Temporal Distribution of Arsenic and Metals in Soil From King George Island, Antarctica

The polar regions are vulnerable to impacts caused by local and global pollution. The Antarctic continent has been considered an environment that has remained little affected by human activities. Direct exposure to contaminants may occur in areas continuously occupied by research stations for several decades. Admiralty Bay on the southeast coast of King George Island, has potential for being affected by human activities due research stations operating in the area, including the Brazilian Commandant Ferraz Antarctic Station (CFAS). The levels of metals and arsenic were determined in soils collected near CFAS (points 5, 6, 7, and 9), Base G and at two points distant from the CFAS: Refuge II and Hennequin. Samples were collected after the fire in CFAS occurred in February 2012, up to December 2018 to assess the environmental impacts in the area. Al and As were related with Base G. Refuge II and Hennequin can be considered as control points for this region. As a consequence of the accident, the increased levels for Cd, Cu, Pb, and Zn, especially at point 9 (inside the CFAS) and in the soil surrounding the CFAS in 2013. The results from 2016 to 2018 demonstrated a reduction in levels of all studied metals near CFAS, which may be related to the leaching of metals into Admiralty Bay; it is thus, being important the continue monitoring soil, sediments, and Antarctic biota.

Consortium blockchains based traceability system for chicken product supply chain

In recent years, people pay increasing attention to food safety. Chicken, as the second largest meat consumer goods in China, requires high level quality traceability. However, due to the small monomer and large quantity of live poultry, it is difficult to duplicate the whole chain tracing mode of pig industry. In this paper we use HACCP (Hazard Analysis and Critical Control Points) to analyze the key control points in the chicken supply chain, and design the traceability code for each chicken product. The traceability system applies the consortium blockchains technology to realize the secure and trusted up-chaining of traceability data, which ensures the quality and safety of chicken in the market.

Evaluation of Damage Limit State for RC Frame Based on FE Modeling

Many damage limit states have been defined to characterize the extent of damages occurred in RC frame. Some of the damage limit states are defined by models that relate the limit states with the control points. Both control points and the limit state are expressed in term of response quantities. This research aims to evaluate the validity of such models by identifying the defined damage limit state with the corresponding damage based on FE modeling. The FE modeling provides a direct link between the damage and the response quantities. This link can be exploited as a basis for the evaluation. Based on the evaluation, this study proposed modified damage limit states. The response quantities with its corresponding progressive damage from FE simulation will also be used to inspect whether damage that can be expected to occur in the model structure is within the range estimated by the code based approach (CBA) damage limit state. Finally, fragility curves are constructed to assess the probability of the expected damage in the model structure under Design Basis Earthquake (DBE) and Maximum Considered Earthquake (MCE) scenarios. Utilizing the proposed damage limit states, the most probable damage in the structure falls in the category of slight if an earthquake at a level of DBE or MCE strikes the structure. However, at MCE level the probability of moderate damage attains 35%, or an increase by 23% compared to the DBE level.

High-Precision Digital Surface Model Extraction from Satellite Stereo Images Fused with ICESat-2 Data

The lack of ground control points (GCPs) affects the elevation accuracy of digital surface models (DSMs) generated by optical satellite stereo images and limits the application of high-resolution DSMs. It is a feasible idea to use ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) laser altimetry data to improve the elevation accuracy of optical stereo images, but it is necessary to accurately match the two types of data. This paper proposes a DSM registration strategy based on terrain similarity (BOTS), which integrates ICESat-2 laser altimetry data without GCPs and improves the DSM elevation accuracy generation from optical satellite stereo pairs. Under different terrain conditions, Worldview-2, SV-1, GF-7, and ZY-3 stereo pairs were used to verify the effectiveness of this method. The experimental results show that the BOTS method proposed in this paper is more robust when there are a large number of abnormal points in the ICESat-2 data or there is a large elevation gap between DSMs. After fusion of ICESat-2 data, the DSM elevation accuracy extracted from the satellite stereo pair is improved by 73~92%, and the root mean square error (RMSE) of Worldview-2 DSM reaches 0.71 m.

A Calculation Method for the Deformation Behavior of Warp-Knitted Fabric

In this paper, a new method to simulate the structure and loop deformation behavior of double-bar reflex-lapping warp-knitted fabrics based on the structural characteristics is proposed. A simplified mass-spring model was built in which loops knitted by filaments were considered as particles with the uniform mass distribution connected by structure springs for overlaps and shear springs for underlaps. Deformation forces and direction on particles were analyzed to describe the displacement and deformation behavior of particles. A loop model with eight control points was established, and the relationship between control points and particles was studied combining the quadratic Bezier curves. The deformation simulation was implemented by a simulator program with C# and JavaScript via web technology on Visual Studio 2015. The stereoscopic sense of filaments was realized by changing the direction and intensity of the light. The results show that the fabric deformation and the loop shape can be accurately achieve using the simplified mass-spring model compared with the real sample.

Fully Automatic Cell Segmentation with Fourier Descriptors

Cell segmentation is a fundamental problem in biology for which convolutional neural networks yield the best results nowadays. In this paper, we present HarmonicNet, a network, which is a modification of the popular StarDist and SplineDist architectures. While StarDist and SplineDist describe an object by the lengths of equiangular rays and control points respectively, our network utilizes Fourier descriptors, predicting a coefficient vector for every pixel on the image, which implicitly define the resulting segmentation. We evaluate our model on three different datasets, and show that Fourier descriptors can achieve a high level of accuracy with a small number of coefficients. HarmonicNet is also capable of accurately segmenting objects that are not star-shaped, a case where StarDist performs suboptimally according to our experiments.

Improving the Accuracy of Aerial Photography Using Ground Control Points

The authors showed that it is possible to quickly collect up-to-date information on the agricultural land condition using an unmanned aerial vehicle. It was noted that the use of ground control points increases the accuracy of project measurements, helps to compare the project post-processing results with the real measurements. (Research purpose) To compare the results of standard and high-precision post-processing of aerial survey data using ground control points. (Materials and methods) Aerial photography was carried out on a 1.1- hectare breeding field. The authors used DJI Matrice 200 v2 unmanned aerial vehicle with a GNSS L1/L2 receiver and a modified DJI X4S camera, five control points sized 50 × 50 centimeters and an EMLID Reach RS2 multi-frequency GNSS receiver. The results of scientific research into the use of ground control points during aerial photography were studied. (Results and discussion) It was found out that the error of georeferencing images obtained by an unmanned aerial vehicle without control points is significantly higher during the standard data processing compared to the high-precision one. The project error when using five control points is 3.9 times higher during the standard data processing. (Conclusions) It was shown that using ground control points it is possible to improve the project measurement accuracy, as well as compare the project post-processing results with the measurements on the ground. It was detected that the high-precision monitoring enables the use of fewer ground control points. It was found out that in order to obtain data with the accuracy of 2-4 centimeters in plan and height, at least 3 ground control points need to be used during the high-precision post-processing.