Occupation Distribution Research Articles

Quantum thermalization via multiwave mixing

We discuss thermalization in a multimode quantum cavity under unitary evolution. According to general principles, an isolated system with quadratic couplings does not exhibit thermalization. However, we find that nonlinearities, here three-wave perturbation, typical for instance in superconducting Josephson systems, may lead to thermalization into a Bose-Einstein distribution of occupations of the modes. The temperature of this state is dictated by energy conservation in this closed system, and the thermal distribution is robust against weak disturbances. We discuss how our findings open up new avenues to experimentally probe fundamental assumptions of statistical physics in solid-state systems. Published by the American Physical Society 2024

Cosmological parameters from the joint analysis of density split and second order statistics: An emulator based on the halo occupation distribution

Cosmological parameters from the joint analysis of density split and second order statistics: An emulator based on the halo occupation distribution

Assessment of Patients Applying for Medical Reports at the Family Medicine Clinic

Abstract Objective: Reports are crucial in Family Medicine, but many legal issues remain unresolved. Unnecessary examination requests cause significant costs, labor loss for physicians, and affect occupational safety. This can be prevented by informing institutions and reducing primary care physicians' workload by classifying tasks for workplace physicians to handle follow-ups. This study aims to evaluate the age, gender, and occupational distribution of people applying to the Family Medicine Outpatient Clinic for employment, driver's license, marriage, diaper, and drug reports, and to examine the relationship between the requested examinations and reports. Methods: In this study, the examinations requested according to the age and gender data of the people who applied to the Family Medicine Outpatient Clinic between 01.01.2014-01.01.2015 to obtain employment, health, driver's license, marriage, diaper and drug reports were evaluated by retrospective file screening method.Laboratory reference intervals were determined as the intervals used by the laboratory of our hospital.After all data were collected, they were entered into the SPSS 16.0 (SPSS, Inc., Chicago, Illinois) program and analyzed using this program. Chi-square test was used for comparison of categorical variables. Significance level was accepted as p

Adaptive spatial down-sampling method based on object occupancy distribution for video coding for machines

As the performance of machine vision continues to improve, it is being used in various industrial fields to analyze and generate massive amounts of video data. Although the demand for and consumption of video data by machines has increased significantly, video coding for machines needs to be improved. It is therefore necessary to consider a new codec that differs from conventional codecs based on the human visual system (HVS). Spatial down-sampling plays a critical role in video coding for machines because it reduces the volume of the video data to be processed while maintaining the shape of the data’s features that are important for the machine to reference when processing the video. An effective method of determining the intensity of spatial down-sampling as an efficient coding tool for machines is still in the early stages. Here, we propose a method of determining an optimal scale factor for spatial down-sampling by collecting and analyzing information on the number of objects and the ratio of the area occupied by the object within a picture. We compare the data reduction ratio to the machine accuracy error ratio (DRAER) to evaluate the performance of the proposed method. By applying the proposed method, the DRAER was found to be a maximum of 21.40 dB and a minimum of 11.94 dB. This shows that video coding gain for the machines could be achieved through the proposed method while maintaining the accuracy of machine vision tasks.

A new occupancy index model based on artificial vision for enhancing beach management

This study proposes a new method to more effectively plan the use of beaches by combining indices and artificial vision systems. The Overcrowding Index (Iocr) measures the number of people on the beach in relation to its surface area, while the Distancing Index (Idis) evaluates the spatial distribution and distance between beachgoers. Both indices are combined to generate an overall index called the Occupancy Index (Iocu). The proposed methodology uses cameras and computer vision algorithms such as YOLOX and ByteTrack to automate the counting of people and measure distances. This allows for continuous monitoring of the quantity (carrying capacity and density) and distribution of beachgoers (degree of social distancing), as well as a functional prototype in which the indices are calculated in real time. It was observed that as density increased, Iocr showed an inverse trend, being close to 0 when approaching maximum density. The calculation of the distance between groups validated that, even with medium densities, close to the shoreline, the reference distance of 2 m was not accomplished, obtaining a very low Idis (0.18). The resulting Iocu was 0.31, validating the appropriate integration of both indices. Overall, the system's effectiveness for accurately monitoring the number of users and their distribution, and calculating the defined indices for beach management, is demonstrated. The proposed approach provides a valuable tool, allowing a more efficient management of beaches according to their actual occupancy and user distribution.

