Two Measures for Enhancing Data Association Performance in SLAM

Data association is one of the key problems in the SLAM community. Several data association failures may cause the SLAM results to be divergent. Data association performance in SLAM is affected by both data association methods and sensor information. Two measures of handling sensor information are introduced herein to enhance data association performance in SLAM. For the first measure, truncating strategy of limited features, instead of all matched features, is used for observation update. These features are selected according to an information variable. This truncating strategy is used to lower the effect of false matched features. For the other measure, a special rejecting mechanism is designed to reject suspected observations. When the predicted robot pose is obviously different from the updated robot pose, all observed sensor information at this moment is discarded. The rejecting mechanism aims at eliminating accidental sensor information. Experimental results indicate that the introduced measures perform well in improving the stability of data association in SLAM. These measures are of extraordinary value for real SLAM applications

LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF

Neural Radiance Fields (NeRFs) have made great success in representing complex 3D scenes with high-resolution details and efficient memory. Nevertheless, current NeRF-based pose estimators have no initial pose prediction and are prone to local optima during optimization. In this paper, we present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter, which introduces a two-stage localization mechanism in city-scale NeRF. In place recognition stage, we train a regressor through images generated from trained NeRFs, which provides an initial value for global localization. In pose optimization stage, we minimize the residual between the observed image and rendered image by directly optimizing the pose on tangent plane. To avoid convergence to local optimum, we introduce a Truncated Dynamic Low-pass Filter (TDLF) for coarse-to-fine pose registration. We evaluate our method on both synthetic and real-world data and show its potential applications for high-precision navigation in large-scale city scenes. Codes and data will be publicly available at https://github.com/jike5/LATITUDE.Comment: 7 pages, 6 figures, submitted to ICRA 202

Climate warming accelerates temporal scaling of grassland soil microbial biodiversity.

Determining the temporal scaling of biodiversity, typically described as species-time relationships (STRs), in the face of global climate change is a central issue in ecology because it is fundamental to biodiversity preservation and ecosystem management. However, whether and how climate change affects microbial STRs remains unclear, mainly due to the scarcity of long-term experimental data. Here, we examine the STRs and phylogenetic-time relationships (PTRs) of soil bacteria and fungi in a long-term multifactorial global change experiment with warming (+3 °C), half precipitation (-50%), double precipitation (+100%) and clipping (annual plant biomass removal). Soil bacteria and fungi all exhibited strong STRs and PTRs across the 12 experimental conditions. Strikingly, warming accelerated the bacterial and fungal STR and PTR exponents (that is, the w values), yielding significantly (P < 0.001) higher temporal scaling rates. While the STRs and PTRs were significantly shifted by altered precipitation, clipping and their combinations, warming played the predominant role. In addition, comparison with the previous literature revealed that soil bacteria and fungi had considerably higher overall temporal scaling rates (w = 0.39-0.64) than those of plants and animals (w = 0.21-0.38). Our results on warming-enhanced temporal scaling of microbial biodiversity suggest that the strategies of soil biodiversity preservation and ecosystem management may need to be adjusted in a warmer world

Global diversity and biogeography of bacterial communities in wastewater treatment plants

Microorganisms in wastewater treatment plants (WWTPs) are essential for water purification to protect public and environmental health. However, the diversity of microorganisms and the factors that control it are poorly understood. Using a systematic global-sampling effort, we analysed the 16S ribosomal RNA gene sequences from ~1,200 activated sludge samples taken from 269 WWTPs in 23 countries on 6 continents. Our analyses revealed that the global activated sludge bacterial communities contain ~1 billion bacterial phylotypes with a Poisson lognormal diversity distribution. Despite this high diversity, activated sludge has a small, global core bacterial community (n = 28 operational taxonomic units) that is strongly linked to activated sludge performance. Meta-analyses with global datasets associate the activated sludge microbiomes most closely to freshwater populations. In contrast to macroorganism diversity, activated sludge bacterial communities show no latitudinal gradient. Furthermore, their spatial turnover is scale-dependent and appears to be largely driven by stochastic processes (dispersal and drift), although deterministic factors (temperature and organic input) are also important. Our findings enhance our mechanistic understanding of the global diversity and biogeography of activated sludge bacterial communities within a theoretical ecology framework and have important implications for microbial ecology and wastewater treatment processes

Effects of Nurse-led Psychosocial Intervention on Diabetes Distress and Glycemic Control among Patients withDiabetes : A Descriptive Literature Review

