Parametric Model Research Articles

Risk equations for prosthetic joint infections (PJIs) in UK: a retrospective study using the Clinical Practice Research Datalink (CPRD) AURUM and GOLD databases

BackgroundProsthetic joint infections (PJIs) are a serious negative outcome of arthroplasty with incidence of about 1%. Risk of PJI could depend on local treatment policies and guidelines; no UK-specific risk...

Prostate cancer diagnosis rates among insured men with and without HIV in South Africa: a cohort study.

Several studies have found lower prostate cancer diagnosis rates among men with HIV (MWH) than men without HIV, but reasons for this finding remain unclear. We used claims data from a South African private medical insurance scheme (07/2017-07/2020) to assess prostate cancer diagnosis rates among men aged ≥18 years with and without HIV. Using flexible parametric survival models, we estimated hazard ratios (HR) for the association between HIV and incident prostate cancer diagnoses. We accounted for potential confounding by age, population group, and sexually transmitted infections (confounder-adjusted model), and additionally for potential mediation by prostatitis diagnoses, prostate-specific antigen (PSA) testing, and prostate biopsies (fully adjusted model). We included 288 194 men, of whom 20 074 (7%) were living with HIV. Prostate cancer was diagnosed in 1 614 men without HIV (median age at diagnosis: 67 years) and in 82 MWH (median age at diagnosis: 60 years). In the unadjusted analysis, prostate cancer diagnosis rates were 35% lower among MWH than men without HIV (HR 0.65, 95% confidence interval [CI] 0.52-0-82). However, this association was no longer evident in the confounder-adjusted model (HR 1.03, 95% CI 0.82-1.30) or in the fully adjusted model (HR 1.14, 95% CI 0.91-1.44). When accounting for potential confounders and mediators, our analysis found no evidence of lower prostate cancer diagnosis rates among men with HIV than men without HIV in South Africa. Our results do not support the hypothesis that HIV decreases the risk of prostate cancer.

Dominant subspaces of high-fidelity polynomial structured parametric dynamical systems and model reduction

In this work, we investigate a model order reduction scheme for high-fidelity nonlinear structured parametric dynamical systems. More specifically, we consider a class of nonlinear dynamical systems whose nonlinear terms are polynomial functions, and the linear part corresponds to a linear structured model, such as second-order, time-delay, or fractional-order systems. Our approach relies on the Volterra series representation of these dynamical systems. Using this representation, we identify the kernels and, thus, the generalized multivariate transfer functions associated with these systems. Consequently, we present results allowing the construction of reduced-order models whose generalized transfer functions interpolate these of the original system at pre-defined frequency points. For efficient calculations, we also need the concept of a symmetric Kronecker product representation of a tensor and derive particular properties of them. Moreover, we propose an algorithm that extracts dominant subspaces from the prescribed interpolation conditions. This allows the construction of reduced-order models that preserve the structure. We also extend these results to parametric systems and a special case (delay in input/output). We demonstrate the efficiency of the proposed method by means of various numerical benchmarks.

Stochastic comparison results between two finite mixture models with generalized Weibull distributed components

In this paper, we establish sufficient conditions for stochastic comparisons of two finite mixture models (FMMs) with respect to the usual stochastic order, hazard rate order, and likelihood ratio order when the mixing components have generalized Weibull family of distributions. The established (sufficient) conditions are mainly based on the majorization order, weak supermajorization order, and weak submajorization order. The stochastic comparisons are studied when there is heterogeneity in one (model) parameter, and then in two parameters (model parameter and mixing proportion). Further, the concept of unordered majorization order is employed to establish the usual stochastic order between two FMMs. To illustrate the theoretical results established here, several numerical examples and counterexamples are presented. Finally, we have generalized some of the results to the case of τ-mixture models.