A simplified method for calculating air conditioning load of multi-family housing community considering the spatiotemporal distribution of occupants

Occupant behavior is considered a vital factor influencing housing energy consumption by adjusting the indoor thermal environment and the use of service system. Multi-family housing is popular in the hot summer and cold winter (HSCW) zone of China, where residents typically adopt a “partial time, partial space” approach to environmental control. Therefore, the behavioral differences among families pose challenges for predicting hourly energy consumption at community scale. Taking Changsha, a typical city in the HSCW zone, as an example, this study investigates and summarizes the spatiotemporal distribution characteristics of multi-family occupants, analyzing their impact on air conditioning (AC) load under ideal environmental control conditions (i.e., AC is on where is occupied). Hourly AC load modified equations and multi-family occupancy modified coefficients are introduced to construct a method for estimating hourly AC load of residential communities that comprehensively considers the spatiotemporal distribution of multi-family occupants. The results show that the proposed method achieves fitting degrees of 87%-92.4% for predicting heating load and 77.9%-84.9% for predicting cooling load. This method not only dramatically reduces the workload and time required for physical modeling of residential communities, but also enables fast and refined simulation of the hourly AC load.

Heatwaves at work: typology and spatial distributions of occupations exposed to heatwaves in Korea

Heatwaves at work: typology and spatial distributions of occupations exposed to heatwaves in Korea

A multiple-input fluid queue model for performance evaluation of fog server in an intelligent vehicular network

Nowadays, there is a growing trend towards fog computing which is a relatively new concept that has been introduced as an extension of cloud computing. It is considered as a promising paradigm for intelligent vehicular networks due to its ability to reduce delays and enhance network efficiency. The utilization of fog computing plays a crucial role in tackling the distinct obstacles encountered in vehicular computing, including issues like real-time data processing, and limitations on bandwidth. By relocating computational resources closer to the network’s edge, it enhances the effectiveness, dependability, and safety of vehicular applications while simultaneously boosting privacy and security measures. In addition, fog offloading has played a pivotal role in fog computing and edge computing structures. Its objective is to efficaciously allocate the data and assign the processing of tasks among edge devices, fog nodes, and cloud resources. Efficient fog offloading strategies are adaptable, scalable, and are able to handle faults, making them indispensable for optimizing these architectures. Although efficiency and quality of service are crucial objectives in a fog computing based intelligent vehicular network environment, performance remains a significant concern that cannot be overlooked. In light of this, to evaluate the efficacy of the probabilistic offloading approach on a fog server, a thorough performance evaluation is necessary. This research proposes a fluid queue approach that accounts for the constant flow of data packets while evaluating a fog server’s performance. For a fog computing-based intelligent vehicular network (FCIVN) with numerous heterogeneous smart vehicles (SVs), we construct a multiple-input fluid queue to model the tasks handed over to the fog server in order to evaluate its performance. In an FCIVN, the arrivals are drawn from various sources at the fog server. Accordingly, in the proposed model the fluid queue is modulated by more than one independent and distinct finite-state birth–death processes (BDPs) which control the variable inflow, and another BDP which controls the variable outflow. We present the details concerning an intermediate fog server’s buffer occupancy distribution within an FCIVN. Further, we assess the performance measures in terms of the offered load, expected buffer-level, average throughput and average latency of the tasks in an FCIVN. Finally, quantitative illustrations are presented to demonstrate the appropriateness of the fluid queue model developed in this study. The results are found to be in consistence with the expected behaviour of these performance indicators.

Impact of assembly bias on clustering plus weak lensing cosmological analysis

Context. Empirical models of galaxy-halo connection such as the halo occupation distribution (HOD) model have been widely used over the past decades to intensively test perturbative models on quasi-linear scales. However, these models fail to reproduce the galaxygalaxy lensing signal on non-linear scales, over-predicting the observed signal by up to 40%. Aims. With ongoing Stage-IV galaxy surveys such as DESI and Euclid that will measure cosmological parameters at sub-percent precision, it is now crucial to precisely model the galaxy-halo connection in order to accurately estimate the theoretical uncertainties of perturbative models. Methods. This paper compares a standard HOD (based on halo mass only) to an extended HOD that incorporates as additional features galaxy assembly bias and local environmental dependencies on halo occupation. These models were calibrated against the observed clustering and galaxy-galaxy lensing signal of eBOSS luminous red galaxies and emission line galaxies in the range 0.6 < z < 1.1. We performed a combined clustering-lensing cosmological analysis on the simulated galaxy samples of both HODs to quantify the systematic budget of perturbative models. Results. By considering not only the mass of the dark matter halos but also these secondary properties, the extended HOD offers a more comprehensive understanding of the connection between galaxies and their surroundings. In particular, we found that the luminous red galaxies preferentially occupy denser and more anisotropic environments. Our results highlight the importance of considering environmental factors in empirical models with an extended HOD that reproduces the observed signal within 20% on scales below 10 h−1 Mpc. Our cosmological analysis reveals that our perturbative model yields similar constraints regardless of the galaxy population, with a better goodness of fit for the extended HOD. These results suggest that the extended HOD should be used to quantify modelling systematics. This extended framework should also prove useful for forward modelling techniques.

