基于双层修正无迹卡尔曼的水下节点定位算法* .txt

摘要：针对水下无线传感网络中运动节点定位精度低的问题，提出了一种新的基于双层修正无迹卡尔曼的水下节点定位算法(DLMUKF)。该算法利用下层无迹卡尔曼滤波算法对节点状态进行预测，根据各信标节点的测距传播时延对预测的节点状态进行修正。运用上层无迹卡尔曼滤波算法对修正后的状态进行新的预测与修正。仿真实验中，DLMUKF算法的平均定位误差约为传统多边定位算法的15%，约为基于无迹卡尔曼滤波（UKF）定位算法的16%，受节点运动时间与速度的影响最小。通过实验证明DLMUKF算法能更充分利用实际距离值，可以有效减小运动节点的定位误差。 .txt     

Radon and moisture impacts from interventions integrated with housing energy retrofits

Energy retrofits can reduce air exchange, raising the concern of whether indoor radon and moisture levels could increase. This pre/post-intervention study explored whether simple radon interventions implemented in conjunction with energy retrofits can prevent increases in radon and moisture levels. Treatment homes (n = 98) were matched with control (no energy retrofits or radon intervention) homes (n = 12). Control homes were matched by geographic location and foundation type. t-tests were used to determine whether post-energy retrofit radon and moisture level changes in treatment homes significantly differed from those in control homes. The radon interventions succeeded in preventing statistically significant increases in first floor radon using arithmetic (p = 0.749) and geometric means (p = 0.120). In basements, arithmetic (p = 0.060) and geometric (p = 0.092) mean radon levels statistically significantly increased, consistent with previous studies which found that basement radon levels may increase even if first floor levels remain unchanged. Changes in infiltration were related to changes in radon (p = 0.057 in basements; p = 0.066 on first floors). Only 58% of the change in infiltration was due to air sealing, with the rest due to weather changes. There was no statistically significant association between air sealing itself and radon levels on the first floor (p = 0.664). Moisture levels also did not significantly increase.     

Efficient atom localization via probe absorption in an inverted-Y atomic system

The behaviour of atom localization in an inverted-Y atomic system is theoretically investigated. For the atoms interacting with a weak probe field and several orthogonal standing-wave fields, their position information can be obtained by measuring the probe absorption. Compared with the traditional scheme, we couple the probe field to the transition between the middle and top levels. It is found that the probe absorption sensitively depends on the detuning and strength of the relevant light fields. Remarkably, the atom can be localized at a particular position in the standing-wave fields by coupling a microwave field to the transition between the two ground levels.     

Window Detection in Facades Using Heatmap Fusion

Journal of Computer Science and Technology - Window detection is a key component in many graphics and vision applications related to 3D city modeling and scene visualization. We present a novel...     

增材制造技术在超高膨胀封隔器中的应用

石油和天然气行业不断关注增材制造技术在航空航天和汽车行业的应用发展。研发了利用增材制造技术的超高膨胀封隔器,该封隔器的支承环系统由增材制造。增材制造设计大幅减少了支承系统的构件数量,同时显著提高了膨胀能力和额定压力。密封元件系统与增材制造支承环安装在一起,提供了极端膨胀比、零挤压间隙和对不规则孔的良好适应性。分析和测试结果表明:直径膨胀比高达111%,与常规封隔器相比,提高50%以上; 至少涵盖5种线重的套管(外径相同); 在148.89 ℃的温度下,密封元件能够保持压力68.95 MPa。介绍了增材制造技术、增材制造支承环概念、增材制造材料力学性能、密封元件系统优化和测试情况,以期给我国的完井作业提供借鉴。     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

A general mechanistic model for predicting the fate and transport of phthalates in indoor environments

