOY WITH ENHANCED MECHANICAL PROPERTIES

Purpose. To develop a rational heat treatment regime for a new biodegradable magnesium alloy of the Mg-Zr-Nd system, to ensure enhanced mechanical properties throughout the entire treatment period. Research methods. Differential thermal analysis (DTA) was used to determine phase transformation temperatures. Microstructure analysis was conducted using optical microscopy (“Neophot 32” and “OLYMPUS IX 70”) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SELMI RЕМ-106I). Mechanical properties were determined using an INSTRON 2801 testing machine. The influence of cooling rate on microstructure and properties was studied using ProCAST simulation software. Heat treatment was carried out in a Bellevue type shaft furnace and a PAP-4M furnace. X-ray analysis was used to detect internal defects in samples. Results. A new heat treatment regime was developed for the biodegradable Mg-3.15Nd-1.25Zr-0.6Zn (wt%) alloy. Using differential thermal analysis and microstructure studies at various quenching temperatures, the optimal quenching temperature was established at 560 °C. Empirical relationships describing the influence of heat treatment parameters on the alloy's microstructure were calculated. The new heat treatment regime (quenching from 560 °C for 8 hours, air cooling + aging at 200 °C for 16 hours) resulted in improved mechanical properties (UTS = 276–282 MPa, δ = 5.2–5.8%) compared to the standard T6 regime. Scientific novelty. For the first time, a comprehensive study of the influence of heat treatment parameters on the structure and properties of a new Mg-3.15Nd-1.25Zr-0.6Zn (wt%) alloy with increased content of alloying elements was conducted. New dependencies describing the influence of quenching temperature on the alloy's grain size were established. Practical value. A new heat treatment regime for the biodegradable magnesium alloy was developed, which ensures complete dissolution of the pseudoeutectic phase and formation of strengthening phases, resulting in improved mechanical properties compared to the standard alloy Mg-2.5Nd-0.4Zn-0.5Zr (wt%) and the standard T6 regime.

Converging profile relationships for offshore wind speed and turbulence intensity

Abstract. This paper reduces uncertainty in the quantification of offshore wind speed and turbulence intensity. A range of industry standard relationships, including those from International Electrotechnical Commission (IEC) and International Organization for Standardization (ISO), are compared with an extensive set of met mast data collected offshore northwestern Europe over recent decades. Analysis initially focused on over 1000 independent storm peak events identified within the 10 min mean wind speed data. Time series and coherent vertical profiles were subjected to detailed scrutiny and analysis, considering wind speeds at various averaging periods, turbulence intensity and gust factors. Most peak events were associated with neutral atmospheric conditions, so they were well represented by the ISO Frøya profile, with a shear close to the IEC power law exponent of α= 0.11. A new pragmatic approximation of atmospheric stability in terms of relative shear is outlined, bringing together key elements of the IEC and ISO standards. New empirical relationships to quantify offshore wind ambient turbulence intensity are described. A simple generalised form of gust factor relationship is adopted, with a coefficient that varies with averaging period. Distinct recommendations are made for estimating peak 10 min mean winds from peaks in 1 or 3 h mean winds. Finally, a simplified workflow for the estimation of extreme offshore winds is used to show how IEC and ISO relationships can be effectively combined.