Background: With the increasing incidence of diabetes worldwide, the World HealthOrganization statistics that a total of 422 million adults suffer from diabetes worldwide,and the direct medical expenses caused by diabetes will also bring huge economiclosses to the world. Diabetes distress has become a serious mental problem of patientswith diabetes and will affect the glycemic control level of patients with diabetes, andultimately affect the quality of life of patients with diabetes.Aim: To describe the effect of nurse-led psychosocial intervention based on Roy'sadaptation theory on diabetes distress and glycemic control in diabetic patients.Method: A descriptive literature review was conducted by searching the literaturerelated to quantitative studies in database PubMed. Then, a total of 10 articles wereincluded and the data results were summarized and analyzed. Finally drawing thecorresponding conclusions.Results: Among the 10 articles, all of them elaborated the effects of nurse-ledpsychosocial intervention on diabetes distress, 7 articles argued that nurse-ledpsychosocial intervention may improve diabetes distress in diabetes patients, and theother 3 articles failed to clarify this point of view. There were 7 articles mentioned theeffects of nurse-led psychosocial intervention on glycemic control level, among which 5articles suggested that nurse-led psychosocial intervention methods could help improveglycemic control level, while the other literatures failed to clarify this point of view. Inaddition to the 7 articles, the other 3 articles did not indicate significant change ofglycemic control level.Conclusion: The nurse-led psychosocial interventions nurses may be a good way tohelp diabetes patients improve their diabetes distress and glycemic control level. Nursescan teach diabetes knowledge and skills through to psychosocial interventions helpdiabetes patients overcome obstacles, such as diabetes distress and improve their selfmanagement ability.Keywords: Nurses, psychosocial intervention, diabetes distress, glycemic controlleve

Effects of Nurse-led Psychosocial Intervention on Diabetes Distress and Glycemic Control among Patients withDiabetes : A Descriptive Literature Review

Background: With the increasing incidence of diabetes worldwide, the World HealthOrganization statistics that a total of 422 million adults suffer from diabetes worldwide,and the direct medical expenses caused by diabetes will also bring huge economiclosses to the world. Diabetes distress has become a serious mental problem of patientswith diabetes and will affect the glycemic control level of patients with diabetes, andultimately affect the quality of life of patients with diabetes.Aim: To describe the effect of nurse-led psychosocial intervention based on Roy'sadaptation theory on diabetes distress and glycemic control in diabetic patients.Method: A descriptive literature review was conducted by searching the literaturerelated to quantitative studies in database PubMed. Then, a total of 10 articles wereincluded and the data results were summarized and analyzed. Finally drawing thecorresponding conclusions.Results: Among the 10 articles, all of them elaborated the effects of nurse-ledpsychosocial intervention on diabetes distress, 7 articles argued that nurse-ledpsychosocial intervention may improve diabetes distress in diabetes patients, and theother 3 articles failed to clarify this point of view. There were 7 articles mentioned theeffects of nurse-led psychosocial intervention on glycemic control level, among which 5articles suggested that nurse-led psychosocial intervention methods could help improveglycemic control level, while the other literatures failed to clarify this point of view. Inaddition to the 7 articles, the other 3 articles did not indicate significant change ofglycemic control level.Conclusion: The nurse-led psychosocial interventions nurses may be a good way tohelp diabetes patients improve their diabetes distress and glycemic control level. Nursescan teach diabetes knowledge and skills through to psychosocial interventions helpdiabetes patients overcome obstacles, such as diabetes distress and improve their selfmanagement ability.Keywords: Nurses, psychosocial intervention, diabetes distress, glycemic controlleve

An experimental study of the behavior of a model variable refrigerant flow system with common faults

Variable refrigerant flow (VRF) systems faults are inevitable due to installation errors, degradation, and other reasons. It is of great value to quantitatively understand the impact of faults on VRF systems performance and to clarify the changing trends of variables under different types of faults through experiments. In particular, the experimental analysis of simultaneous faults situations is helpful to improve the fault detection and diagnosis technology of VRF systems. There have been some previous experimental studies on the impact of faults, but none of them concerns modern VRF systems and their simultaneous faults. This paper presents results from a laboratory study of a VRF system with different types of faults. It provides the first published results of combinations of triple simultaneous faults, in addition to previously untested types of double simultaneous faults. The quantitative impact of the three crucial performance parameters, e.g. cooling capacity, system power, and COP, of the system under different faults has been analyzed. In addition, the quantitative influence and variation trend of system parameter variables during single fault and simultaneous fault are summarized. Results show that the outdoor fouling fault has the greatest impact, which can cause a 47.6% COP drop and 80.27% cooling capacity reduction. The influence of the simultaneous fault on the variable trend is superimposed and offset, but the trend influence of some faults also has a dominant characteristic