Parametric modeling and performance assessment of a novel cogeneration system of biomass chemical looping gasification driven by solar energy

Parametric modeling and performance assessment of a novel cogeneration system of biomass chemical looping gasification driven by solar energy

BEARING SURFACE MATERIALS AND THE RISK OF REVISION FOLLOWING PRIMARY TOTAL HIP ARTHROPLASTY: A COHORT ANALYSIS OF 1,026,481 HIP ARTHROPLASTIES FROM THE NATIONAL JOINT REGISTRY

Hip bearing surfaces materials are typically broadly reported in national registry (metal-on-polyethylene, ceramic-on-ceramic etc). We investigated the revision rates of primary total hip replacement (THR) reported in the National Joint Registry (NJR) by detailed types of bearing surfaces used.We analysed THR procedures across all orthopaedic units in England and Wales. Our analyses estimated all-cause and cause-specific revision rates. We identified primary THRs with heads and monobloc cups or modular acetabular component THRs with detailed head and shell/liner bearing material combinations. We used flexible parametric survival models to estimate adjusted hazard ratios (HR).A total of 1,026,481 primary THRs performed between 2003–2019 were included in the primary analysis (Monobloc cups: n=378,979 and Modular cups: n=647,502) with 20,869 (2%) of these primary THRs subsequently undergoing a revision episode (Monobloc: n=7,381 and Modular: n=13,488).Compared to implants with a cobalt chrome head and highly crosslinked polyethylene (HCLPE) cup, the overall risk of revision for monobloc acetabular implant was higher for patients with cobalt chrome or stainless steel head and non-HCLPE cup. The risk of revision was lower for patients with a delta ceramic head and HCLPE cup implant, at any post-operative period.Compared to patients with a cobalt chrome head and HCLPE liner primary THR, the overall risk of revision for modular acetabular implant varied non-constantly. THRs with a delta ceramic or oxidised zirconium head and HCLPE liner had a lower risk of revision throughout the entire post-operative period.The overall and indication-specific risk of prosthesis revision, at different time points following the initial implantation, is reduced for implants with a delta ceramic or oxidised zirconium head and a HCLPE liner/cup in reference to THRs with a cobalt chrome head and HCLPE liner/cup.

Minimizing robust density power-based divergences for general parametric density models

Minimizing robust density power-based divergences for general parametric density models

Abstract PO2-17-11: Management guidelines for epithelial atypia diagnosed in breast screening, based on an analysis of a large prospective cohort study (Sloane Project)

