Heterogeneous Parameters Research Articles

Neuromodulatory control of complex adaptive dynamics in the brain.

How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a diverse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons-in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked examples, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.

Analysis of Homogeneous/Heterogeneous Reactions in an Electrohydrodynamic Environment Utilizing the Second Law.

In this study, we investigate what happens to entropy in the presence of electrokinetic phenomena. It is speculated that the microchannel has an asymmetrical and slanted configuration. The presence of fluid friction, mixed convection, Joule heating, presence and absence of homogeneity, and a magnetic field are modelled mathematically. It is also emphasized that the diffusion factors of the autocatalyst and the reactants are equal. The governing flow equations are linearized using the Debye-Huckel and lubrication assumptions. The resulting nonlinear couple differential equations are solved using the program's integrated numerical solver, Mathematica. We take a graphical look at the results of homogeneous and heterogeneous reactions and talk about what we see. It has been demonstrated that homogeneous and heterogeneous reaction parameters affect concentration distribution f in different ways. The Eyring-Powell fluid parameters B1 and B2 display an opposite relation with the velocity, temperature, entropy generation number, and Bejan number. The mass Grashof number, the Joule heating parameter, and the viscous dissipation parameter all contribute to the overall increase in fluid temperature and entropy.

Consistency Analysis of Drivers’ Car-Following Behaviors

Car-following models are calibrated to account for various driver behaviors such as speed and space headway. Because drivers do not all drive the same way, they are typically classified based on their level, or profile, of aggressiveness. This approach to model calibration assumes that a single set of car-following parameters applies to an individual driver consistently, that is, during the entire driving period a study considers. The purpose of this research is to challenge that assumption by analyzing the heterogeneity and inconsistency of driver behaviors in different traffic conditions. A total of 3,262 urban expressway car-following periods from 51 drivers were extracted from the Shanghai Naturalistic Driving Study database. The intelligent driver model (IDM) was selected as this study’s car-following model for its favorable performance in highly dynamic situations; its parameters, that is, desired speed, desired time headway, maximum acceleration, comfortable deceleration, acceleration exponent, and minimum spacing, were calibrated. To reflect the effect of traffic conditions, the car-following periods were categorized into three regimes from low-speed to high-speed. Two-way analysis of variance was used to evaluate heterogeneity and inconsistency in the car-following parameters. The findings of this study show that (1) the main significant variable that distinguished driver profile was desired time headway, while the comfortable acceleration was commonly affected by both driver profile and speed regime; (2) variability of individual driver parameter estimates greatly depended on the traffic regime (low-, medium-, and high-speed), showing that driver behavior was highly influenced by traffic conditions; and (3) speed information was demonstrated to be a useful tool by which to divide car-following periods for modeling, as the car-following parameters exhibited distinct differences among the regimes in the varied traffic environment.

A benchmark study of different numerical methods for predicting rock failure

Nowadays, with many available numerical methods developed in rock mechanics, researchers have always focused on the parameter calibration of the numerical model but ignored the predictive capability of these methods. A comparative study of nine commonly used numerical methods was performed for predicting rock failure through international cooperation organized by the Discontinuous Deformation Analysis (DDA) commission of the International Society for Rock Mechanics (ISRM). Two steps of numerical modelling were conducted including a calibration procedure from given experimental results and a numerical prediction for benchmark tests with these calibrated parameters for three types of rocks. Through the comparison between different numerical and experimental results, the inherent weaknesses and strengths of different numerical methods in terms of predicting rock failure were identified and analysed. The influence of human intervention in terms of parameter selection is even more significant than the choice of different numerical methods. Some potential factors (i.e., different boundary conditions, heterogeneity of rock material, strength parameters, particle packing, and failure criteria) that may occur in numerical and physical tests were further discussed. Through the comparison of different failure criteria, we found the selection of rock failure criterion might be the major factor that affected the predictive capability of numerical methods, and the nonlinear failure model (the Hoek–Brown criterion) showed the superiority in the prediction of rock fracturing subjected to complex stress conditions. This comparative work also enlightens the significance of a high-quality calibration process and the future advancement of rock failure criteria.

