Searching For a Lost Plane

Malaysia plane MH370 disappeared en route from Kuala Lumpur to Beijing on 8, March 2014. Besides considering the factors such as air piracy, weather, electromagnetic wave, and kinds of bugs of the airplane, in order to find the wreckage efficiently the growing concern is to confirm a limited area where the airplane probably fell, and then to find an optimum way to find the plane. It’s essential to build such a model involving both of the two layers mentioned above that can cover all the searching area by using the most efficient way. The first layer is to confirm the limited area. We use the Poisson Probability Distribution, the Drag equation, and the Proper Orthogonal Decomposition Theorem to assume the direction of the airplane and the sea area where it probably fell. All assumptions are based on the actual situation. The second model will basically rely on the Bayesian principles. In this case, the model would be advantageous as it will rely on contingency as an important role in the search for lost objects in the sea or on land. As matter of fact, any information that is provided to the search team would be put into good use as it will be used in developing the probabilities. It is also good in that it\u27s flexible and would be good enough to sustain the ongoing search even with new information or facts obtained regarding the flight of the plane and/or the initial findings of the debris. This helps in rounding down to a lesser geographical search region and, by extension, increases the probability of getting the plane

Expression of genes involved in regulation of polyunsaturated fatty acid metabolism in liver of Atlantic salmon (Salmo salar) undergoing parr-smolt transformation

Purposes The primary aim of this thesis was to study if differences in nutritional and environmental factors influence the regulation of n-3 LC-PUFA synthesis in liver of Atlantic salmon (big smolts) undergoing parr-smolt transformation. A further aim was to use the cell line RTH-149 to establish a protocol for gene knockout of ∆6 desaturase isoform ∆6fad_b. Methods The experimental fish were fed a commercial diet until the start of the trial (30 October 2012), and thereafter fed a diet with an oil fraction consisting of only 10% fish oil (FO) and 90% vegetable oil (VO) until the end of the trial. The fish were kept under full light (24 hours per day), except in a period from 20 November 2012 to 16 January 2013, when the light duration was gradually reduced from 24 hours to 12 hours in order to delay the smoltification process in the fish so that a large smolt could be produced in freshwater. Thereafter the fish were subjected to 24 hours light again to prepare it for final smoltification and transfer to seawater in February at approximately 400 gram. The expression of the selected genes (including ∆5 and ∆6 desaturases, transcription factors PPARα and SREBPS, and microRNAs which are related to lipid metabolism) was determined at four time points (30 October 2012, 27 November 2012, 26 February 2013 and 12 March 2013) during this fish trial. Cell line RTH-149 were transfected at a confluence of approximately 70% by CRISPR-Cas9 system with either sgRNA1, sgRNA2, sgRNA1/2 (a combination of sgRNA1 and sgRNA2, both sgRNA1 and sgRNA2 are targeting gene ∆6fad_b but with different cleavage sites) or sgRNA of control random-oligo. The differently transfected cells were further split for time-course study. The expression of the protein coding genes was determined at three selected time points during a 24-hour experiment with an interval of eight hours (i.e. at 8:00, 16:00 and 0:00). Results The expression of ∆5fad and ∆6fad_a increased slightly up to the seawater transfer, and then decreased after seawater transfer. The expressions of these genes in March were almost returned to their starting levels of expression in October. On the contrary, the expression of ∆6fad_b and ∆6fad_c showed a similar pattern of expression from October to February, but the opposite pattern to ∆5fad and ∆6fad_a with an increased expression after seawater transfer. The expression of the transcription factors pparα, srebp-1 and srebp-2 dropped from October to February and thereafter increased prior to seawater transfer, after which the expression levels of pparα and srebp-1 again significantly decreased after seawater transfer except srebp-2 which did not change in seawater. The expressions of mir-122-5p dropped from October to November; the expression increased prior to seawater transfer and thereafter dropped again in seawater. The gene expression of mir-30c-3p, mir-8163-3p, mir-27a-3p, mir-15a-5p, mir-429-3p, mir-33a-3p and mir-145-3p showed a similar pattern prior to seawater transfer, but the expression did not change after transfer to seawater. There were reduced expression levels of ∆6fad_b 24 hours after transfection but together with a restrained growth rate and a low viability of the cell cultures. There were relatively moderate and few significant differences in the expression of genes involved in lipid metabolism between the three time points measured during the 24 hour duration of experiment in the RTH cell line. Further, we disclosed a potential positive relationship between ∆6fad_a, ∆6fad_b, elovl2a, elovl2b, elovl5a and aco, and a potential compensatory response of gene ∆5fad to the silencing of gene ∆6fad_b. Conclusions This present study has shown that both nutritional and environmental factors influence expression of genes involved in regulation of LC-PUFA in liver of Atlantic salmon undergoing parr-smolt transformation. This is the first time that transcription factors and microRNAs were involved in a dynamic regulation of the omega-3 metabolic pathway under different environmental conditions at different life stages.M-A

