Planning and implementing trajectories for autonomous underwater vehicles to track evolving ocean processes based on predictions from a regional ocean model

Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

Autonomous underwater vehicle trajectory design coupled with predictive ocean models : a case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Scale adaptive tracking using mean shift and efficient feature matching

The mean shift tracker has achieved great success in visual object tracking due to its efficiency being nonparametric. However, it is still difficult for the tracker to handle scale changes of the object. In this paper, we associate a scale adaptive approach with the mean shift tracker. Firstly, the target in the current frame is located by the mean shift tracker. Then, a feature point matching procedure is employed to get the matched pairs of the feature point between target regions in the current frame and the previous frame. We employ FAST-9 corner detector and HOG descriptor for the feature matching. Finally, with the acquired matched pairs of the feature point, the affine transformation between target regions in the two frames is solved to obtain the current scale of the target. Experimental results show that the proposed tracker gives satisfying results when the scale of the target changes, with a good performance of efficiency.

Rapid increase in scrub typhus incidence in Mainland China, 2006-2014

Scrub typhus is a vector-borne disease, which has recently reemerged in China. In this study, we describe the distribution and incidence of scrub typhus cases in China from 2006 to 2014 and quantify differences in scrub typhus cases with respect to sex, age, and occupation. The results of our study indicate that the annual incidence of scrub typhus has increased during the study period. The number of cases peaked in 2014, which was 12.8 times greater than the number of cases reported in 2006. Most (77.97%) of the cases were reported in five provinces (Guangdong, Yunnan, Anhui, Fujian, and Shandong). Our study also demonstrates that the incidence rate of scrub typhus was significantly higher in females compared to males (P < 0.001) and was highest in the 60–69 year age group, and that farmers had a higher incidence rate than non farmers (P < 0.001). Different seasonal trends were identified in the number of reported cases between the northern and southern provinces of China. These findings not only demonstrate that China has experienced a large increase in scrub typhus incidence, but also document an expansion in the geographic distribution throughout the country.

Raman microscopic study of the Li amphibole holmquistite, from the Martin Marietta Quarry, Bessemer City, NC, USA

The Raman spectrum of holmquistite, a Li-containing orthorhombic amphibole from Bessemer City, USA has been measured. The OH-stretching region is characterized by bands at 3661, 3646, 3634 and 3614 cm–1 assigned to 3 Mg–OH, 2 Mg + Fe2+–OH, Mg + 2Fe2+–OH and 3 Fe2+–OH, respectively. These Mg and Fe2+ cations are located at the M1 and M3 sites and have a Fe2+/(Fe2+ + Mg) ratio of 0.35. The 960–1110 cm–1 region represents the antisymmetric Si–O–Si and O–Si–O stretching vibrations. For holmquistite, strong bands are observed around 1022 and 1085 cm–1 with a shoulder at 1127 cm–1 and minor bands at 1045 and 1102 cm–1. In the region 650–800 cm–1 bands are observed at 679, 753 and 791 cm–1 with a minor band around 694 cm–1 attributed to the symmetrical Si–O–Si and Si–O vibrations. The region below 625 cm–1 is characterized by 14 vibrations related to the deformation modes of the silicate double chain and vibrations involving Mg, Fe, Al and Li in the various M sites. The 502 cm–1 band is a Li–O deformation mode while the 456, 551 and 565 cm–1 bands are Al–O deformation modes.

Osteopontin expression correlates with melanoma invasion

Melanoma is one of the most aggressive cancers affecting humans. Although early melanomas are curable with surgical excision, metastatic melanomas are associated with high mortality. The mechanism of melanoma development, progression, and metastasis is largely unknown. In order to uncover genes unique to melanoma cells, we used high-density DNA microarrays to examine the gene expression profiles of metastatic melanoma nodules using benign nevi as controls. Over 190 genes were significantly overexpressed in metastatic melanomas compared with normal nevi by at least 2-fold. One of the most abundantly expressed genes in metastatic melanoma nodules is osteopontin (OPN). Immunohistochemistry staining on tissue microarrays and individual skin biopsies representing different stages of melanoma progression revealed that OPN expression is first acquired at the step of melanoma tissue invasion. In addition, blocking of OPN expression by RNA interference reduced melanoma cell numbers in vitro. Our observations suggest that OPN may be acquired early in melanoma development and progression, and may enhance tumor cell growth in invasive melanoma.

Structural health monitoring for long span bridges : Hong Kong experience and continuing onto Australia

Structural health monitoring has been accepted as a justified effort for long-span bridges, which are critical to a region's economic vitality. As the most heavily instrumented bridge project in the world, WASHMS - Wind And Structural Health Monitoring System has been developed and installed on the cable-supported bridges in Hong Kong (Wong and Ni 2009a). This chapter aims to share some of the experience gained through the operations and studies on the application of WASHMS. It is concluded that Structural Health Monitoring should be composed of two main components: Structural Performance Monitoring (SPM) and Structural Safety Evaluation (SSE). As an example to illustrate how the WASHMS could be used for structural performance monitoring, the layout of the sensory system installed on the Tsing Ma Bridge is briefly described. To demonstrate the two broad approaches of structural safety evaluation - Structural Health Assessment and Damage Detection, three examples in the application of SHM information are presented. These three examples can be considered as pioneer works for the research and development of the structural diagnosis and prognosis tools required by the structural health monitoring for monitoring and evaluation applications.

Climate variability and hemorrhagic fever with renal syndrome transmission in northeastern China

Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. ---------- Objective: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. ---------- Methods: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997–2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. ----------- Results: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3–5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3–5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. ---------- Conclusions: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.

A participant’s response : recreating the circle with We Al-Li: a program for sharing and regeneration

Personal reflections on the We Al-Li Program

Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.