High-density Environments Research Articles

Healthy Dwelling: The Perspective of Biophilic Design in the Design of the Living Space

As urbanization continues to advance rapidly, the emergence of biophilic design offers a positive perspective to address the alienation between humans and nature, becoming a hot research topic in areas related to human living environments. Biophilic design, as a design concept inspired by nature, has positive significance in promoting the development of ecological diversity and improving human physical and mental health. This paper makes a comparative analysis of two of China’s residential communities in the same high-density environment through the main influencing factors of plot ratio, greening rate, external facades environments, and internal living space. Starting from the five senses of the human body, namely, sight, hearing, touch, smell, and taste, this paper aims to investigate the design of living spaces through the lens of biophilic design, and proposes a biophilic design model, along with strategies and recommendations tailored to high-density urban environments, in the hope of serving as a valuable reference and source of inspiration for future healthy dwelling design.

Galaxy evolution in compact groups – I. Revealing a transitional galaxy population through a multiwavelength approach

ABSTRACT Compact groups (CGs) of galaxies show members with morphological disturbances, mainly products of galaxy–galaxy interactions, thus making them ideal systems to study galaxy evolution, in high-density environment. To understand how this environment affects the properties of galaxies, we select a sample of 340 CGs in the Stripe 82 region, for a total of 1083 galaxies, and a sample of 2281 field galaxies as a control sample. By performing a multiwavelength morphological fitting process using Southern Photometric Local Universe Survey data, we divide our sample into early-type galaxies (ETGs), late-type galaxies (LTGs), and transition galaxies using the r-band Sérsic index and the colour (u − r). We find a bimodal distribution in the plane of the effective radius – Sérsic index, where a secondary ‘peculiar’ galaxy population of smaller and more compact galaxies is found in CGs, which is not observed in the control sample. This indicates that galaxies are undergoing a morphological transformation in CGs. In addition, we find significant statistical differences in the distribution of specific star-formation rate (sSFR) when we compare both environments for LTGs and ETGs. We also find a higher fraction of quenched galaxies and a lower median sSFR in CGs than in the control sample, suggesting the existence of environmental effects favouring the cessation of star formation, regardless of galaxy type. Our results support the notion that CGs promote morphological and physical transformations, highlighting their potential as ideal systems for galaxy pre-processing.

Main Sequence to Starburst Transitioning Galaxies: Gamma-Ray Burst Hosts at z ∼ 2

Star-forming galaxies populate a main sequence (MS), a well-defined relation between stellar mass (M *) and star formation rate (SFR). Starburst (SB) galaxies lie significantly above the relation, whereas quenched galaxies lie below the sequence. In order to study the evolution of galaxies on the SFR–M * plane and its connection to the gas content, we use the fact that recent episodes of star formation can be pinpointed by the existence of gamma-ray bursts (GRBs). Here we present sensitive [C i] nondetections of z ∼ 2 ultraluminous infrared (ULIRG) GRB host galaxies. We find that our GRB hosts have similar molecular masses to those of other ULIRGs. However, unlike other ULIRGs, the GRB hosts are located at the MS or only a factor of a few above it. Hence, our GRB hosts are caught in the transition toward the SB phase. This is further supported by the estimated depletion times, which are similar to those of other transitioning galaxies. The GRB hosts are [C i]-dark galaxies, defined as having a [C i]/CO temperature brightness ratio of <0.1. Such a low [C i]/CO ratio has been found in high-density environments (n H > 104 cm−3) where CO is shielded from photodissociation, leading to underabundances of [C i]. This is consistent with the merger process that is indeed suggested for our GRB hosts by their morphologies.

