Search

Despite emerging recognition of the benefits of green and blue spaces on human health, evidence for their effect modifications on heat-mortality associations is limited. We aimed to investigate the effect modifications of green and blue spaces on heat-mortality associations among different age and sex groups and at different heat levels.Daily mortality and meteorological data from 2008 to 2017 in Hong Kong, China were collected. The Normalized Difference Vegetation Index and distance to coast were used as proxies for green and blue space exposure, respectively. Time-series analyses was performed using fitting generalized linear mixed models with an interaction term between heat and levels of exposure to either green or blue space. Age-, sex-, and heat level-stratified analyses were also conducted.With a 1 °C increase in temperature above the 90th percentile (29.61 °C), mortality increased by 5.7% (95% confidence interval [CI]: 1.6, 10.1%), 5.4% (1.4, 9.5%), and 4.6% (0.8, 8.9%) for low, medium and high levels of green space exposure, respectively, and by 7.5% (3.9, 11.2%) and 3.5% (0.3, 6.8%) for low and high levels of blue space exposure, respectively. Significant effect modifications of green and blue spaces were not observed for the whole population or any specific age and sex group, either at a moderate heat level or a heat level (Ps0.05).No significant effect modifications of green and blue spaces on heat-related mortality risk were observed in Hong Kong. These findings challenge the existing evidence on the prominent protective role of green and blue spaces in mitigating heat-related mortality risks.

Many scholars have advocated for the use of empirical evidence to assess resilience across scales and over time. Accordingly, we conduct a case study using survey data on individual perceptions of disaster relief that were gathered each month from August to December 2015, shortly after the 2015 Nepal earthquake. We construct a scale-specific resilience index (SSRI) based on a set of variables that are validated separately at different spatial scales and over time against the survey data. The regression results show that the variables related to household structure, industrial diversity, community capital, and accessibility and emergency services are validated against the survey data at both the district and sub-district levels, the variables related to ethnic diversity and the capacity of emergency camps are validated only at the district level, and the earthquake experiences variable is validated only at the sub-district level. Consequently, to achieve optimal models, we use six validated variables to construct an SSRI at the district level and seven variables, including those related to the vulnerability of household property and the average elevation, to construct an SSRI at the sub-district level. The SSRI scores are validated via multilevel regression models against the surveyed relief scores after the 2015 Nepal earthquake. The results show that the SSRI scores based on the validated variables correlate favorably and as expected against the survey data at both district and sub-district levels, and outperform the composite resilience index, which considers all of the variables regardless of their individual validation results. The method used to construct the SSRI helps to identify the contributions of multidimensional resilience indicators across spatial scales and over time in real cases, and also provides index scores of scale-specific resilience that are easily understood and applicable to multi-scale decision-making processes.

Transportation planners often need to justify transportation related investments to public officials. Besides efficiency measures, the environment protection and sustainability are gaining more and more importance. In order to improve freight flow efficiency in a sustainable way, it is necessary to have a systematic tool to study the freight flow over all three major surface modes and their connections and, in turn, to help public officials identify the best way to improve freight transportation. We built a system-level intermodal simulation model that includes highways, railways, and waterways because all three modes, working together, play significant roles in freight flows. We evaluated the performance of the Louisiana freight network under different scenarios and measured the benefits of mode changes evaluating the tradeoff between environmental goals and other performance measures.

Extreme heat is a leading cause of weather-related human mortality throughout much of the world, posing a significantly heavy burden on the development of healthy and sustainable cities. To effectively reduce heat health risk, a better understanding of where and what risk factors should be targeted for intervention is necessary. However, little research has examined how different risk factors for heat-related mortality operate at varying spatial scales. Here, we present a novel application of the multiscale geographically weighted regression (GWR) approach to explore the scale of effect of each underlying risk factor using Hong Kong as a case study. We find that a hybrid of global and local processes via multiscale GWR yields a better fit of heat-related mortality risk than models using GWR and ordinary least squares (OLS) approaches. Predictor variables are categorized by the scale of effect into global variables (i.e., age and education attainment, socioeconomic status), intermediate variables (i.e., work place, birth place and language), and local variables (i.e., thermal environment, low income). These findings enrich our understanding of the spatial scale-dependent risk factors for heat-related mortality and shed light on the importance of hierarchical policy-making and site-specific planning processes in effective heat hazard mitigation and climate adaptation strategies.