Evolution of HOD and galaxy properties in filaments and nodes of the cosmic web

ABSTRACT We study the evolution of the halo occupation distribution (HOD) and galaxy properties of nodes and filamentary structures obtained by disperse from the Illustris TNG300-1 hydrodynamical simulation, in the redshift range $0 \le z \le 2$. We compute the HOD in filaments and nodes and fit the HOD parameters to study their evolution for both faint and bright galaxies. In nodes, the number of faint galaxies increases with decreasing redshift in the low-mass haloes, while no significant differences are seen in high-mass haloes. Limiting the HOD to bright galaxies shows that haloes increase in mass more than the number of bright galaxies they accrete. For filaments, no large differences in HOD are found for faint galaxies, although for brighter galaxies the behaviour is the same as in nodes. The HOD parametrization suggests that filaments have no effect on the mass required to host a galaxy (central or satellite), whereas nodes do. The results of the study indicate that with this parametrization, filaments do not seem to affect the stellar mass content of galaxies. In contrast, nodes appear to affect haloes with masses below approximately $10^{12.5} h^{-1} {\rm M}_{\odot }$ at local redshift. The analysis of the galaxy colour evolution shows a reddening towards lower redshift, although these processes seem to be more efficient in massive haloes, with a strong effect on bright galaxies. The general evolution suggests that the building of galaxy population within haloes is influenced by both the accretion of faint galaxies and the mass growth of the bright ones.

Overeducation and economic mobility

We assess the hypothesis that declining intergenerational economic mobility in Norway is attributable to a rising signaling value of education accompanied by more overeducation particularly among upper-class offspring. We identify five empirical facts that together point in this direction:• The educational earnings premium has risen, but only through the extensive (employment) margin.• The rising earnings premium is associated with completed degrees only. When educational attainment is measured as time actually invested, the premium has declined.• Both educational attainment and the labor market's skill-requirements (as predicted by the occupational distribution) have increased, but attainment has risen faster than requirements such that the incidence of overeducation has increased.• There is a steep positive social gradient in overeducation: Overeducation is more frequent and has risen faster among offspring in upper-class families.• There is a steep negative social gradient in non-employment: Non-employment is more frequent and has risen faster among offspring in lower-class families.

Experimental Study of the Influence of Occupants on Speech Intelligibility in an Automotive Cabin

Adding occupants to an enclosed space often leads to perceptible changes in the sound field and, therefore, speech intelligibility; however, this issue has not yet been examined in automotive cabins. This study investigated the effect of occupants in an automotive cabin on SI. Binaural room impulse responses (BRIRs) were measured in an automotive cabin with an artificial mouth and dummy head under different speaker–listener position configurations and occupancy modes. Based on the measured BRIRs, the speech transmission index (STI) was determined, and subjective speech–reception thresholds (SRTs) in Mandarin Chinese were assessed. The results indicate that speech intelligibility mostly decreased slightly after adding additional occupants. In most cases, the occupants did not significantly affect speech intelligibility, with STI variations of no more than the just-noticeable difference and SRT variation within 1 dB. When the listener was in the back-right seat, the effect of the occupants on speech intelligibility could not be ignored, with STI variations of up to 0.07 and an SRT variation of 2 dB under different occupancy modes. In addition, the influence of front-row passengers on the speech intelligibility of rear-row listeners was extremely small, and vice versa. Furthermore, altering the distribution of occupants had an effect comparable to changing the number of occupants.