Instrumental variable estimation with first-stage heterogeneity

We propose a simple data-driven procedure that exploits heterogeneity in the first-stage correlation between an instrument and an endogenous variable to improve the asymptotic mean squared error (MSE) of instrumental variable estimators. We show that the resulting gains in asymptotic MSE can be quite large in settings where there is substantial heterogeneity in the first-stage parameters. We also show that a naive procedure used in some applied work, which consists of selecting the composition of the sample based on the value of the first-stage t-statistic, may cause substantial over-rejection of a null hypothesis on a second-stage parameter. We apply the methods to study (1) the return to schooling using the minimum school leaving age as the exogenous instrument and (2) the effect of local economic conditions on voter turnout using energy supply shocks as the source of identification.

Water quality variation in the middle route of South-to-North Water Diversion Project, China

The South-to-North Water Division Middle Route Project (MRP) is currently the longest inter-basin water diversion project in the world. It benefits a large population and its water quality has attracted much attention. In this study, seasonal investigations on 11 sampling sites along the MRP were conducted from 2018 to 2019; water temperature, pH, turbidity, transparency, CODMn, dissolved oxygen, total phosphorus, phosphate, total nitrogen, ammonia, nitrate, and chlorophyll a were determined synchronously. Single leakage distance clustering analysis identified the spatio-seasonal heterogeneity of physiochemical parameters. The trophic level index (TLI) and the water quality status were assessed: TLI increased and WQI decreased from south to north; TLI and WQI had seasonal differences (p < 0.001), the best water quality was observed in autumn, and the lowest TLI was observed in winter. The trophic level was “oligotrophic to mesotrophic”; water quality status was “good.” The multiple linear stepwise regression analysis confirmed that total nitrogen (TN), Chl a, and CODMn were the driving factors in water quality. These factors were applied to build the simplified WQI model, which was confirmed as a reliable method of water quality assessment for the MRP and a fitting substitute for TLI and WQI. The results provided support for the water quality evaluation of the MRP.

Method Selection for Analyzing the Mesopore Structure of Shale—Using a Combination of Multifractal Theory and Low-Pressure Gas Adsorption

Nitrogen adsorption experiments have been extensively applied to shale pore structure research and evaluation. The pore structure can be quantitatively characterized in accordance with the nitrogen adsorption–desorption isotherm using various calculation models, whereas the results obtained using different models can more effectively indicate the pore characteristics of shale remains unclear. Further, there has not been any unified process in the optimization of calculation models for pore size distribution (PSD). In this study, the Barret–Joyner–Halenda adsorption (BJH-AD) and BJH desorption (BJH-DE) models were used with Longmaxi Formation shale as an example. Subsequently, the density functional theory (DFT) calculations were conducted on different shale lithofacies samples. Next, the pore structure parameters and heterogeneity obtained using different models were compared, and the consistency parameters of different models were obtained in accordance with Cronbach’s alpha. The results indicated that the pore structure parameters obtained using the BJH-AD model were underestimated since the macroscopic thermodynamic theory was not applicable to this study. The DFT model showed multiple peaks in the range of 1–10 nm, whereas the BJH-DE model had a significant artificial peak in the range of 3.8 nm due to the tensile strength effect, thus suggesting that the DFT model is more capable of characterizing the pores with a pore size 10 nm lower than the BJH model. The PSD curves generated using the three models exhibited multifractal characteristics, whereas the results of the heterogeneity achieved using different models were different. Moreover, the consistency of the results of different models can be studied in depth by combining Cronbach’s alpha with various heterogeneity parameters. The DFT model exhibited high consistency in pore structure parameters and pore heterogeneity, thus suggesting that the DFT method of N2 is the optimal physical adsorption data analysis method in the shale mesoporous range. Accordingly, the nitrogen adsorption curve, the hysteresis loop shape, multifractal parameters, and Cronbach’s alpha were integrated to generate a working flow chart of the nitrogen adsorption model for N2-adsorption-model optimization.

MRL ordering of largest order statistics from heterogeneous scale variables

ABSTRACT For comparing largest order statistics from independent heterogeneous non-negative scale variables in the mean residual life order, a new framework is introduced here. This framework can be viewed as a generalization of the well-known multiple-outlier scale model, and it additionally includes the situation in which all the random variables are heterogeneous. We also find some sufficient conditions for comparing the largest order statistics, one with complete heterogeneous scale parameters and another with homogeneous scale parameters, in the mean residual life order. As examples of the obtained results, generalized gamma, generalized beta of the second kind, power-generalized Weibull, and half-normal distributions are all presented. The findings of this work generalize and also reinforce some of the existing results in this direction.