Abstract Background: Epithelial atypia in the breast is most frequently detected through breast screening. Internationally, guidelines differ between advising diagnostic surgical excision of screen-detected atypia versus vacuum-assisted excision (VAE), often with annual follow up surveillance mammography. Prospective data with detailed follow-up and outcomes for subsequent cancer events is lacking. We evaluated a large prospective cohort of screen-detected atypia (Sloane Project) and an expert consensus meeting to develop management recommendations. Methods: We undertook an observational analysis of women with screen-detected epithelial atypia (Atypical Ductal Hyperplasia (ADH), Flat Epithelial Atypia (FEA), Lobular In Situ Neoplasia (LISN), or mixed atypia) reported to the National Health Service (NHS) Breast Screening Programme (BSP) between 01/04/03 and 20/06/18. We estimated cumulative incidence of invasive cancers per 1000 women within 1 and 2 subsequent screening rounds using cumulative incidence functions and repeated these by women’s age, type of atypia and year of diagnosis. Flexible parametric modelling produced hazard ratios (HR). The results were presented at a consensus meeting with clinical experts, patient representation, national decision-makers and commissioners from the NHS in England. A consensus on management recommendations was reached. Results: Among 3238 women (19088 person-years of follow up) with screen-detected atypia, diagnoses increased from 2010 (n=119) to 2015 (n=502). This coincided with the introduction of digital mammography into English screening centres from 2010 and changes in biopsy technique. A total of 141 invasive breast cancers were detected up to December 2018. Cumulative incidence of invasive breast cancer per 1000 women with atypia (ADH, FEA, LISN or mixed) was 14.2 (95% CI 10.3, 19.1) and 45.0 (36.3, 55.1) at 3- and 6-years post atypia based on 40 and 94 cancers, respectively. Women diagnosed with atypia during 2013-2018 had an invasive cancer detected less frequently within 3 years than women with an atypia diagnosis between 2003-2007 or 2008-2012 (6.0 invasive cancers (3.1, 10.9) per 1000 women in 2013-2018 Vs 24.3 (13.7, 40.1) and 24.6 (14.9, 38.3) in 2003-2007 and 2008-2012), suggesting that atypia diagnosis may increasingly contribute to ‘overdiagnosis’. Cancers detected were similar to the general screening population regarding grade, size and nodal involvement. Ipsilateral and contralateral cancers were detected in equal numbers, supporting the concept that atypia represents a risk factor rather than precursor of invasive cancer in the short term. Results by age and type of atypia did not suggest a need for risk-stratified management. Considering subsequent invasive cancer, VAE appeared to be as safe as diagnostic surgical excision of atypia (HR 0.75 (0.45, 1.25)). The expert consensus considered that increased screening of women with screen-detected atypia over and above routine 3-yearly screening was not beneficial, given the overall low numbers of cancers at three years. This applied to all types of atypia and all women who received digital mammography and diagnosis of atypia on core or vacuum-assisted biopsy followed by VAE within a quality assured NHS BSP. Conclusions: Breast atypia represents a risk factor for invasive cancer and does not necessitate surgical excision. Changes to mammography (digital vs plain film) and biopsy techniques (gauge of needle and use of vacuum-assistance) may lead to detection of atypia which is then ‘over-managed’. Current recommendations for annual mammography for 5 years after a diagnosis of epithelial atypia may be overly cautious. We suggest that women with screen detected atypia should be followed up with routine screening appointments. Citation Format: Karoline Freeman, David Jenkinson, Karen Clements, Matthew Wallis, Sarah E Pinder, Elena Provenzano, Hilary Stobart, Nigel Stallard, Olive Kearins, Nisha Sharma, Abeer Shaaban, Cliona Kirwan, Bridget Hilton, Alastair Thompson, Sian Taylor-Phillips. Management guidelines for epithelial atypia diagnosed in breast screening, based on an analysis of a large prospective cohort study (Sloane Project) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-17-11.

The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model

AbstractTransit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO3−) management. However, relying solely on instream NO3− concentration for model calibration can result in poor parameter identifiability. This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO3− concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ18O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT50) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO3− and δ18O time series offer similar information for calibration. However, the absolute values of transport parameters and TT50 time series, as well as the degree of parameter interaction differed. Experiment 1 showed greater interaction between certain transport parameters and denitrification rate, leading to greater equifinality. Conversely, Experiment 3 yielded reduced parameters interaction, which enhanced transport parameters identifiability and decreased uncertainty in TT50 time series. Hence, even a modest effort to incorporate only monthly δ18O values in model calibration for highly frequent NO3−, improved the description of hydrological transport. This study showcased the value of combining NO3− and δ18O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO3− management strategies.

Numerical study of hemodynamic flow in the aortic vessel of Williams syndrome patient with congenital heart disease original article