Metallicity beats sSFR: the connection between superluminous supernova host galaxy environments and the importance of metallicity for their production

ABSTRACT We analyse 33 Type I superluminous supernovae (SLSNe) taken from Zwicky Transient Facility (ZTF)’s Bright Transient Survey to investigate the local environments of their host galaxies. We use a spectroscopic sample of galaxies from the Sloan Digital Sky Survey (SDSS) to determine the large-scale environmental density of the host galaxy. Noting that SLSNe are generally found in galaxies with low stellar masses, high star formation rates (SFRs), and low metallicities, we find that SLSN hosts are also rarely found within high-density environments. Only $3\substack{+9 \\ -1}$ per cent of SLSN hosts were found in regions with two or more bright galaxies within 2 Mpc. For comparison, we generate a sample of 662 SDSS galaxies matched to the photometric properties of the SLSN hosts. This sample is also rarely found within high-density environments, suggesting that galaxies with properties required for SLSN production favour more isolated environments. Furthermore, we select galaxies within the IllustrisTNG simulation to match SLSN host galaxy properties in colour and stellar mass. We find that the fraction of simulated galaxies in high-density environments quantitatively match the observed SLSN hosts only if we restrict to simulated galaxies with metallicity 12 + log (O/H) ≤ 8.12. In contrast, limiting to only the highest specific star formation rate (sSFR) galaxies in the sample leads to an overabundance of SLSN hosts in high-density environments. Thus, our measurement of the environmental density of SLSN host galaxies appears to break the degeneracy between low metallicity and high sSFR as the driver for SLSN hosts and provides evidence that the most constraining factor on SLSN production is low metallicity.

Dark Matter Annihilation inside Large-Volume Neutrino Detectors.

New particles in theories beyond the standard model can manifest as stable relics that interact strongly with visible matter and make up a small fraction of the total dark matter abundance. Such particles represent an interesting physics target since they can evade existing bounds from direct detection due to their rapid thermalization in high-density environments. In this work we point out that their annihilation to visible matter inside large-volume neutrino telescopes can provide a new way to constrain or discover such particles. The signal is the most pronounced for relic masses in the GeV range, and can be efficiently constrained by existing Super-Kamiokande searches for dinucleon annihilation. We also provide an explicit realization of this scenario in the form of secluded dark matter coupled to a dark photon, and we show that the present method implies novel and stringent bounds on the model that are complementary to direct constraints from beam dumps, colliders, and direct detection experiments.

The Impact of High-Density Urban Wind Environments on the Distribution of COVID-19 Based on Machine Learning: A Case Study of Macau

The COVID-19 epidemic has become a global challenge, and the urban wind environment, as an important part of urban spaces, may play a key role in the spread of the virus. Therefore, an in-depth understanding of the impact of urban wind environments on the spread of COVID-19 is of great significance for formulating effective prevention and control strategies. This paper adopts the conditional generative confrontation network (CGAN) method, uses simulated urban wind environment data and COVID-19 distribution data for machine training, and trains a model to predict the distribution probability of COVID-19 under different wind environments. Through the application of this model, the relationship between the urban wind environment and the spread of COVID-19 can be studied in depth. This study found that: (1) there are significant differences in the different types of wind environments and COVID-19, and areas with high building density are more susceptible to COVID-19 hotspots; (2) the distribution of COVID-19 hotspots in building complexes and the characteristics of the building itself are correlated; and (3) similarly, the building area influences the spread of COVID-19. In response to long COVID-19 or residential area planning in the post-epidemic era, three principles can be considered for high-density cities such as Macau: building houses on the northeast side of the mountain; making residential building layouts of “strip” or “rectangular” design; and ensuring that the long side of the building faces southeast (the windward side). (4) It is recommended that the overall wind speed around the building be greater than 2.91 m/s, and the optimal wind speed is between 4.85 and 8.73 m/s. This finding provides valuable information for urban planning and public health departments to help formulate more effective epidemic prevention and control strategies. This study uses machine learning methods to reveal the impact of urban wind environments on the distribution of COVID-19 and provides important insights into urban planning and public health strategy development.