Build a simple model for improving the maintenance efficiency of electric multiple units in Chinese high-speed rails.The solution method yields the optimal track utilization in a small amount of computational time.A case is presented to show the real application of the method and discuss the difference caused by the track layout. The Chinese high-speed rail network has a fast-growing number of electric multiple units (EMU) in service and is facing increasing pressure of maintaining all EMUs on-time. The capacity at an EMU maintenance depot is relevant to its track utilization rate, which can be improved by a better EMU-to-track assignment in various areas, such as the maintenance yard, temporary storage yard, and washing yard. Most tracks at EMU depots have two sections that can accommodate one long EMU of sixteen railcars or two short EMUs of eight railcars. The two yard types, stub-end and through, further add complexity to the assignment problem, which is currently handled manually. To make the assignment process more efficient, this paper proposes a simple optimization model for yards with either type and with any combination of long and short EMUs. The numerical results based on a real-world case show that the proposed solution method can yield an assignment plan with the optimal track utilization in a small amount of computational time and can be implemented in a computer-aided planning system easily. The case also discusses potential changes in practice to improve the track utilization rate, such as changing the maintenance schedule and connecting two short EMUs into a long EMU. After comparing the track utilization rates between the two yard types, the paper suggests that the through type is more appropriate for the current schedule at EMU depots, especially for the maintenance yard.

Due to the high self-interference from the transmitter, the deployment of the full-duplex system is still far from trivial. The digital self-interference cancellation (DSIC) is the main means of dealing with self-interference. The performance of the typical DSIC is constrained by the elimination capacity of the nonlinear distortion. Based on the characteristic of the nonlinear signal caused by power amplifiers, memory polynomial can portray it properly. Encouraged by this characteristic, we propose a novel DSIC structure to achieve a better efficiency. The auxiliary receiver chain named as the pre-processing stage in this paper is included to process the linear part of the self-interference signal. Moreover, the pro-processing stage provides the convergence direction of the adaptive filter. Shorter convergence time and lower mean square error (MSE) are reached. The numerical results furnished by the realistic and rigorous simulations substantiate the efficiency of the proposed architecture.

This paper investigates dynamic railcar planning in railroad classification yards. The plan decides the assignment of railcars from inbound trains to outbound trains under various size limitations of outbound trains and allows dynamic sequencing of inbound train classification and outbound train assembly. A mixed-integer program is presented for the problem along with a heuristic algorithm based on the harmony search strategy. The numerical results based on both a real-world case and randomly created instances show that dynamic sequencing can reduce total dwell time compared to static sequencing, especially when more trains are classified at a yard. However, the savings on average dwell time for each railcar become smaller when the traffic volume goes up. Once the volume through a yard is close to its capacity, the dwell time per rail car goes up very quickly and the benefit of dynamic sequencing diminishes. It implies that the benefit of dynamic sequencing is more significant for yards with lower traffic...

The most recent extreme heat recorded in Europe re-alerts the world to the threat of heat stress. Future extreme heat events are reported to be more frequent, long-lasting, and intense. The intense exposure to hot temperatures can cause an excess of heat-related deaths, leading to an increasing risk of heat-related health. In reducing Heat Health Risk (HHR), the use of fine-scale evidence-based mapping of heat-related health risk index (HHRI) and its underlying contributors is essential for policy-making and site-specific action plans. However, its use is still considered to be at an early stage, especially in high-density cities like Hong Kong. This study conducted a spatially explicit assessment of HHR in Hong Kong and constructed a HHRI based on indicators categorized through Principle Component Analysis (PCA) into four meaningful components representing social/language, social isolation, socioeconomic, and urbanization/environmental risks. The applicability of the index was validated against heat-related mortality data at the community level. The community-level maps of HHRI and its subcomponents revealed that portions of Kowloon Peninsula had always suffered exceptionally high HHR ten years ago and after, but the hot spots and problematic communities experienced displacement and the dominant underlying factors of their HHR also varied. Results also showed that HHRI correlated fairly well with the heat-related deaths ratio (R2 = 0.60) at the community level for most of Hong Kong (62.33% of all communities that contain 81.69% of total population). Our analysis results helped generate an evidence-based index to assess HHR in high-density cities like Hong Kong and provided fine-scale maps of the index and its subcomponents, with the aim of benefiting site-specific policy making and optimizing the existing action plans.