Congenital arterial stenoses such as supravalvar aortic stenosis (SVAS) are highly prevalent in Williams syndrome (WS) and other arteriopathies pose a substantial health risk. Conventional tools for severity assessment, including clinical findings and pressure gradient estimations, often fall short due to their susceptibility to transient physiological changes and disease stage influences. Moreover, in the pediatric population, the severity of these and other congenital heart defects (CHDs) often restricts the applicability of invasive techniques for obtaining crucial physiological data. Conversely, evaluating CHDs and their progression requires a comprehensive understanding of intracardiac blood flow. Current imaging modalities, such as blood speckle imaging (BSI) and four-dimensional magnetic resonance imaging (4D MRI) face limitations in resolving flow data, especially in cases of elevated flow velocities. To address these challenges, we devised a computational framework employing zero-dimensional (0D) lumped parameter models coupled with patient-specific reconstructed geometries pre- and post-surgical intervention to execute computational fluid dynamic (CFD) simulations. This framework facilitates the analysis and visualization of intricate blood flow patterns, offering insights into geometry and flow dynamics alterations impacting cardiac function. In this study, we aim to assess the efficacy of surgical intervention in correcting an extreme aortic defect in a patient with WS, leading to reductions in wall shear stress (WSS), maximum velocity magnitude, pressure drop, and ultimately a decrease in cardiac workload.

Development and validation of health-oriented personal evaluation for the community-dwelling older person based on the International Classification of Functioning, Disability and Health.

The International Classification of Functioning, Disability and Health (ICF) offers a standardized international terminology to operationalize function management across multiple domains, but the summary score of the ICF qualifier scale provides limited information on the comparison of personal abilities and functioning difficulties. To enhance the interpretative power of the ICF-based Health-oriented Personal Evaluation for the community-dwelling older person (iHOPE-OP) scale through the implementation of the item response theory (IRT) modelling. This cross-sectional, multi-centre study administrated 161 ICF categories (58 on body functions, 15 on body structures, 60 on activities or participation and 28 on environmental factors) to evaluate the functional level of 338 older citizens (female = 158, male = 180) residing in community or supportive living facilities. The validation process encompassed assessing the IRT model fitness and evaluating the psychometric properties of the IRT-derived iHOPE-OP scale. The age of participants ranged from 60 to 94.57, with the mean age of 70. The analysis of non-parametric and parametric models revealed that the three-parameter logistic IRT model, with a dichotomous scoring principle, exhibited the best fit. The 53-item iHOPE-OP scale demonstrated high reliability (Cronbach's α = 0.9729, Guttman's lambda-2 = 0.9749, Molenaar-Sijtsma Statistic = 0.9803, latent class reliability coefficient = 0.9882). There was a good validity between person abilities and the Barthel Index (p < .001, r = .83), as well as instrumental activities of daily living (p < .001, r = .84). IRT methods generate the reliable and valid iHOPE-OP scale with the most discriminable and minimal items to represent the older person's functional performance at a comprehensive level. The use of the Wright map can aid in presby-functioning management by visualizing item difficulties and person abilities. Considering the intricate and heterogeneous health status of older persons, a single functional assessment tool might not fulfil the need to fully understand the multifaceted health status. For use in conjunction with the IRT and ICF framework, the reliable and valid iHOPE-OP scale was developed and can be applied to capture presby-functioning. The Wright map depicts the distribution of item difficulties and person abilities on the same scale that facilitates person-centred goal setting and tailors intervention.

From Scans to Parametric BIM: An Enhanced Framework Using Synthetic Data Augmentation and Parametric Modeling for Highway Bridges

From Scans to Parametric BIM: An Enhanced Framework Using Synthetic Data Augmentation and Parametric Modeling for Highway Bridges

Stochastic ordering in multivariate extremes

AbstractThe article considers the multivariate stochastic orders of upper orthants, lower orthants and positive quadrant dependence (PQD) among simple max-stable distributions and their exponent measures. It is shown for each order that it holds for the max-stable distribution if and only if it holds for the corresponding exponent measure. The finding is non-trivial for upper orthants (and hence PQD order). From dimension $$d\ge 3$$ d ≥ 3 these three orders are not equivalent and a variety of phenomena can occur. However, every simple max-stable distribution PQD-dominates the corresponding independent model and is PQD-dominated by the fully dependent model. Among parametric models the asymmetric Dirichlet family and the Hüsler-Reiß family turn out to be PQD-ordered according to the natural order within their parameter spaces. For the Hüsler-Reiß family this holds true even for the supermodular order.