Bounds on galaxy stochasticity from halo occupation distribution modeling

The joint probability distribution of matter overdensity and galaxy counts in cells is a powerful probe of cosmology, and the extent to which variance in galaxy counts at fixed matter density deviates from Poisson shot noise is not fully understood. The lack of informed bounds on this stochasticity is currently the limiting factor in constraining cosmology with the galaxy–matter probability distribution function (PDF). We investigate stochasticity in the conditional distribution of galaxy counts along lines of sight with fixed matter density, and we present a halo occupation distribution (HOD)-based approach for obtaining plausible ranges for stochasticity parameters. To probe the high-dimensional space of possible galaxy–matter connections, we derive a set of HODs that conserve the galaxies’ linear bias and number density to produce REDMAGIC-like galaxy catalogs within the ABACUSSUMMIT suite of N-body simulations. We study the impact of individual HOD parameters and cosmology on stochasticity and perform a Monte Carlo search in HOD parameter space subject to the constraints on bias and density. In mock catalogs generated by the selected HODs, shot noise in galaxy counts spans both sub-Poisson and super-Poisson values, ranging from 80% to 133% of Poisson variance for cells with mean matter density. Nearly all of the derived HODs show a positive relationship between local matter density and stochasticity. For galaxy catalogs with higher stochasticity, modeling galaxy bias to second order is required for an accurate description of the conditional PDF of galaxy counts at fixed matter density. The presence of galaxy assembly bias also substantially extends the range of stochasticity in the super-Poisson direction. This HOD-based approach leverages degrees of freedom in the galaxy–halo connection to obtain informed bounds on nuisance model parameters and can be adapted to study other parametrizations of shot noise in galaxy counts, in particular to motivate prior ranges on stochasticity for cosmological analyses.

Occupant-Detection-Based Individual Control of Four-Way Air Conditioner for Sustainable Building Energy Management

In this study, individual control of a four-way air conditioner was developed based on the distribution of occupants to prevent unnecessary energy consumption during room-wide control. An occupancy detection algorithm was created in Python using YOLOv5 object recognition technology to identify the occupants’ distribution in space. Recorded video data were used to test the algorithm. A simulation case study for a building energy model was conducted, assuming that this algorithm was applied using surveillance cameras in commercial buildings, such as cafés and restaurants. A grey-box model was established based on measurements in a thermal zone, dividing one space into two zones. The temperature data for the two zones were collected by individually turning on the air conditioner for each zone in turns for a specific period. Manual closure was applied to each supply blade using a tape to provide cooling to the target zone. Finally, through energy simulations, the decreased rates in energy consumption between the proposed individual control and existing room-wide controls were compared. Different scenarios for the occupants’ schedules were considered, and average rates in energy savings of 21–22% were observed, demonstrating the significance of individual control in terms of energy consumption. However, marginal comfort violations were observed, which is inevitable. The developed control method is expected to contribute to sustainable energy management in buildings.

Occupation distribution analysis of Co in La-Co substituted M-type hexaferrite and its significant effect on magnetic properties

In recent years, La-Co co-substituted M-type strontium hexaferrite (La-Co SrM) has gained significant attention due to its improved permanent magnet performance and elevated operating temperature. However, the occupation of Co ions within the lattice of La-Co SrM has sparked considerable debate over the past two decades. To address this, neutron powder diffraction and Raman spectroscopy were employed in this study to analyze Co occupancy in La-Co SrM single crystal and polycrystalline samples. Results consistently reveal a preference for most Co ions to occupy the spin-down tetrahedral 4f1 site, which enhances the net magnetic moment and uniaxial magnetic anisotropy. Differences in Co ion distribution between single crystals (octahedral 12k and 2a sites) and polycrystalline powders (bipyramidal 2b sites) are attributed to sample preparation conditions, often overlooked in previous discussions. Therefore, precise regulation of Co occupancy, particularly maximizing the occupation of the 4f1 site, proves pivotal in enhancing magnetic properties.

Metabolic syndrome in personnel of TUMS☆ and its association with types of occupations: A cross-sectional study

BackgroundMetabolic syndrome (MetS) causes an increased risk of cardiovascular disease and death. Hospital staff as an influential segment of the population are at risk of developing MetS. This study aimed to determine the occupational distribution of MetS in hospital staff and to examine the association between the type of occupation and the likelihood of developing MetS. MethodsIn this cross-sectional study we recruited 3128 personnel of TUMS, including healthcare workers, office workers and supportive workers of Tehran's University Teaching Hospitals during 2020–2022. Demographic, anthropometric indices and laboratory tests were recorded. MetS was determined using three definitions including ATP III recommendations, IDF and regional IDF criteria. Statistical analysis was performed using SPSS 26. ResultsMetS was observed in 641 (20.5%) subjects according to ATP III recommendations, 923 (29.5%) based on IDF and 713 (22.8%) using regional IDF criteria. Using regional IDF criteria, age, gender and occupational status were associated with the MetS occurrence (all p < 0.0001). Adjusting for the age and gender of participants, healthcare workers were less likely to develop MetS compared to both office workers (OR = 0.66, 95%CI for OR: 0.55–0.80, p < 0.0001) and supportive workers (OR = 0.72, 95%CI for OR: 0.58–0.90, p = .003). However, office workers and supportive workers did not differ significantly regarding this parameter (p = .44). ConclusionRegardless of the MetS definition criteria, the findings indicated an alarming MetS prevalence, particularly among supportive workers and office workers. Considering the significant role of hospital staff in patients’ health promotion, effective management is essential.

