Genetic Structure and Diversity of Hatchery and Wild Populations of Yellow Catfish Tachysurus fulvidraco (Siluriformes: Bagridae) from Korea.

Yellow catfish Tachysurus fulvidraco is an important commercial fish species in South Korea. However, due to their current declines in its distribution area and population size, it is being released from hatchery populations into wild populations. Hatchery populations also produced from wild broodstocks are used for its captive breeding. We reported 15 new microsatellite DNA markers of T. fulvidraco to identify the genetic diversity and structure of its hatchery and wild populations, providing baseline data for useful resource development strategies. The observed heterozygosity of the hatchery populations ranged from 0.816 to 0.873, and that of the wild populations ranged from 0.771 to 0.840. Their inbreeding coefficient ranged from -0.078 to 0.024. All populations experienced a bottleneck (p < 0.05), with effective population sizes ranging from 21 to infinity. Their gene structure was divided into two groups with STRUCTURE results of K = 2. It was confirmed that each hatchery population originated from a different wild population. This study provides genetic information necessary for the future development and conservation of fishery resources for T. fulvidraco.

A map matching algorithm based on modified hidden Markov model considering time series dependency over larger time span.

With the advancement of geopositioning systems and mobile devices, much research with geopositioning data are currently ongoing. Along with the research applications, map matching is a technology that infers the actual position of error-prone trajectory data. It is a core preprocessing technique for trajectory data. Among various map matching algorithms, map matching using Hidden Markov Model (HMM) has gained high attention. However, the HMM model simplifies the dependency of time series data excessively, which leads to inferring incorrect matching results for various situations. For example, complex road relationships or movement patterns, such as in urban areas, or serious observation errors and sampling intervals make matching more difficult. In this research, we propose a new algorithm called trendHMM map matching, which complements the assumptions of HMM. This algorithm considers a wider range of dependencies of geopositioning data by incorporating the movements of neighboring data into the matching process. For this purpose, the concept of the window containing adjacent geopositioning data is introduced. Thus trendHMM can utilize relationships among continuous geopositioning data and showed considerable enhancement over HMM-based algorithm. Through experiments, we demonstrated that trendHMM map matching provides more accurate results than the existing HMM map matching for various environments and geopositioning data sets. Our trendHMM algorithm shows up to 17.58% of performance enhancement compared to HMM based one in terms of Route Mismatch Fraction.

A future location prediction method based on lightweight LSTM with hyperparamater optimization.

In this study, we presented a method for future location prediction based on machine learning over geopositioning data sets. There are large amounts of geopositioning data sets collected by mobile devices mainly due to modern geopositioning systems such as GPS, GLONASS and Galileo. Based on these geopositioning data sets, it is possible to have a wide variety of location-based services. These data sets can be used for future location prediction of objects, especially humans. Additionally, they have a high possibility for further applications. The purpose of this research is to present a simple and lightweight method that can be applicable to devices with lower computing capability devices, such as AIoT (Artificial Intelligence of Things) or EdgeML (Edge Machine Learning) devices. We introduced a basic LSTM (Long Short Term Memory) model with hyperparameter optimization, especially on window size of continuous geopositioning data, using limited previous geopositioning data for location prediction purposes. We found that the results of using our method for future location prediction are considerably fast and accurate compared with existing neural network-model-based approaches. We also applied our method to non-continuous geopositioning data sets and found it to be equally effective.

Characterization of the complete mitogenome of the endangered freshwater fish Gobiobotia naktongensis from the Geum River in South Korea: evidence of stream connection with the Paleo-Huanghe.

BACKGROUND: The freshwater fish Gobiobotia naktongensis (Teleostei, Cypriniformes, and Gobionidae) is an endangered class I species whose population size has been greatly reduced. OBJECTIVE: To successfully protect and restore the highly endangered freshwater fish G. naktongensis from the Geum River in South Korea. METHODS: The mitogenome was characterized using the primer walking method with phylogenetic relationships. RESULTS: The complete mitogenome of G. naktongensis Geum River was 16,607 bp, comprising 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA (tRNA) genes. Seventeen substitutions were found by comparing the tRNA regions between G. naktongensis Geum and Nakdong Rivers and G. pappenheimi; most were specific to G. naktongensis Nakdong River, with changes in their secondary structures. The comparison between G. naktongensis Geum River and G. pappenheimi revealed differences in the lengths of the D-loop and two tRNAs (tRNAArg and tRNATrp) and the secondary structures in the TΨC-arm of tRNAHis. In the phylogenetic tree, G. naktongensis Geum River did not cluster with its conspecific specimen from the Nakdong River in South Korea, but showed the closest relationship to G. pappenheimi in mainland China. CONCLUSIONS: Our results support the existence of the Paleo-Huanghe River connecting the Korean peninsula and mainland China, suggesting that G. naktongensis in the Geum River should be treated as a different evolutionarily significant unit separated from that in the Nakdong River. The complete mitogenome of G. naktongensis Geum River provides essential baseline data to establish strategies for its conservation and restoration.