A Systematic Review Assessing Patient-Related Predictors of Response to Transcranial Magnetic Stimulation in Major Depressive Disorder.

The safety and efficacy of transcranial magnetic stimulation (TMS) in the acute treatment of major depressive disorder (MDD) is well established. However, it is not well understood which patient-related factors are associated with a more robust antidepressant response. Identifying predictive factors for therapeutic response to TMS treatment in depression will guide clinicians in patient selection. By systematic review of clinical trial data, the current study aims to identify and analyze reported patient-specific predictors of response to an acute course of TMS treatment for MDD. PubMed was searched for randomized controlled trials of TMS for patients with depression. Studies were appraised for risk of bias using components recommended by the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. TMS data were available from 375 studies, 18 of which were included in this review. Treatment response is inversely associated with treatment refractoriness and age. Inadequate sample size and large heterogeneity in study parameters among clinical trials limit any strong conclusions from being drawn; nonetheless, despite these limitations, there is mounting evidence, which points to age and treatment refractoriness as candidate variables for predicting clinical outcome. Implications of these findings for treatment of MDD are discussed.

Transcranial magnetic stimulation as a new therapeutical approach in autism spectrum disorders and attention deficit hyperactivity disorder – a review

Introduction and aim. Autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD) neurobiology reveals a complex picture of altered excitation-inhibition balance, aberrant neuronal and neurotransmitter activity, and network disorganization that could be addressed through repetitive transcranial magnetic stimulation (TMS). In this paper, we provide a narrative review of the most recent literature on the use of TMS to treat patients with ASD and ADHD. Material and methods. Literature search from 2018 up to November 2022 has been conducted on PubMed database. Keywords reflected diagnoses and treatment modalities of interest. Analysis of the literature. Eleven clinical trials regarding the use of TMS as a therapeutic tool in ASD, and seven studies (of which 3 are case reports) for ADHD have been reported. The dorsolateral prefrontal cortex (DLPFC) is the most frequent area stimulated. Heterogeneity in stimulation parameters, patient age, and outcome measures limited the interpretation of findings. Conclusion. TMS as a therapeutic tool for neurodevelopmental disorders is still in its infancy. To define the real efficacy of TMS, future studies must be randomized, sham-controlled, and double-blind, and should include a larger sample with adequate inclusion/exclusion criteria, and longitudinal follow-up.

Self-construal, face concerns and conflict management strategies: a meta-analysis

PurposeIn this meta-analysis, the authors investigate the relationship between self-construal and conflict management strategies and shed light on the inconsistent findings in the literature. Moreover, they examine the mediating role of face concerns in this relationship. Importantly, the present meta-analysis is the first to test the assumptions of face-negotiation theory with the meta-analytic structural equation modeling (MASEM), which enabled the authors to test the hypothesized relationships in one single model.Design/methodology/approachThe authors used the method of MASEM to test the relationship between self-construal and conflict management and assess the mediating role of face concerns. In this regard, the authors employed one-stage meta-analytic structural equation modeling to perform MASEM and its moderators.FindingsTwo hundred fifty-four effect sizes based on thirty-three studies were pooled in this meta-analysis. The authors found that individuals with stronger independent self-construal and stronger self-face concerns were more likely to use forcing. Moreover, the relationship between independent self-construal and forcing was mediated by self-face concerns. Individuals with a stronger interdependent self-construal and individuals with stronger other-face concerns were more likely to use problem-solving and yielding. The relationship between interdependent self-construal and problem-solving and yielding was mediated by other-face concerns. Finally, interdependent self-construal also had an indirect effect, via other-face concern, on avoiding and compromising.Originality/valueThe present meta-analysis is the first effort that the authors are aware of to test the assumptions of face-negotiation theory (FNT) using MASEM method. The authors used one-stage meta-analytic structural equation modeling viewed as the state of the methods to perform MASEM and its moderators. They employed full information meta-analytic structural equation modeling to show the generalizability and heterogeneity of structural equation modeling parameters. They applied studentized deleted residuals to assess outlier analysis and also conducted different methods to perform MASEM to check the robustness of the findings resulted. Finally, the current study adds multiple methods of assessing for publication bias.