A metamaterial bone plate for biofixation based on 3D printing technology

Bone plate design and production methods are critical for producing metamaterial bone plates. This study investigated the design and development process of porous structures and metamaterial bone plates for biofixation applications. We designed the porous structures for bone plates using parametric modeling and fused them via the implicit surface fusion method. Likewise, we designed the metamaterial bone plate structure using reverse reconstruction and topological optimization. Thereafter, we utilized three-dimensional (3D) printing for producing and post-processing the metamaterial bone plate. We observed a reduced stress-shielding effect after topological optimization. Additionally, the resultant diamond porous structure maintained a high porosity under pressure. The 3D-printed bone plates and fillers had a bright porous surface, with clear pore structures and good connectivity. The assembly of the 3D-printed femur, bone plate, filler, and standardized screw indicated a good fitting, and the filler could be fixed by the inclined surface. Taken together, the findings of this study established the foundation for the prospective application of metamaterial bone plates in biofixation.

Neural Garment Dynamics via Manifold‐Aware Transformers

AbstractData driven and learning based solutions for modeling dynamic garments have significantly advanced, especially in the context of digital humans. However, existing approaches often focus on modeling garments with respect to a fixed parametric human body model and are limited to garment geometries that were seen during training. In this work, we take a different approach and model the dynamics of a garment by exploiting its local interactions with the underlying human body. Specifically, as the body moves, we detect local garment‐body collisions, which drive the deformation of the garment. At the core of our approach is a mesh‐agnostic garment representation and a manifold‐aware transformer network design, which together enable our method to generalize to unseen garment and body geometries. We evaluate our approach on a wide variety of garment types and motion sequences and provide competitive qualitative and quantitative results with respect to the state of the art.

Information fusion-based maintenance strategies selection for coastal concrete bridges using recycled fishing nets

Repurposing recycled materials for coastal concrete bridge maintenance addresses both engineering requirements and marine ecosystem preservation. This study explored the application of recycled nylon (RN) and polyethylene (PE) from discarded fishing nets in coastal concrete beam maintenance. Specifically, these fibers were incorporated into the polymer cement mortar (PCM) to produce two repair materials. Then, thirteen unrepaired or preventive/post-repaired concrete beams were exposed to the tidal zone for one or two years, followed by beam bending tests and the establishment of the corresponding parametric Finite element modeling (FEM). As an alternative to traditional heavy-parameter models, a novel lightweight crack segmentation model (LiteSqueezeSeg) was proposed for quantitatively analyzing beam surface crack properties. Lastly, experimental, simulated, and quantitative crack information were fused to comprehensively assess the beam performance. Results showed that both PCM-RN and PCM-PE effectively inhibit chloride ion penetration. The proposed LiteSqueezeSeg model (95.66% accuracy) achieved nearly identical performance to Deeplab v3 + but only with about 1/6 parameters. Fused results revealed that PCM-PE repaired beams exhibited superior mechanical performance but inferior ductility compared to PCM-RN. Moreover, both PCM-PE and PCM-RN repaired beams demonstrated that preventive repairs achieved more balanced performance than post repairs. Consequently, utilizing PCM-RN for preventive repair emerged as an optimal candidate. This study significantly contributes to the utilization of waste fishing nets in coastal concrete structure maintenance.

Is lithium from geothermal brines the sustainable solution for Li-ion batteries?

