Ceiling-fan-integrated air conditioning: Airflow and temperature characteristics of a sidewall-supply jet interacting with a ceiling fan

Ceiling-Fan-Integrated Air Conditioning (CFIAC) is a proposed system that can greatly increase buildings’ cooling efficiency. In it, terminal supply ducts and diffusers are replaced by vents/nozzles, jetting supply air toward ceiling fans that serve to mix and distribute it within the room. Because of the fans’ air movement, the system provides comfort at higher room temperatures than in conventional commercial/ institutional/retail HVAC. We have experimentally evaluated CFIAC in a test room. This paper covers the distributions of air-speed, temperature, and calculated comfort level throughout the room. Two subsequent papers report tests of human subject comfort and ventilation effectiveness in the same experimental conditions. The room’s supply air emerged from a high-sidewall vent directed toward a ceiling fan on the jet centerline; we also tested this same jet on a fan located off to the side of the jet. Primary variables are: ceiling fan flow volumes in downward and upward directions, supply air volume, and room-vs-supply temperature difference. Velocity, turbulence, and temperature distributions are presented for vertical and horizontal transects of the room. The occupied zone is then evaluated for velocity and temperature non-uniformity, and for comfort as predicted by the ASHRAE Standard 55 elevated air speed method. We show that temperatures are well-mixed and uniform across the room for all of the fan-on configurations, for fans both within or out of the supply jet centerline. The ceiling fan flow dominates the CFIAC airflow, and even though non-uniform is capable of providing comfortable conditions throughout the occupied area of the room

Floquet Weyl semimetal phases in light-irradiated higher-order topological Dirac semimetals

Floquet engineering, the concept of tailoring a system by a periodic drive, is increasingly exploited to design and manipulate topological phases of matter. In this work, we study periodically driven higher-order topological Dirac semimetals associated with a $k$-dependent quantized quadrupole moment by applying circularly polarized light. The undriven Dirac semimetals feature gapless higher-order hinge Fermi arc states which are the consequence of the higher-order topology of the Dirac nodes. Floquet Weyl semimetal phases with hybrid-order topology, characterized by both a $k$-dependent quantized quadrupole moment and a $k$-dependent Chern number, emerge when illumining circularly polarized light. Such Floquet Weyl semimetals support both hinge Fermi arc states and topological surface Fermi arc states. In addition, Floquet Weyl semimetals with tilted Weyl cones in higher-order topological Dirac semimetals are also discussed. Considering numerous higher-order topological Dirac semimetal materials were recently proposed, our findings can be testable soon.Comment: Accepted for publication as a Letter in Phys. Rev.

Adaptive distributed differential evolution

Due to the increasing complexity of optimization problems, distributed differential evolution (DDE) has become a promising approach for global optimization. However, similar to the centralized algorithms, DDE also faces the difficulty of strategies' selection and parameters' setting. To deal with such problems effectively, this article proposes an adaptive DDE (ADDE) to relieve the sensitivity of strategies and parameters. In ADDE, three populations called exploration population, exploitation population, and balance population are co-evolved concurrently by using the master-slave multipopulation distributed framework. Different populations will adaptively choose their suitable mutation strategies based on the evolutionary state estimation to make full use of the feedback information from both individuals and the whole corresponding population. Besides, the historical successful experience and best solution improvement are collected and used to adaptively update the individual parameters (amplification factor F and crossover rate CR) and population parameter (population size N), respectively. The performance of ADDE is evaluated on all 30 widely used benchmark functions from the CEC 2014 test suite and all 22 widely used real-world application problems from the CEC 2011 test suite. The experimental results show that ADDE has great superiority compared with the other state-of-the-art DDE and adaptive differential evolution variants

Influence of lifestyle on suboptimal health: Insights from a national cross-sectional survey in China

Background: Suboptimal health status (SHS) is a non-clinical or pre-disease state between optimal/ideal health and disease. While its etiology remains unclear, lifestyle is considered one of the most important risk factors. We aimed to examine the effects of lifestyles on SHS through a nationwide survey in China. Methods: We conducted a cross-sectional survey in 148 cities across China between 20 June and 31 August 2022, on 30 505 participants from rural and urban communities gathered through stratified quota sampling. We measured SHS with the Short-Form Suboptimal Health Status Questionnaire (SHSQ-SF). We gathered information on participants\u27 lifestyles (ie, smoking, alcohol consumption, breakfast habits, weekly food delivery frequency, intermittent fasting, sleep duration and physical activities) through face-to-face interview. We determined the relationship between lifestyle and SHS logistic regression analysis by based on odds ratios (ORs) and 95% confidence intervals (CIs). Results: We included 22 897 participants (female: 13 056, male: 9841), 12 108 (52.88%) of whom reported exposure to SHS. After adjusting for demographic characteristics, individuals who currently smoked (OR = 1.165; 95% CI = 1.058-1.283) and those who drank alcohol (OR = 1.483; 95% CI = 1.377.1.596) were at a higher risk of SHS than those who have never done either. In a dose-response way, takeaway food consumption was associated with a higher risk of SHS, while increased frequency of breakfast and mild-intensity exercise conversely reduced said risk. Individuals with shorter sleep duration had a higher risk of SHS when compared to those who slept for more than seven hours per day. Conclusions: We observed a relatively high prevalence of SHS across China, highlighting the importance of lifestyle in health promotion. Specifically, adopting healthy dietary habits, engaging in regular physical activity, and ensuring high-quality sleep are key in preventing SHS. Registration: Chinese Clinical Trial Registry (ChiCTR2200061046)