Building communities' resilience to natural weather hazards requires the appropriate assessment of such capabilities. The resilience of a community is affected not only by social, economic, and infrastructural factors but also by natural factors (including both site characteristics and the intensity and frequency of events). To date, studies of natural factors have tended to draw on annual censuses and to use aggregated data, thus allowing only a limited understanding of site-specific hot or cold spots of resilience. To improve this situation, we carried out a comprehensive assessment of resilience to typhoon disasters in Nansha district, Guangzhou, China. We measured disaster resilience on 1×1-km grid units with respect to socioeconomic and infrastructural dimensions using a set of variables and also estimated natural factors in a detailed manner with a meteorological modeling tool, the Weather Research and Forecast model. We selected typhoon samples over the past 10 years, simulated the maximum typhoon-borne strong winds and precipitation of each sample, and predicted the wind speed and precipitation volume at the 100-year return-level on the basis of extreme value analysis. As a result, a composite resilience index was devised by combining factors in different domains using factor analysis coupled with the analytic hierarchy process. Resilience mapping using this composite resilience index allows local governments and planners to identify potential hot or cold spots of resilience and the dominant factors in particular locations, thereby assisting them in making more rational site-specific measures to improve local resilience to future typhoon disasters.

Building “disaster-resilient” rather than “disaster-resistant” cities/communities requires the development of response capabilities to natural disasters and subsequent recovery. This study devises a new method to measure resilience via recovery capability to validate indicators from social, economic, infrastructural, and environmental domains. The pollutant discharge data (waste-water and waste-gas discharge/emission data) of local power plants, sewage treatment plants and main factories were used to monitor recovery process of both people’s living and local industrial production as the waste water/gas is released irregularly during the short disaster-hit period. A time series analysis of such data was employed to detect the disturbance on these infrastructures from disasters and to assess community recovery capability. A recent record-breaking flash flood in Changzhou, a city in eastern-central China, was selected as a case study. We used ordinal logistic regression to identify leading proxies of flood resilience. A combination of six variables related to socioeconomic factors, infrastructure development and the environment, stood out and explained 61.4% of the variance in measured recovery capability. These findings substantiate the possibility of using recovery measurement based on pollutant discharge to validate resilience metrics, and contribute more solid evidences for policy-makers and urban planners to make corresponding measures for resilience enhancement.

The effect of secondary electrons on emission is studied by modelling the electrons behaviours in multi-layers, including electron injection, transportation, multiplication, and emission. The dielectric constant model and carrier mobility model are presented to describe the voltage distribution in multi-layers for the non-current injection and current injection respectively. After injection, the electrons are accelerated in SiO 2 , where they collide with the electrons, generating secondary electrons, consequently contributing to emission. A multiplying factor M is introduced to describe the secondary electrons multiplication in certain electrical field strength. The prediction was further proved by comparing two groups of devices with and without the accelerating layer: ITO/MEH-PPV/SiO 2 /Al and ITO/MEH-PPV/BCP/Al. The current avalanche observed in current–illumination experiment is a proof of the existence and contribution of secondary electrons.

Maintainability is an important product quality attribute that has significant influence on operational effectiveness and lifecycle cost. It is emphasized that maintainability has to be designed into product and standards or handbooks were developed to guide how the maintainability engineering is implemented. However, how to design product to meet maintenance needs is not explained clearly. Only some primary common rules are presented. A methodology for translating product maintenance needs to product features that have significant influence on maintainability is developed and illustrated. The method is expected to improve the logic and operability of maintainability practices.