Interference-Aware Deployment for Maximizing User Satisfaction in Multi-UAV Wireless Networks

In this letter, we study the deployment of Unmanned Aerial Vehicle mounted Base Stations (UAV-BSs) in multi-UAV cellular networks. We model the multi-UAV deployment problem as a user satisfaction maximization problem, that is, maximizing the proportion of served ground users (GUs) that meet a given minimum data rate requirement. We propose an interference-aware deployment (IAD) algorithm for serving arbitrarily distributed outdoor GUs. The proposed algorithm can alleviate the problem of overlapping coverage between adjacent UAV-BSs to minimize inter-cell interference. Therefore, reducing co-channel interference between UAV-BSs will improve user satisfaction and ensure that most GUs can achieve the minimum data rate requirement. Simulation results show that our proposed IAD outperforms comparative methods by more than 10% in user satisfaction in high-density environments.

Efficient Clustering of Visible Light Communications in VANET

The deployment of vehicular ad hoc network (VANET) is crucial to the development of autonomous vehicles. Radio frequency (RF) technology has been employed to transmit messages between vehicles and infrastructure in VANET. However, the limited RF bands may cause interference when vehicles transmit messages in a high-density environment. Moreover, when numerous vehicles transmit messages to the infrastructure at the same time, the simultaneous transmissions may cause channel congestion. While the issue of signal interference can be solved by the techniques of Visible Light Communication (VLC), vehicle clustering can be employed to improve the transmission performance of vehicles. VLC is an emerging technology with the advantage of immunity to electromagnetic interference. The technique of vehicle clustering categorizes vehicles into different sets, where each set has a leader for intra-cluster messaging. In this work, we present a clustering algorithm for VANET based on VLC. Our algorithm estimates the positions of vehicles based on their current movements. Then, it selects cluster heads based on the number of neighboring vehicles and generates clusters. We evaluate the performance of our scheme for both urban and highway scenarios. The simulation results show that the proposed algorithm can minimize the number of clusters and improve the transmission data rate for vehicles.

Environments of red nuggets at z ∼ 0.7 from the VIPERS survey

ABSTRACT Red ultra-compact massive galaxies, called red nuggets were formed at high redshifts (z ∼ 2–3). Survivors of red nuggets, known as relics, observed at lower redshifts (z &amp;lt; 2) are believed to remain almost unchanged since their formation. For the first time, we verify the environmental properties of red nuggets at intermediate redshift (0.5 &amp;lt; z &amp;lt; 0.9) using 42 red, massive (log(Mstar/M⊙) ≥ 10.9), and ultra compact (Re &amp;lt; 1.5 kpc) from the VIMOS Public Extragalactic Redshift Survey (VIPERS). We found that the increasing fraction of red galaxies, when moving to denser environments, is driven by the red massive normal-size galaxies. Red nuggets, similarly to red intermediate-mass (10.4 ≲ log (Mstar/M⊙) &amp;lt; 10.9) ultra-compact galaxies, are found in various types of environments, with consistent (within 1σ) fractions across all local densities. Analysis of red nugget stellar ages suggests that relics are preferably found in high-density regions while quiescent red nuggets are overabundant in low-density environments. We speculate that red nuggets have survived to lower redshifts via two channels: i) in low-density environments, where the fraction of red nuggets decreases as time passes due to (very) limited merger activity, ii) in high-density environments, where the number of red nuggets drops at higher redshift due to merger activity and is preserved at lower redshift as the high velocities of clusters prevent them from being cannibalized. Even more, the fraction of red nuggets in clusters may increase due to the addition of red massive normal-size galaxies deprived of their envelopes with cosmic time.