Adaptive granularity learning distributed particle swarm optimization for large-scale optimization

Large-scale optimization has become a significant and challenging research topic in the evolutionary computation (EC) community. Although many improved EC algorithms have been proposed for large-scale optimization, the slow convergence in the huge search space and the trap into local optima among massive suboptima are still the challenges. Targeted to these two issues, this article proposes an adaptive granularity learning distributed particle swarm optimization (AGLDPSO) with the help of machine-learning techniques, including clustering analysis based on locality-sensitive hashing (LSH) and adaptive granularity control based on logistic regression (LR). In AGLDPSO, a master-slave multisubpopulation distributed model is adopted, where the entire population is divided into multiple subpopulations, and these subpopulations are co-evolved. Compared with other large-scale optimization algorithms with single population evolution or centralized mechanism, the multisubpopulation distributed co-evolution mechanism will fully exchange the evolutionary information among different subpopulations to further enhance the population diversity. Furthermore, we propose an adaptive granularity learning strategy (AGLS) based on LSH and LR. The AGLS is helpful to determine an appropriate subpopulation size to control the learning granularity of the distributed subpopulations in different evolutionary states to balance the exploration ability for escaping from massive suboptima and the exploitation ability for converging in the huge search space. The experimental results show that AGLDPSO performs better than or at least comparable with some other state-of-the-art large-scale optimization algorithms, even the winner of the competition on large-scale optimization, on all the 35 benchmark functions from both IEEE Congress on Evolutionary Computation (IEEE CEC2010) and IEEE CEC2013 large-scale optimization test suites

Dietary Intake of Fatty Acids, Total Cholesterol, and Stomach Cancer in a Chinese Population.

To investigate the associations between dietary fatty acids and cholesterol consumption and stomach cancer (SC), we analyzed data from a population-based case-control study with a total of 1900 SC cases and 6532 controls. Dietary data and other risk or protective factors were collected by face-to-face interviews in Jiangsu Province, China, from 2003 to 2010. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multiple unconditional logistic regression models and an energy-adjusted method. The joint associations between dietary factors and known risk factors on SC were examined. We observed positive associations between dietary saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and total cholesterol and the development of SC, comparing the highest versus lowest quarters. Increased intakes of dietary SFAs (p-trend = 0.005; aOR, 1.11; 95% CI, 1.01-1.22 with a 7 g/day increase as a continuous variable) and total cholesterol (p-trend < 0.001; aOR, 1.13; 95% CI, 1.06-1.22 with a 250 mg/day increase as a continuous variable) were monotonically associated with elevated odds of developing SC. Our results indicate that dietary SFAs, MUFAs, and total cholesterol are associated with stomach cancer, which might provide a potential dietary intervention for stomach cancer prevention

Two-Particle Angular Correlations in Heavy Ion Collisions From a Multiphase Transport Model

We extend our earlier study on two-particle angular correlations in $pp$ collisions at low transverse momentum ($p_T$) to $p$-Pb, Pb-Pb and Au-Au collisions at RHIC and LHC energies. We mainly use the string melting version of a multiphase transport model with improved quark coalescence for this study. We start from the analysis of $\pi^{\pm}$, $K^{\pm}$ and $p$($\bar{p}$) $p_T$ and rapidity distributions at different centralities. We then focus on two-particle angular correlations in $p$-Pb collisions at $\mathrm{\sqrt{s_{NN}} = 5.02}$ TeV and Pb-Pb collisions at $\mathrm{\sqrt{s_{NN}}= 2.76}$ TeV. For $p$-Pb collisions, a near side depression in the angular correlation is observed for low $p_T$ proton pairs and $\Lambda$ pairs but not for pion pairs or kaon pairs, similar to our earlier finding for $pp$ collisions at $\mathrm{\sqrt{s}= 7}$ TeV. This is also the case for very low multiplicity Pb-Pb and Au-Au collisions. We also find that parton interactions and the improved quark coalescence are mainly responsible for the depression feature in baryon pair angular correlations. However, no such baryon-baryon anti-correlations are observed in Pb-Pb and Au-Au collisions at higher multiplicities. Therefore our results suggest that low $p_T$ baryon-baryon angular anti-correlations have a strong multiplicity dependence.Comment: 10 pages, 15 figures, submit for publicatio