Characteristics of the mineral phase constituents of lacustrine deposits from the Fildes Peninsula of King George Island, Antarctica and their environmental implication

Based on analytical data of mineral phase constituents at three sections from Tern Lake, West Lake and Kitezh Lake in the Fildes Peninsula of King George Island, Antarctica, the characteristics of mineral phase constituents, material source and their environmental implication have been discussed. Research results indicate that lacustrine deposits came primarily from widespread volcanic rocks at the peninsula. Under cold and dry condition in Antarctica, the weathering process of the parent rocks in some area is mainly physical weathering with a weak chemical one. The relation curves of abundance of kaolinite and calcite against deposition age change steeply at the boundary between lacustrine and glacial deposits, indicating that the corresponding environment changes are abrupt, which may be related to different transportation fashion of both different deposits and the protection of glacial deposits

Developing Non-Negative Spatial Autoregressive Models for Better Exploring Relation Between Nighttime Light Images and Land Use Types

Exploring the relationship between nighttime light and land use is of great significance to understanding human nighttime activities and studying socioeconomic phenomena. Models have been studied to explain the relationships, but the existing studies seldom consider the spatial autocorrelation of night light data, which leads to large regression residuals and an inaccurate regression correlation between night light and land use. In this paper, two non-negative spatial autoregressive models are proposed for the spatial lag model and spatial error model, respectively, which use a spatial adjacency matrix to calculate the spatial autocorrelation effect of light in adjacent pixels on the central pixel. The application scenarios of the two models were analyzed, and the contribution of various land use types to nighttime light in different study areas are further discussed. Experiments in Berlin, Massachusetts and Shenzhen showed that the proposed methods have better correlations with the reference data compared with the non-negative least-squares method, better reflecting the luminous situation of different land use types at night. Furthermore, the proposed model and the obtained relationship between nighttime light and land use types can be utilized for other applications of nighttime light images in the population, GDP and carbon emissions for better exploring the relationship between nighttime remote sensing brightness and socioeconomic activities

Obstacle Avoidance for Unmanned Undersea Vehicle in Unknown Unstructured Environment

To avoid obstacle in the unknown environment for unmanned undersea vehicle (UUV), an obstacle avoiding system based on improved vector field histogram (VFH) is designed. Forward looking sonar is used to detect the environment, and the divisional sonar modal is applied to deal with the measure uncertainty. To adapt to the VFH, rolling occupancy grids are used for the map building, and high accuracy details of local environment are obtained. The threshold is adaptively adjusted by the statistic of obstacles to solve the problem that VFH is sensitive to threshold. To improve the environment adaptability, the hybrid-behaviors strategy is proposed, which selects the optimal avoidance command according to the motion status and environment character. The simulation shows that UUV could avoid the obstacles fast and escape from the U shape obstacles

Environmental magnetic measurements of marine sediments from Antarctica: implications to paleoclimate changes during the past 15 ka

In this paper, authors report some results obtained from systematic rock magnetic measurements on Core NP95-1 and Core NG93-1, which were collected from the Prydz Bay, Eastern Antarctica and Great Wall Bay (Maxwell Bay), Western Antarctica respectively during the 11th and 9th CHINARE and a sequence of paleoclimate variations is well established based on sediment rock magnetic properties. In Antarctica, the magnetic properties show a close linkage to paleoenvironmental variations. The Core NP95-1 well recorded several paleoclimatic events, such as Heinrich event 1, Bolling-Allerod warm period and Younger Dryas cold event. The Heinrich event 1 occurred at about 14.2 ka B.P., Younger Dryas cold event occurred between 11.7 ka B.P. and 10.3 ka B.P., and the boundary of Pleistocene and Holocene in Antarctica is 10.3 ka B.P.. In Holocene, two warm periods were recorded at about 10.0 ka B.P. and 6.0 ka B.P. with a little cold period between them. After 6.0 ka B.P., two cores both recorded a cold climatic oscillation. Paleoclimate described by two cores rock magnetic measurements was simultaneously changed in Eastern and Western Antarctica during the same period two cores commonly covered

The elemental geochemical characteristics of Late Quaternary rock core from Yanwo Lake in the Great Wall Station area, King George Island, Southwest Antarctica

This paper is mainly to treat the change regularity of the contents, distributions, enrich coefficients and correlative coefficients of some trace and constant elements in the sediments of Late Quaternary rock core from Yanwo Lake in the Great Wall Station area, King George Island and to discuss the sedimentary sources in Yanwo Lake and the periodical changes of Late Quaternary climate and the environment in the area. It is concluded that the clastic sedimentary rocks, including volcanic sedimentary rocks, around Yanwo Lake are the major sources of Yanwo Lake sediments, the mantle material is also one of its sources and what is more, the continent-sourced materials are transported by the Antarctic glacier

Learning-based fully automated prediction of lumbar disc degeneration progression with specified clinical parameters and preliminary validation

Abstract Background: Lumbar disc degeneration (LDD) may be related to aging, biomechanical and genetic factors. Despite the extensive work on understanding its etiology, there is currently no automated tool for accurate prediction of its progression. Purpose: We aim to establish a novel deep learning-based pipeline to predict the progression of LDD-related findings using lumbar MRIs. Materials and methods: We utilized our dataset with MRIs acquired from 1,343 individual participants (taken at the baseline and the 5-year follow-up timepoint), and progression assessments (the Schneiderman score, disc bulging, and Pfirrmann grading) that were labelled by spine specialists with over ten years clinical experience. Our new pipeline was realized by integrating the MRI-SegFlow and the Visual Geometry Group-Medium (VGG-M) for automated disc region detection and LDD progression prediction correspondingly. The LDD progression was quantified by comparing the Schneiderman score, disc bulging and Pfirrmann grading at the baseline and at follow-up. A fivefold cross-validation was conducted to assess the predictive performance of the new pipeline. Results: Our pipeline achieved very good performances on the LDD progression prediction, with high progression prediction accuracy of the Schneiderman score (Accuracy: 90.2 ± 0.9%), disc bulging (Accuracy: 90.4% ± 1.1%), and Pfirrmann grading (Accuracy: 89.9% ± 2.1%). Conclusions: This is the first attempt of using deep learning to predict LDD progression on a large dataset with 5-year follow-up. Requiring no human interference, our pipeline can potentially achieve similar predictive performances in new settings with minimal efforts