A mechanistic model that considers particle dynamics and their effects on surface emissions and sorptions was developed to predict the fate and transport of phthalates in indoor environments. A controlled case study was conducted in a test house to evaluate the model. The model‐predicted evolving concentrations of benzyl butyl phthalate in indoor air and settled dust and on interior surfaces are in good agreement with measurements. Sensitivity analysis was performed to quantify the effects of parameter uncertainties on model predictions. The model was then applied to a typical residential environment to investigate the fate of di‐2‐ethylhexyl phthalate (DEHP) and the factors that affect its transport. The predicted steady‐state DEHP concentrations were 0.14 μg/m³ in indoor air and ranged from 80 to 46 000 μg/g in settled dust on various surfaces, which are generally consistent with the measurements of previous studies in homes in different countries. An increase in the mass concentration of indoor particles may significantly enhance DEHP emission and its concentrations in air and on surfaces, whereas increasing ventilation has only a limited effect in reducing DEHP in indoor air. The influence of cleaning activities on reducing DEHP concentration in indoor air and on interior surfaces was quantified, and the results showed that DEHP exposure can be reduced by frequent and effective cleaning activities and the removal of existing sources, though it may take a relatively long period of time for the levels to drop significantly. Finally, the model was adjusted to identify the relative contributions of gaseous sorption and particulate‐bound deposition to the overall uptake of semi‐volatile organic compounds (SVOCs) by indoor surfaces as functions of time and the octanol‐air partition coefficient (K_oa) of the chemical. Overall, the model clarifies the mechanisms that govern the emission of phthalates and the subsequent interactions among air, suspended particles, settled dust, and interior surfaces. This model can be easily extended to incorporate additional indoor source materials/products, sorption surfaces, particle sources, and room spaces. It can also be modified to predict the fate and transport of other SVOCs, such as phthalate‐alternative plasticizers, flame retardants, and biocides, and serves to improve our understanding of human exposure to SVOCs in indoor environments.     

Prelabeling Expansion Single-Molecule Localization Microscopy with Minimal Linkage Error

Expansion microscopy combined with single-molecule localization microscopy (ExSMLM) has a potential for approaching molecular resolution. However, ExSMLM faces multiple challenges such as loss of fluorophores and proteins during polymerization, digestion or denaturation, and an increase in linkage error arising from the distance between the fluorophore and the target molecule. Here, we introduce a trifunctional streptavidin to link the target, fluorophore and gel matrix via a biotinylizable peptide tag. The resultant ExSMLM images of vimentin filaments demonstrated high labeling efficiency and a minimal linkage error of ∼5 nm. Our ExSMLM provides a simple and practical means for fluorescence imaging with molecular resolution.     

Particulate matter emitted from ultrasonic humidifiers—Chemical composition and implication to indoor air

Household humidification is widely practiced to combat dry indoor air. While the benefits of household humidification are widely perceived, its implications to the indoor air have not been critically appraised. In particular, ultrasonic humidifiers are known to generate fine particulate matter (PM). In this study, we first conducted laboratory experiments to investigate the size, quantity, and chemical composition of PM generated by an ultrasonic humidifier. The mass of PM generated showed a correlation with the total alkalinity of charge water, suggesting that CaCO₃ is likely making a major contribution to PM. Ion chromatography analysis revealed a large amount of SO₄²⁻ in PM, representing a previously unrecognized indoor source. Preliminary results of organic compounds being present in humidifier PM are also presented. A whole-house experiment was further conducted at an actual residential house, with five low-cost sensors (AirBeam) monitoring PM in real time. Operation of a single ultrasonic humidifier resulted in PM_2.5 concentrations up to hundreds of μg m⁻³, and its influence extended across the entire household. The transport and loss of PM_2.5 depended on the rate of air circulation and ventilation. This study emphasizes the need to further investigate the impact of humidifier operation, both on human health and on the indoor atmospheric chemistry, for example, partitioning of acidic and basic compounds.     

Teachers' work-related non-literature-known building-related symptoms are also connected to indoor toxicity: A cross-sectional study

A previous study showed that classical building-related symptoms (BRS) were related to indoor dust and microbial toxicity via boar sperm motility assay, a sensitive method for measuring mitochondrial toxicity. In this cross-sectional study, we analyzed whether teachers’ most common work-related non-literature-known BRS (nBRS) were also associated with dust or microbial toxicity. Teachers from 15 schools in Finland completed a questionnaire evaluating 20 nBRS including general, eye, respiratory, hearing, sleep, and mental symptoms. Boar sperm motility assay was used to measure the toxicity of extracts from wiped dust and microbial fallout samples collected from teachers’ classrooms. 231 teachers answered a questionnaire and their classroom toxicity data were recorded. A negative binomial mixed model showed that teachers’ work-related nBRS were 2.9-fold (95% CI: 1.2-7.3) higher in classrooms with highly toxic dust samples compared to classrooms with non-toxic dust samples (p = 0.024). The RR of work-related nBRS was 1.8 (95% CI: 1.1-2.9) for toxic microbial samples (p = 0.022). Teachers’ BRS appeared to be broader than reported in the literature, and the work-related nBRS were associated with toxic dusts and microbes in classrooms.