How does fiscal decentralization lead to renewable energy transition and a sustainable environment? Evidence from highly decentralized economies

Effective fiscal management ensures the coordination of taxes and spending authority for attaining inclusive and sustainable growth. Therefore, this study intends to estimate the direct and indirect channels of expenditure, revenue, and composite fiscal decentralization on carbon emissions through renewable energy transition in highly decentralized countries. It employs a cross-sectional augmented auto-regressive distributed Lag (CS-ARDL) method, allowing dependencies across countries and heterogeneity in the slope parameters. In the long run, the direct effects of expenditure (revenue) decentralization on carbon emissions are significantly positive (negative) with coefficient magnitudes of 0.16% and 0.04% (0.09% and 0.08%). The indirect effects of expenditure and revenue decentralization are substantially negative through renewable energy consumption with the coefficient magnitude of 0.135% and 0.138%, respectively. In contrast, composite decentralization and its interactive terms with renewable energy show an emissions-mitigating effect of 0.179% and 0.192%, respectively. These outcomes exhibit that the down-delegation of financial authority (revenue or composite) at local government increases resource efficiency and leads to higher renewable energy consumption. Similar results are echoed in the short run; however, the magnitude of coefficients is significantly higher in the long run. The overall findings provide fascinating policy recommendations.

Deep prostate-specific antigen response and overall survival in patients with metastatic castration-sensitive prostate cancer: A systematic review and meta-analysis.

195 Background: Preliminary data suggests that patients with metastatic castration-sensitive prostate cancer (mCSPC) who achieve deep prostate-specific antigen (PSA) response may have improved survival. This finding may have implications for developing treatment de-escalation strategies. Thus, we assessed the overall survival by deep PSA response in mCSPC patients receiving intensified treatments. Methods: MEDLINE and EMBASE were systematically searched from each database’s inception through 1st October 2022. Trials assessing androgen deprivation therapy intensification (doublets, triplets) and reporting overall survival (OS) by deep PSA response were considered eligible for inclusion. Deep PSA response was defined as the PSA level of less than 0.1 or 0.2 ng/ml within eight months after initiation of intensified treatment. Precomputed effect estimates of OS (deep PSA response vs no deep PSA response) were pooled using an inverse-variance approach after logarithmic transformation; a random-effects meta-analysis was conducted within the Bayesian framework using empirical informative priors for heterogeneity parameter as specified by Turner et al. Summary effect was expressed as hazard ratios (HR) with the corresponding 95% credible intervals (CrI). A sensitivity analysis was conducted using the Der Simonian-Lairds random-effects meta-analysis with Hartung-Knapp (HK) adjustment. Results: Five RCTs (PEACE-1, ARASENS, CHAARTED, LATITUDE, TITAN) with 2533 patients were included in this systematic review. A total of 1335 patients experienced a deep PSA response, while 1218 did not achieve a deep PSA response after the initiation of intensified treatment. The pooled incidence of deep PSA response was 49.45% (95% confidence interval: 37.75-61.18). Bayesian meta-analysis showed significantly improved OS in overall mCSPC patient population who achieved a deep PSA response after intensified treatment with either triplet or doublet therapy as compared to those who did not achieve a deep PSA response (HR: 0.39; 95% CI: 0.30-0.50) as shown. The results were consistent with HK adjustment. Conclusions: Excellent overall survival in patients with deep PSA response may offer an opportunity to guide treatment de-escalation trials in carefully selected mCSPC patients. [Table: see text]

Predictive and prognostic potential of pretreatment 68Ga-PSMA PET tumor heterogeneity index in patients with metastatic castration-resistant prostate cancer (mCRPC).