The Application of Shape Gradient for the Incompressible Fluid in Shape Optimization

This paper is concerned with the numerical simulation for shape optimization of the Stokes flow around a solid body. The shape gradient for the shape optimization problem in a viscous incompressible flow is evaluated by the velocity method. The flow is governed by the steady-state Stokes equations coupled with a thermal model. The structure of continuous shape gradient of the cost functional is derived by employing the differentiability of a minimax formulation involving a Lagrange functional with the function space parametrization technique. A gradient-type algorithm is applied to the shape optimization problem. Numerical examples show that our theory is useful for practical purpose, and the proposed algorithm is feasible and effective

SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry

In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on automated unit testing tool CAUT, we rebuild a new tool, SmartUnit, to solve the engineering requirements that take place in our partner companies. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May 27-June 3, 2018 (ICSE-SEIP '18), 10 page

MMNet: Multi-Mask Network for Referring Image Segmentation

Referring image segmentation aims to segment an object referred to by natural language expression from an image. However, this task is challenging due to the distinct data properties between text and image, and the randomness introduced by diverse objects and unrestricted language expression. Most of previous work focus on improving cross-modal feature fusion while not fully addressing the inherent uncertainty caused by diverse objects and unrestricted language. To tackle these problems, we propose an end-to-end Multi-Mask Network for referring image segmentation(MMNet). we first combine picture and language and then employ an attention mechanism to generate multiple queries that represent different aspects of the language expression. We then utilize these queries to produce a series of corresponding segmentation masks, assigning a score to each mask that reflects its importance. The final result is obtained through the weighted sum of all masks, which greatly reduces the randomness of the language expression. Our proposed framework demonstrates superior performance compared to state-of-the-art approaches on the two most commonly used datasets, RefCOCO, RefCOCO+ and G-Ref, without the need for any post-processing. This further validates the efficacy of our proposed framework.Comment: 10 pages, 5 figure

Is China-US cooperation on climate change issues mutually beneficial?

published_or_final_versionInternational and Public AffairsMasterMaster of International and Public Affair

EAVL: Explicitly Align Vision and Language for Referring Image Segmentation

Referring image segmentation aims to segment an object mentioned in natural language from an image. A main challenge is language-related localization, which means locating the object with the relevant language. Previous approaches mainly focus on the fusion of vision and language features without fully addressing language-related localization. In previous approaches, fused vision-language features are directly fed into a decoder and pass through a convolution with a fixed kernel to obtain the result, which follows a similar pattern as traditional image segmentation. This approach does not explicitly align language and vision features in the segmentation stage, resulting in a suboptimal language-related localization. Different from previous methods, we propose Explicitly Align the Vision and Language for Referring Image Segmentation (EAVL). Instead of using a fixed convolution kernel, we propose an Aligner which explicitly aligns the vision and language features in the segmentation stage. Specifically, a series of unfixed convolution kernels are generated based on the input l, and then are use to explicitly align the vision and language features. To achieve this, We generate multiple queries that represent different emphases of the language expression. These queries are transformed into a series of query-based convolution kernels. Then, we utilize these kernels to do convolutions in the segmentation stage and obtain a series of segmentation masks. The final result is obtained through the aggregation of all masks. Our method can not only fuse vision and language features effectively but also exploit their potential in the segmentation stage. And most importantly, we explicitly align language features of different emphases with the image features to achieve language-related localization. Our method surpasses previous state-of-the-art methods on RefCOCO, RefCOCO+, and G-Ref by large margins.Comment: 10 pages, 4 figures. arXiv admin note: text overlap with arXiv:2305.1496