X-ray observations of Blueberry galaxies

Context. Compact star-forming galaxies were dominant galaxy types in the early Universe. Blueberry galaxies (BBs) represent their local analogues, being very compact and having intense star formation. Aims. Motivated by high X-ray emission recently found in other analogical dwarf galaxies, called Green Peas, we probed the X-ray properties of BBs to determine if their X-ray emission is consistent with the empirical laws for star-forming galaxies. Methods. We performed the first X-ray observations of a small sample of BBs with the XMM-Newton satellite. Spectral analysis for detected sources and upper limits measured via Bayesian-based analysis for very low-count measurements were used to determine the X-ray properties of our galaxy sample. Results. Clear detection was obtained for only two sources, with one source exhibiting an enhanced X-ray luminosity to the scaling relations. For the remaining five sources, only an upper limit was constrained, suggesting BBs to be rather underluminous as a whole. Our analysis shows that the large scatter cannot be easily explained by the stochasticity effects. While the bright source is above (and inconsistent with) the expected distribution at almost the 99% confidence level, the upper limits of the two sources are below the expected distribution. Conclusions. These results indicate that the empirical relations between the star formation rate, metallicity, and X-ray luminosity might not hold for BBs with uniquely high specific star formation rates. One possible explanation could be that the BBs may not be old enough to have a significant X-ray binary population. The high luminosity of the only bright source can then be caused by an additional X-ray source, such as a hidden active galactic nucleus or more extreme ultraluminous X-ray sources.

The Health-Employment-Longevity Nexus: Implications for Retirement Age Policies in European Countries

Abstract Background Advances in medical knowledge and technology have led to increased general and healthy life expectancy in Europe. Combined with declining fertility rates, these trends have resulted in an aging population. Many European countries have been reluctant to adjust the retirement age, putting pension funds and Pay-As-You-Go social insurance systems at risk. Linking entitlement age to life expectancy could mitigate this risk and extend working life, but such policies are politically unpopular. This study investigates the empirical relationship among self-perceived health, employment, job quality, and life expectancy in the European context. Methods The study analyzes the determinants of self-rated health using the SHARE database, combined with general and healthy life-expectancy data from EUROSTAT and, where missing, the WHO, focusing on European countries. Results In Europe, both past and present employment improve self-rated health. Job quality has a detrimental effect on self-rated health for women and a positive effect on men. Life expectancy and healthy life expectancy raise self-rated health, while poverty rates negatively affect it. Job quality is widespread among European women, and its negative effect on health rises with age. For European men, job quality has a positive effect, peaking around age 56. The effects of employment and job quality on self-rated health are simultaneous. In European countries with an elasticity >1, healthy life expectancy rises faster than general life expectancy at higher ages, suggesting an improved ability to work at older ages. This finding indicates that adjusting the retirement age could be a powerful tool for improving the sustainability of social insurance systems in Europe. Conclusions For younger European women, it may be rational to set higher retirement-age increments and put them on a declining course as they age, considering the gender-specific age dynamics and job quality effects on health. Key messages • In Europe, employment and job quality significantly influence self-rated health, with gender-specific effects that vary with age and impact retirement age policies. • Adjusting retirement age in line with healthy life expectancy could improve the sustainability of European social insurance systems, considering health-employment dynamics.

Numerical experiment on data assimilation for geothermal doublets using production data and electromagnetic observations

The data assimilation process for geothermal reservoirs often relies on well data, which primarily offer insights into the immediate vicinity of the borehole. However, integrating geophysical methods can provide valuable information beyond well proximity, possibly enhancing reservoir predictions. Current methods of monitoring geothermal reservoirs struggle to maintain a good signal-to-noise ratio for deep reservoirs. Diffusive electromagnetic (EM) methods can be sensitive to the decreasing conductivity from heat extraction in geothermal reservoirs and offer promising additional value. To test their potential effectiveness, numerical examples are simulated. A scheme to incorporate diffusive EM observations into a data assimilation process for geothermal reservoirs is presented and implemented in this study. First, an ensemble of prior models representing the reservoir uncertainty is used to determine the moments of the resulting temperature field using a forward geothermal simulation. Subsequently, a conductivity model is calculated from the temperature field using an empirical relationship. The expected electric field response can then be simulated using an EM forward model. EM sources are placed on the surface around the expected cold plume location. The receiver is placed at reservoir depth. To assimilate the data, the ensemble smoother with multiple data assimilation method is used. The findings demonstrate that the incorporation of EM data provides valuable information regarding the temperature field. This improves the accuracy of the temperature forecast of the entire reservoir when combined with the localized data from the production well and, therefore, helps to resolve the complex migration of the cold front. These results highlight the monitoring potential of EM observations for geothermal reservoirs.