How does the visual environment influence pedestrian physiological stress? Evidence from high-density cities using ambulatory technology and spatial machine learning

Revealing the phased impacts of the visual environment on physiological stress in outdoor environments can facilitate accurate and practical planning strategies towards healthy and sustainable living environments. This study adopted ambulatory sensing to monitor high spatiotemporal physiological stress from skin conductance level (SCL) and analyzed the association between the visual environment and the SCL in high-density environments. The multi-level visual environment was quantified from isovist and street view images. The most influential lags for each visual exposure factor were identified. Furthermore, multiple linear regression (MLR) and geographical random forest (GRF) were established to examine the effects of the lagged visual exposure factors on SCL. Particularly, the GRF can explore spatial nonstationary and complex relationships. The MLR (R2 = 0.466) suggests that exposure to trees, sky, and sign symbols can relieve stress. The GRF with 5 visual exposure factors can explain 87.4% of the spatial variance of SCL. This study confirms the effectiveness of monitoring pedestrians’ stress in high-density cities and the phased and non-instantaneous impacts of the visual environment. The results have practical implications in urban design at both district and site levels for a sustainable and psychologically friendly urban environment.

Feasibility Study of Operation Volume Design Concept for Integration of Aircraft Flying Under Visual Flight Rules Based on Actual Flights

Segregation through operation volumes can enable safe and efficient low altitude airspace usage by various aircraft types, both manned and unmanned. Current traditional aircraft flying under visual flight rules (VFR) are not required to adhere to a strict flight plan and share their flight intentions, but their integration in high-density environment will require better strategic trajectory prediction. This paper proposes VFR trajectory modeling based on mission type and typical flight characteristics. The idea is illustrated with a reconnaissance mission mimicking landmark (highway) tracking to check for post-disaster damages. Results from a flight campaign with an experimental helicopter conducted in 2020 verify the assumptions posed at trajectory modeling and identify the degree of uncertainties necessary to determine the buffers around each trajectory and therefore design operation volumes. The same mission-based trajectory modeling and operation volume design approach can be applied to further missions and vehicles, which makes it transferable to the needs of advanced air mobility as well, especially addressing dense operations.

X-ray transmission effects in a high-density dynamic-dusty plasma environment

X-ray communication (XCOM), which employs modulated X-ray photons as the carrier for signal transmission, is a promising wireless optical technology for space applications, particularly during spacecraft blackout re-entry. Currently, several challenges related to XCOM require solutions, including incomplete transmission attenuation models and a lack of experimental verification of the dynamic-dusty communication effects. This study improved the XCOM transmission characteristics in high-density dynamic-dusty plasma based on a collision model. A dynamic-dusty plasma XCOM was built to verify a modulated X-ray tube and an alkali-metal plasma source. The results show that with an increase in photon energy and flow, the X-ray carrier achieves a higher transmission speed, which is sharper than that of photon energy under the influence of flow. When the average electron density of the dusty plasma is 1012–1013 cm−2, the plasma flow speed is 550–650 m/s, the macro temperature exceeds 1500 K, and the communication demonstration system achieves a stable data rate of 50 kbps at a bit error (BER) of 1.7 × 10−5 with a carrier amplitude and frequency of approximately 20 kV and 4.8 Mcps, respectively. This experiment yielded theoretical and actual values for the development of XCOM technology in space applications during re-entry blackouts.

MmWave Channel Stationarity Analysis of V2X Communications in an Urban Environment

Vehicular communication channels are subject to high non-stationarity mainly characterized by the scatterers' and/or transceivers' high mobility. In this sense, this work presents a characterization of the channel quasi-stationarity regions (QSR) in a V2X generic high-dense urban environment at millimeter wave (mmWave) frequencies (28 GHz). Results are extracted from multiple snapshot simulations by means of a three-dimensional ray-launching (3D-RL) algorithm inducing the continuous mobility of the vehicles on the scene and validated with an experimental campaign of measurements in the real scenario. The average power delay profile (APDP) correlation matrix is used as a descriptor of the channel non-stationarity and the mean correlation is outlined for several thresholds. The obtained QSR results are consistent with the related works reported in the literature. Finally, the effects of these QSR in small- and large-scale parameters are assessed as per threshold considerations.