Influences of electric fields on the emission from organic light-emitting diodes (OLEDs) based on poly(N-vinylcarbazole) (PVK) and 4′-bis(2-2diphenylvinyl)-1,1′-biphenyl (DPVBi) as the active emission layer are studied. Electroluminescence (EL) spectra of PVK:DPVBi (1:1 w/w) films show one new emission peak locating at 640 nm compared with its photoluminescence (PL) spectra. There may be exists an electroplex emission between the PVK and DPVBi under high electric field strength. The emission intensity of peaking at 640 nm strongly depends on the driving voltage, and the ratio of electroplex emission intensity to exciton emission intensity (Ielectroplex/Iexciton) increases with the increase of driving voltage.

Influences of electric fields on the emission from organic light-emitting diodes (OLEDs) based on poly (N-vinylcarbazole) (PVK); 2, 9-dimethyl-4, 7-diphenyl-1, 10-phenanthroline (BCP); and tris (8-hydroxyquinoline) aluminum (Alq3) were studied. There are three emission peaks at 420 nm, 520 nm, and 620 nm of the device ITO/PEDOT: PSS/PVK/BCP/LiF/Al under different driving voltages. The emissions at 420 nm and 520 nm should be from the exciton emission of PVK and Alq3, respectively. The last emission at 620 nm could be attributed to electroplex emission at the interface between the PVK and BCP layers. A high intensity white emission via electroplex formation was obtained with Commission International d'Eclairage (CIE) coordinates (0.33, 0.34) at 15 V, which is very close to the equienergy white point (0.33, 0.33).

Bulk heterojunction organic solar cells (OSCs) based on the blend of poly(2-methoxy-5(2′-ethyl-hexyloxy)-1,4-phenylenevinylene (MEH-PPV) and [6,6]-phenyl C61 butyric acid methyl ester (PCBM) with different weight ratios (from 1:3 to 1:5) have been fabricated and the effect of annealing treatment on the performance of OSCs has also been studied. Experimental results point to the best optimized doping concentration 1:4 for MEH-PPV:PCBM. Furthermore, it is found that the devices with annealing treatment at 150°C with 8 min show better performance compared with the devices without treatment. The series resistance (R s) is decreased, while the shunt resistance (R sh) increased by nearly 1.5 times. The short-circuit current density (J sc) and fill factor (FF) are improved by annealing treatment. As a result, the power conversion efficiency (PCE) of the devices increases from 0.49 % to 1.21 % with the ratio of 1:3 and from 1.09% to 1.42% with the ratio of 1:4.

Light after dusk disrupts the circadian rhythms and shifts the timing of sleep later; but it is unknown whether outdoor artificial light at night (ALAN) affects sleep quality. This study aimed to explore the association between residential outdoor ALAN and sleep duration in a nationally representative sample of Chinese older adults.We examined the cross-sectional associations of outdoor ALAN with self-reported sleep duration in 13,474 older adults participating in the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Outdoor ALAN exposure was estimated at the residence level using satellite images. We applied generalized linear mixed models to investigate the association between ALAN exposure and sleep duration. We performed stratified analyses by age, sex, education, and household income levels. Moreover, we used multi-level logistic regression models to investigate the effects of ALAN on the short sleep duration (≤6 h) and the long sleep duration (8 h), respectively, in reference to sleep for6-8 h per day.We found a significant association between outdoor ALAN intensity and sleep duration. The highest quartile of ALAN was associated with 17.04 (95% CI: 9.42-24.78) fewer minutes of sleep as compared to the lowest quartile. The reductions in sleep duration per quartile change in ALAN were greater in the young old (≥65-85 years) and in those with higher levels of education, and those with higher household income, respectively. We did not detect a sex difference. In addition, those in the highest quartile of ALAN were more likely to report a 25% (95% CI: 10%-42%) increase in short sleep (6 h), and a 21% (95% CI: 9%-31%) decrease in long sleep (8 h).Increasing outdoor nighttime light intensity surrounding residences was associated with shorter sleep duration in older residents in China. This finding implies the importance of urban outdoor artificial light management as a potential means to lower the public health burden of sleep disorders.