Neutrino Mass Constraint from an Implicit Likelihood Analysis of BOSS Voids

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, ∑m ν , promise to benefit from the inclusion of void statistics. We perform inference on the CMASS Northern Galactic Cap sample of the third-generation Sloan Digital Sky Survey/Baryon Oscillation Spectroscopic Survey (BOSS) with the aim of constraining ∑m ν . We utilize the void size function, the void–galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle-neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of kmax=0.15hMpc−1 and a Planck-inspired Lambda cold dark matter prior, we find upper bounds on ∑m ν of 0.43 and 0.35 eV from the galaxy auto power spectrum and the full data vector, respectively (95% credible interval). Relaxing the scale cut to kmax=0.2hMpc−1 , we find 0.28 and 0.32 eV. Generally, void statistics appear to add modest but nonzero information beyond the auto power spectrum. We also substantiate the usual assumption that the void size function is Poisson distributed.

Heteroatom anchoring to enhance electrochemical reversibility for high-voltage P2-type oxide cathodes of sodium-ion batteries

P2-type cathode has received extensive attention due to its faster Na+ diffusion and a high theoretical capacity in sodium-ion batteries (SIBs). However, undesirable phase transformations have induced dramatic capacity decay of SIBs during the cycling process. In this study, heteroatom anchoring through Cu/Mg dual doping is introduced into P2-type Na0.67Ni0.33Mn0.67O2 cathode to enhance high-voltage electrochemical reversibility and modulate interfacial Na+ kinetics. The as-prepared Na0.67Ni0.23Mg0.05Cu0.05Mn0.67O2 exhibits an outstanding capacity retention (83.4 % after 2000 cycles at 10 C) and rate performance (73 mAh g−1 at 10 C, accounting for 58.7 % of that at 0.1 C) over the voltage range of 2.5–4.4 V. Intensive explorations further manifest that the modified mechanism of dual-ion doping strategy is attributed to the synergistic coupling effect of a substantial change in Na occupancy distribution and an increase in oxygen vacancy buffer. Thus, the optimized cathode expedites Na+ diffusion and reduces detrimental phase transformation, which favors high-rate performance and long-term cycling stability. This study develops a route to rationally design high-voltage cathode materials for SIBs.

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to . We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

The SRG/eROSITA All-Sky Survey

Context. The spatial distribution of galaxy clusters provides a reliable tracer of the large-scale distribution of matter in the Universe. The clustering signal depends on intrinsic cluster properties and cosmological parameters. Aims. The ability of eROSITA on board Spectrum-Roentgen-Gamma (SRG) to discover galaxy clusters allows the association of extended X-ray emission with dark matter haloes to be probed. We measured the projected two-point correlation function to study the occupation of dark matter haloes by clusters and groups detected by the first eROSITA all-sky survey (eRASS1). Methods. We created five volume-limited samples probing clusters with different redshifts and X-ray luminosity values. We interpreted the correlation function with halo occupation distribution (HOD) and halo abundance matching (HAM) models. We simultaneously fit the cosmological parameters and halo bias of a flux-limited sample of 6493 clusters with purity &gt; 96%. Results. We obtained a detailed view of the halo occupation for eRASS1 clusters. The fainter population at low redshift (S0: L̄X = 4.63 × 1043 erg s−1, 0.1 &lt; z &lt; 0.2) is the least biased compared to dark matter, with b = 2.95 ± 0.21. The brightest clusters up to higher redshift (S4: L̄X = 1.77 × 1044 erg s−1, 0.1 &lt; z &lt; 0.6) exhibit a higher bias b = 4.34 ± 0.62. Satellite groups are rare, with a satellite fraction &lt; 14.9% (8.1) for the S0 (S4) sample. We combined the HOD prediction with a HAM procedure to constrain the scaling relation between LX and mass in a new way, and find a scatter of ⟨σLx⟩ = 0.36. We obtain cosmological constraints for the physical cold dark matter density ωc = 0.12−0.02+0.03 and an average halo bias b = 3.63−0.85+1.02. Conclusions. We modelled the clustering of galaxy clusters with a HOD approach for the first time, paving the way for future studies combining eROSITA with 4MOST, SDSS, Euclid, Rubin, and DESI to unravel the cluster distribution in the Universe.