200 Background: 177Lu-PSMA therapy has been introduced as an effective therapeutic option for metastatic castration resistant prostate cancer (mCRPC). Since about one third of the treated patients show no biochemical response (BCR) after therapy, prediction of treatment outcome is important for patient selection. Therefore, this study was conducted to evaluate to the predictive values of volumetric parameters and radiomic features (RFs) extracted form pretreatment 68Ga-PSMA PET and baseline clinical parameters in response to 177Lu-PSMA therapy. Methods: In this multicenter study, mCRPC patients undergoing 177Lu-PSMA therapy were enrolled from September 2017 to January 2022. The available clinical data of all patients was collected and documented from three different centers. The patients underwent several cycles of therapy. According to the outcome of therapy, the patients were classified into two groups including positive BCR (≥ 50% reduction in the serum PSA value) and negative BCR (< 50%). Sixty-five RFs, eight volumetric parameters and also seventeen clinical parameters were evaluated for prediction of BCR. In addition, the impact of such parameters on overall survival (OS) was evaluated. Results: In this retrospective study, 33 prostate cancer patients with a median age of 69 years (range: 49-89) were enrolled. BCR was observed in 22 cases (66%), and 16 cases (48.5%) died during the follow-up time. The results of Spearman correlation test indicated a significant relationship between BCR and treatment cycle, administered dose, HISTO energy, GLCM entropy, and GLZLM LZLGE (p<0.05). In addition, according to the Mann-Whitney U test, age, cycle, dose, GLCM entropy, and GLZLM LZLGE were significantly different between BCR and non BCR patients (p<0.05). According to the ROC curve analysis for feature selection for prediction of BCR, GLCM entropy, age, treatment cycle, and administered dose showed acceptable results (p<0.05). According to SVM for the assessing of the best model for predication of response to therapy, GLCM entropy alone showed the highest predictive performance in treatment planning. For the entire cohort, the Kaplan-Meier test revealed a median OS of 21 months (95% CI: 12.12-29.88). The median OS was estimated at 26 months (95% CI: 17.43-34.56) for BCR patients and 13 months (95% CI: 9.18-16.81) for non BCR patients. Among all variables included in the Kaplan Meier, only response to therapy was statistically significant (p=0.01) and none of the RFs and other clinical factors achieved a p-value of less than 0.05. Conclusions: This exploratory study showed that heterogeneity parameter of pretreatment 68Ga-PSMA PET images might be a potential predictive value for response to 177Lu-PSMA therapy in mCRPC; however, further prospective studies need to be carried out to verify these findings.

SNAPenrollment cycles: New insights from heterogeneous panel models withcross‐sectionaldependence

AbstractThe Supplemental Nutrition Assistance Program (SNAP) has grown rapidly over the past 2 decades. A large literature relies on state‐level panel data on SNAP enrollment and implements traditional two‐way fixed effects estimators to identify the impact of economic conditions on SNAP enrollment. This empirical strategy implicitly assumes slope parameter homogeneity and ignores the possibility of cross‐sectional dependence in the regression error terms. The latter could feasibly arise in state‐level panel data if the time‐varying unobserved common shocks, such as national financial crises, have differential effects on SNAP participation across states in the United States. This study empirically evaluates the appropriateness of these two assumptions by adopting a more general common factor model, allowing for slope parameter heterogeneity and error term cross‐sectional dependence both separately and jointly. We find that although assuming a common slope parameter across states does not seem problematic for identification, allowing for the error term cross‐sectional dependence leads to a roughly 40% reduction in the estimated long‐run impact of the unemployment rate on SNAP enrollment. This finding has important implications for policymaking decisions—even small biases could lead to suboptimal policy responses considering the program's size. Our counterfactual simulations support our main results, implying the importance of carefully accounting for time‐varying unobserved heterogeneity when studying the cyclicality of SNAP enrollment using state‐level panel data.

The influence of facemasks on communication in healthcare settings: a systematic review

Purpose Although a well-established aspect of healthcare practice, the impact of facemasks on verbal communication is surprisingly ambiguous. Materials and Methods A systematic search was conducted in APA PSYCHinfo, CINAHL, NHS Knowledge Network, Medline and SPORTDiscus databases from inception to November 2022 according to the PRISMA guidelines. Studies reporting an objective measure of speech understanding in adults, where information was transmitted or received whilst wearing a facemask were included. Risk of bias of included studies was assessed with the Newcastle-Ottawa score. Results Four hundred and thirty-three studies were identified, of which fifteen were suitable for inclusion, incorporating 350 participants with a median age of 49 (range 19 to 74) years. Wide heterogeneity of test parameters and outcome measurement prohibited pooling of data. 93% (14 of 15) studies reported a deleterious effect of facemasks on speech understanding, and 100% (5 of 5) of the included studies reported attenuation of sound with facemask usage. Background noise added further deleterious effects on speech understanding which was particularly problematic within hearing-impaired populations. Risk of bias in included studies varied but overall was modest. Conclusions Despite considerable complexity and heterogeneity in outcome measure, 93% (14 of 15) articles suggest respiratory protective equipment negatively affects speech understanding in normal hearing and hearing-impaired adults.

