Selection of markets for textile export using the adequate portfolio

Textiles is one of the largest industries in the world, creating significant volumes of trade, export, and jobs. In the European Union, this industry is essential and attempts to retain and increase competitiveness. Most of the textile and clothing sector production is exported; thus, adequate orientation to export markets is essential. The paper’s objective is to determine the countries suitable for exporting the textile production of Lithuania and similar countries using the adequate portfolio model. The adequate portfolio treats the export possibilities according to three parameters: return, reliability, and risk. Clothing annual average index data across countries obtained from the Eurostat database were used for calculations. After performing the research, three portfolio cases were proposed, and the most profitable export countries and their given return were determined. Research results can be applied to the whole country and for individual textile exporting enterprises.

Segmentation of Agricultural Parcels in Satellite Images Based on Historical Vegetation Index Data

This paper considered the issue of agricultural fields boundary recognition in satellite images. A novel algorithm based on the aggregated history of vegetation index data obtained via open satellite data, Sentinel-2, was proposed. The proposed algorithm included several basic steps, namely the detection of parcel regions on aggregated index data; the calculation of aggregated edge maps; the segmentation of parcel regions using the edges obtained; the computation of connected components and their contour extraction. In this paper, we showed that the use of aggregated vegetation index data and boundary maps allow for much more accurate agricultural field segmentation compared to the instant vegetation index approach. The quality of segmentation within regions of Russia and the Ukraine was estimated. The dataset that was used and Python implementation of the proposed algorithm were provided.

Estimating the Mosquito Density in Guangzhou city, China

Mosquito is a vector of many diseases. Predicting the trend of mosquito density is important for early warning and control of mosquito diseases. In this paper, we fit a discrete time mosquito model developed by Gong et al. in 2011, which considers the immature and adult stages, and weather dependent model parameters, to the Breteau Index and Bite Index data for Aedes aegypti in Guangzhou city, China in 2014, as well as the weather data for average temperature, precipitation, evaporation and daylight for the same period. We estimated the model parameters using the Markov Chain Monte-Carlo (MCMC) method. We find that many parameters are not identifiable. We revise and simplify the model so that the parameters of our new model are identifiable. Our results indicate that the model predicted mosquito prevalence agrees well with data. We then use the fitted parameter values against the Breteau Index and Bite Index data for Guangzhou city in 2017 and 2018, and show that the estimated parameter values are applicable for other seasons.

Dr. Kremer et al reply

Drs. Pincus, Bergman, and Yazici have raised some concerns about our published article comparing the Clinical Disease Activity Index (CDAI) with simultaneous measures of the Routine Assessment of Patient Index Data 3 (RAPID3).1 We believe our publication has clearly established that the validated CDAI scores provide a fundamentally different evaluation of disease status compared with the RAPID3.

Should Quantitative Measures and Management of Rheumatoid Arthritis Include More Than Control of Inflammatory Activity?

We agree strongly with Kremer et al that "metrics are essential for evaluating disease activity in patients with rheumatoid arthritis (RA)."1 Nonetheless, data reported from the Corrona and the Brigham and Women's Rheumatoid Arthritis Sequential Study (BRASS) registries for Clinical Disease Activity Index (CDAI) and Routine Assessment of Patient Index Data 3 (RAPID3) are quite similar to those reported in the initial 2008 RAPID3 report.2

Application of Discrete Mathematics in the Evaluation Model of Regional Economic Growth Effect

At present, the evaluation of regional economic growth effect, the consistency test results of evaluation indexes are not accurate, which leads to the phenomenon of “pseudo regression” in the evaluation model, so the application of discrete mathematics in the evaluation model of regional economic growth effect is proposed. Based on the selection principle of regional economic growth effect index put forward in the literature, the evaluation index of regional economic growth effect is determined to measure the location entropy existing in the evaluation index; to deal with the difference of evaluation index data, KMO test and Bartley sphericity test are adopted. Besides the evaluation index layer of economic distribution standard, the test results show that the evaluation index data is suitable for factor analysis method. The evaluation index weight is calculated, and the regional economic growth effect evaluation model is established to evaluate the regional economic growth effect by using the compactness of the combination of discrete mathematics and data and the characteristics of its discretization.