Spatiotemporal characteristics of Chinese metro-led underground space development: A multiscale analysis driven by big data

Nowadays, the use of metro-led underground spaces (MUS) has become imperative in high-density urban environments. However, a comprehensive and systematic understanding of MUS development patterns in densely-populated countries like China is still lacking. Therefore, this study employed a data-driven spatiotemporal analytical framework based on multisource big data to investigate the development mechanism of Chinese MUSs using a full sample. The multiscale analysis, covering MUS, urban, and regional scales, was conducted to identify the driving forces of MUS development over five temporal stages. The results revealed that the development characteristics of Chinese MUSs varied across different spatiotemporal contexts. At the micro level, the primary driving factors, including density, diversity, distance to transit, and destination accessibility, had a strong explanatory power, which is consistent with the mainstream transit-oriented development (TOD) theory. At the macro level, the main drivers included economic factors, environmental factors, and development scale factors. This study provides new insights for MUS development in high-density regions worldwide, and the obtained regularities could be effectively adopted in the planning and design for MUS.

Research on the Healing Effect Evaluation of Campus’ Small-Scale Courtyard Based on the Method of Semantic Differential and the Perceived Restorative Scale

Many studies have proven that campus green space has healing effects, but there are few evaluation studies on the healing effects of a small-scale courtyard landscape on a high-density campus. This research comprehensively employs the method of semantic differential (SD method) and the perceived restorative scale (PRS) to construct an evaluation framework based on environmental preference and restorative evaluation in order to quantify the healing capability of small-scale campus landscapes. The findings demonstrate the following: (1) Plants close to or higher than human visual height, such as trees or shrubs, will lead to a better healing effect than lawns. An irregular layout of the plants can also bring a more beautiful aesthetic and better light than a monotonous layout, thus more strongly diverting people’s attention from pressure. (2) Users’ preferences for activity space do not depend on the scale of the activity space. (3) “Perceived quality” and “Experienced quality” represent the healing quality of the courtyard in terms of abstract feelings or atmospheres that are difficult to distinguish directly. In addition to expanding and deepening the concept of restorative space elements, this research provides some guidance for the design of healing courtyards in high-density campus environments.

A ship evacuation model considering the interaction between pedestrians based on cellular automata

This paper proposes the CAIE (cellular automata with interaction effect) model to evaluate ship passenger evacuation capability. The CAIE model simulates the interaction between passengers by establishing the friction and repulsive force model between passengers, derives the formula of the desired velocity's effect on the movement ability, reflects the influence of a high-density environment on the movement velocity of personnel, and defines push-crossing behavior rules to simulate opposite-flow movement. The proposed CAIE model is verified by passenger evacuation simulation experiments in single-exit cabins under the condition of opposite passenger traffic. The results demonstrate that the CAIE model has similar passenger movement rules as the social force model in terms of the arching and faster-is-slower phenomena. The results also show that the CAIE model meets the test requirements for the MSC.1/Circ.1533 communication of the advanced evacuation simulation model. Finally, the evacuation simulation analysis is performed on a small polar cruise ship using the CAIE model, Pathfinder software, and Maritime Exodus software. The comparison results indicate that the simulation results of the three models and their distributions of evacuation time are consistent. Therefore, the proposed CAIE model can be used to evaluate the evacuation ability of ships.

Evaporation behavior of liquid microdroplets in atmospheric-pressure nonequilibrium plasma

In recent years, atmospheric-pressure nonequilibrium plasma processing using microdroplets has attracted significant attention. To improve the controllability of this process, an understanding of the evaporation behavior of droplets in plasma is highly desirable. In this study, we examine the evaporation behavior of well-controlled inkjet droplets in atmospheric-pressure nonequilibrium argon plasma through both experiments and modeling. A comparison of the droplet evaporation model based on energy balance considering gas temperature, electron and ion collisions, and recombination reactions with experimental evaporation behavior suggests that droplet evaporation is enhanced in high-density plasma environments with electron and ion densities exceeding 1019 m−3 when compared with that in non-ionized gaseous environments at a gas temperature below 1000 K.