Comparison of travel-time and geostatistical inversion approaches for hydraulic tomography: Synthetic modeling study on data density and well configuration issues

Hydraulic tomography (HT) has been proven to be an effective approach in mapping the heterogeneity of hydraulic parameters. The travel-time based inversion (TTI) and geostatistical inversion (GI) approaches are two of several interpretation methods for HT data. In particular, GI is used to estimate heterogeneous hydraulic conductivity (K) and specific storage (Ss) tomograms, while TTI yields the diffusivity (D = K/Ss) tomogram. The main objective of this paper is to compare the performances of these two methods through a synthetic study. Two cases are designed based on different monitoring configurations. In each case, two independent scenarios are designed as: (1) providing the same dataset, and (2) providing datasets based on recommended strategies for each inversion approach. Then, the estimated tomograms are evaluated by direct comparison of estimated parameter distributions and assessment of model validation results. Comparison results show that the advantages of TTI are: (1) imaging of structural features representing high-D zones; and (2) requirement of less data for inverse modeling. In contrast, the advantages of GI are: (1) estimation of parameters throughout the simulation domain; (2) better characterization of low-D zones; and (3) generating the best estimated tomogram leading to best drawdown predictions. Collectively, our study suggests that TTI is suitable for rapid, coarse characterization of heterogeneity that could be utilized for providing hydrogeological structures for GI as an initial model. GI is more robust and preferable to applications that require higher accuracy in parameter estimation over a larger volume.

Distributed and Asynchronous Population-Based Optimization Applied to the Optimal Design of Fuzzy Controllers

Designing a controller is typically an iterative process during which engineers must assess the performance of a design through time-consuming simulations; this becomes even more burdensome when using a population-based metaheuristic that evaluates every member of the population. Distributed algorithms can mitigate this issue, but these come with their own challenges. This is why, in this work, we propose a distributed and asynchronous bio-inspired algorithm to execute the simulations in parallel, using a multi-population multi-algorithmic approach. Following a cloud-native pattern, isolated populations interact asynchronously using a distributed message queue, which avoids idle cycles when waiting for other nodes to synchronize. The proposed algorithm can mix different metaheuristics, one for each population, first because it is possible and second because it can help keep total diversity high. To validate the speedup benefit of our proposal, we optimize the membership functions of a fuzzy controller for the trajectory tracking of a mobile autonomous robot using distributed versions of genetic algorithms, particle swarm optimization, and a mixed-metaheuristic configuration. We compare sequential versus distributed implementations and demonstrate the benefits of mixing the populations with distinct metaheuristics. We also propose a simple migration strategy that delivers satisfactory results. Moreover, we compare homogeneous and heterogenous configurations for the populations’ parameters. The results show that even when we use random heterogeneous parameter configuration in the distributed populations, we obtain an error similar to that in other work while significantly reducing the execution time.

Quantitative Evaluation of the Effects of Input Parameter Heterogeneity on Model Behavior for Bonded Block Models of Laboratory Rock Specimens

Quantitative Evaluation of the Effects of Input Parameter Heterogeneity on Model Behavior for Bonded Block Models of Laboratory Rock Specimens

Implications of lower indoor temperatures – Not cool for cold susceptible individuals across both sexes

Wider temperature ranges in buildings can reduce building energy use and prevent shortage of energy availability. However, humans do not perceive temperature equally and a general lowering of indoor temperature may in particular impact susceptible individuals. The discrepancy between individuals has been ascribed to sex differences, but is not well understood and could relate to heterogeneity in endogenous heat production or other personal parameters. We, therefore, evaluated individual thermal responses including physiological measurements of metabolic heat production in both men and women, identified, and via experiments, verified as cold sensitive or cold resilient. On average, the cold sensitive group had an 18 % lower resting metabolic rate compared to the cold resilient group when controlling for clothing and other important parameters for heat exchange. We observed a 0.9 °C difference in neutral temperature between sexes, but no difference in thermal perception or skin temperature. We concluded that cold susceptibility is not simply a matter of perception, but relates to a measurable difference in endogenous heat production. Currently mandated temperature setpoints at workplaces or recommended household temperatures do therefore not seem to discriminate between sexes as a result of sex-related differences in physiology, but they might have negative implications for cold sensitive individuals.