The rising demand for Li, paramount for energy storage, necessitates expanded supply. As the supply is concentrated in a few countries, this poses supply chain risks for Li-ion battery makers. To diversify suppliers, alternative Li ore deposits such as geothermal brines are being explored. However, Li extraction from geothermal brines is challenging due to the unique chemistry and elevated temperatures. Since Li-extraction from geothermal brines is in its infancy, data availability and quality are still poor, hampering life cycle assessments. Hence, this study provides a parametrized life cycle inventory model of Li carbonate production from geothermal brines. The model accounts for site-specific environmental conditions and technological features. Life cycle impacts at the Salton Sea in the US (1686 cases) and the Upper Rhine Graben in Germany (1982 cases) are quantified. The high case numbers are chosen to mitigate the high uncertainties in input parameters. Specifically, the brine chemistry, adsorption yield, drilling required and energy inputs are varied. Climate change impacts of selected cases vary within 18–59 kg CO2eq/kg Li carbonate at the Salton Sea and within 5.3–46 kg CO2eq/kg Li carbonate at the Upper Rhine Graben, compared to 2.1–11 kg CO2eq/kg Li carbonate in existing ecoinvent data sets. The wide range of potential impacts underscore the necessity of early-stage assessments of the technologies. In case of high drilling demand and use of fossil energy, climate change impacts of Li-ion batteries using Li carbonate from geothermal brines can increase by 30–41 % compared to literature values.

Numerical Model Test of Spilled Oil Transport Near the Korean Coasts Using Various Input Parametric Models

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models

BackgroundMetabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation. Hence, we evaluated the genomic prediction of serum biomarkers levels for metabolic distress in 1353 Holsteins genotyped with the 100K single nucleotide polymorphism (SNP) chip assay. The GS was evaluated using parametric models best linear unbiased prediction (GBLUP), Bayesian B (BayesB), elastic net (ENET), and nonparametric models, gradient boosting machine (GBM) and stacking ensemble (Stack), which combines ENET and GBM approaches.ResultsThe results show that the Stack approach outperformed other methods with a relative difference (RD), calculated as an increment in prediction accuracy, of approximately 18.0% compared to GBLUP, 12.6% compared to BayesB, 8.7% compared to ENET, and 4.4% compared to GBM. The highest RD in prediction accuracy between other models with respect to GBLUP was observed for haptoglobin (hapto) from 17.7% for BayesB to 41.2% for Stack; for Zn from 9.8% (BayesB) to 29.3% (Stack); for ceruloplasmin (CuCp) from 9.3% (BayesB) to 27.9% (Stack); for ferric reducing antioxidant power (FRAP) from 8.0% (BayesB) to 40.0% (Stack); and for total protein (PROTt) from 5.7% (BayesB) to 22.9% (Stack). Using a subset of top SNPs (1.5k) selected from the GBM approach improved the accuracy for GBLUP from 1.8 to 76.5%. However, for the other models reductions in prediction accuracy of 4.8% for ENET (average of 10 traits), 5.9% for GBM (average of 21 traits), and 6.6% for Stack (average of 16 traits) were observed.ConclusionsOur results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.

A Multi-objective Optimization of Window and Light Shelf Design in Office Buildings to Improve Occupants’ Thermal and Visual Comfort

In office buildings, an efficient design of windows and using light shelves as a passive design strategy significantly influence the thermal and visual comfort of occupants while enhancing the productivity and health of users. This study proposes a multi-objective optimization for the optimal design of windows and light shelves in office buildings to improve occupants' comfort. Initially, a parametric model was developed using Grasshopper parametric software. Afterward, the Honeybee energy and daylight plugin was employed for simulating thermal and visual conditions, and finally, multi-objective optimization was conducted with the Octopus plugin. This plugin can determine the best solution as a compromise decision for maximizing occupants' comfort. In this paper, an office building in Tehran has been chosen as a case study. The decision variables are window-to-wall ratio (WWR), shading control strategy, viewpoint, the transmission of glass, light shelf length, and light shelf height. The objective functions of the study are the annual average Predicted Percentage of Dissatisfied (PPD) and the annual average Discomfort Glare Probability (DGP). According to the results, the proposed optimization model leads to an 18.5–70.1% and 9.3–57.1% reduction in DGP and PPD indexes, respectively. The study findings provide practical and useful instruction for architects to select optimal specifications of windows and light shelves to develop occupants' thermal and visual comfort in office buildings.