Unifying Tactical Conflict Prevention, Detection, and Resolution Methods in Non-Orthogonal Constrained Urban Airspace

The use of small aircraft for a wide range of missions in urban airspace is expected to increase in the future. In Europe, efforts have been invested into developing a unified system, called U-space, to manage aircraft in dense very-low-level urban airspace. The Metropolis II project aimed to research what degree of centralisation an air traffic management system should use in such airspace. The paper at hand is a follow-up, and investigates improvements that can be brought to the tactical conflict prevention, detection, and resolution module of such a system in order to harmonise these components with an organic high-density U-space environment. The proposed improvements are: the prioritisation of vertical conflict prevention in intersections, the use of intent in detecting and resolving conflicts, and the use of heading-based manoeuvres in open airspace. Results show that the use of intent information in the conflict detection process, as well as the implementation of suitable tactical prevention procedures, can greatly increase airspace safety. Furthermore, the experiments revealed that the effectiveness of conflict resolution algorithms is highly dependent on the airspace rules and structure. This reiterates the potential for increasing the safety and efficiency of operations within constrained airspace if the tactical separation modules are unified with the other components of air traffic management systems for U-space.

High larval densities and high temperatures lead to a stronger immune response in the black soldier fly

Organisms are expected to invest more in their immune function when the risk of disease infection is high. However, induction of a robust immune response is costly and may not be achievable in suboptimal environments. High conspecific density could simultaneously imply high infection risk and a suboptimal environment for many insect species. We focus on the economically important dipteran species (black soldier fly, BSF) that represents the insect order that has been ignored in previous research on density effects on immunity. The experimental part of the study was carried out to evaluate the effect of larval density (three density treatments: 1, 5 and 10 larvae/cm2) and temperature (three thermal treatments: 23, 27 and 30 °C) on the immune function of BSF larvae. The larvae that were reared at high compared to low larval densities and at higher than lower temperatures had significantly higher activity of phenoloxidase, an enzyme that plays an essential role in insect immune function. Sex did not have a significant effect on phenoloxidase activity and prepupal mass, pupal mass and adult mass were not affected by the levels of phenoloxidase activity of fifth instar larvae. In addition, we give an overview of larval density effects on insect immunity and show that density-dependent prophylaxis (stronger immune response in high larval density environments) is indeed common in the results of published case studies. However, cases with no correlation between density and immunity traits were as frequent. Moreover, in more than half of the studies, qualitatively different within-species patterns in different immunity traits were observed. We conclude that BSF larvae exhibit density-dependent prophylaxis, and larvae invest more into their immune system at high larval densities and temperatures than they do at low larval densities and temperatures.

Galaxy pairs inThe Three Hundredsimulations II: studying bound ones and identifying them via machine learning

ABSTRACTUsing the data set of The Three Hundred project, i.e. 324 hydrodynamical resimulations of cluster-sized haloes and the regions of radius 15 ${{h^{-1}\, {\rm Mpc}}}$ around them, we study galaxy pairs in high-density environments. By projecting the galaxies’ 3D coordinates onto a 2D plane, we apply observational techniques to find galaxy pairs. Based on a previous theoretical study on galaxy groups in the same simulations, we are able to classify the observed pairs into ‘true’ or ‘false’, depending on whether they are gravitationally bound or not. We find that the fraction of true pairs (purity) crucially depends on the specific thresholds used to find the pairs, ranging from around 30 to more than 80 per cent in the most restrictive case. Nevertheless, in these very restrictive cases, we see that the completeness of the sample is low, failing to find a significant number of true pairs. Therefore, we train a machine learning algorithm to help us identify these true pairs based on the properties of the galaxies that constitute them. With the aid of the machine learning model trained with a set of properties of all the objects, we show that purity and completeness can be boosted significantly using the default observational thresholds. Furthermore, this machine learning model also reveals the properties that are most important when distinguishing true pairs, mainly the size and mass of the galaxies, their spin parameter, gas content, and shape of their stellar components.