Occurrence and characteristics of microplastics in fish of the Han River, South Korea: Factors affecting microplastic abundance in fish.

This study examined the abundance of microplastics (MPs) in 106 fish from 22 species inhabiting three sites of the Han River, South Korea. In total, 1753 MPs from 106 fish samples were identified with an average abundance of 15.60 ± 13.45 MPs per individual fish (MPs indiv-1) in the North Han River, 16.35 ± 12.32 MPs indiv-1 in the South Han River, and 20.14 ± 10.01 MPs indiv-1 in downstream of the Han River, indicating that the fish in the downstream of the Han River was the most contaminated by MPs. The dominant size of MPs detected in fish ranged between 0.1 and 0.2 mm, and the most common polymer types found in fish were polypropylene (PP) (≥40%) and polyethylene (PE) (≥23%), followed by polytetrafluoroethylene (PTFE) (≥16%) at all sampling locations. A significant correlation was observed between the log-transformed number of MPs with log-transformed fish length (p < 0.01) and with log-transformed fish weight (p < 0.01). The Kruskal-Wallis test disclosed a significant difference in the number of MPs among the feeding habits (p < 0.01), indicating that omnivorous and insectivorous fish contained more MPs than carnivorous and herbivorous fish. In addition, fish habitat result showed that pelagic fish contained a higher level of MPs than demersal fish, but no significant differences in the number of MPs among fish habitats were observed (p > 0.05).

Complete mitochondrial genome of the Korean endemic species Coreoleuciscus aeruginos holotype from Korea (Cypriniformes, Cyprinidae).

This study is the first to research report the complete 16,563 bp mitochondrial genome of Coreoleuciscus aeruginos, which consists of 13 protein-coding genes (PCGs), 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and a control region (D-loop). The overall base composition of the complete genome is 31.0% A, 28.04% T, 16.27% G, and 24.69% C, with a high A + T content of 59.04%. According to our phylogenetic analysis, C. aeruginos is most closely related to Coreoleuciscus splendidus.

The complete mitochondrial genome of Tachysurus nitidus (Siluriformes: Bagridae) from the Geum river in Korea.

The complete mitochondrial genome of a bagrid catfish, Tachysurus nitidus was completely analyzed by the primer walking method. It was composed of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, and a control region with a total length of 16,537 bp. In the phylogenetic tree, using mitochondrial genome of 13 related sequences revealed that T. nitidus (MW451217) of Korea is clustered with T. nitidus (KC822643) of China. This complete mitochondrial genome provides an important resource for reviewing the phylogenetic relationships and taxonomic status of the bagrid species.

Detecting Positioning Errors and Estimating Correct Positions by Moving Window.

In recent times, improvements in smart mobile devices have led to new functionalities related to their embedded positioning abilities. Many related applications that use positioning data have been introduced and are widely being used. However, the positioning data acquired by such devices are prone to erroneous values caused by environmental factors. In this research, a detection algorithm is implemented to detect erroneous data over a continuous positioning data set with several options. Our algorithm is based on a moving window for speed values derived by consecutive positioning data. Both the moving average of the speed and standard deviation in a moving window compose a moving significant interval at a given time, which is utilized to detect erroneous positioning data along with other parameters by checking the newly obtained speed value. In order to fulfill the designated operation, we need to examine the physical parameters and also determine the parameters for the moving windows. Along with the detection of erroneous speed data, estimations of correct positioning are presented. The proposed algorithm first estimates the speed, and then the correct positions. In addition, it removes the effect of errors on the moving window statistics in order to maintain accuracy. Experimental verifications based on our algorithm are presented in various ways. We hope that our approach can help other researchers with regard to positioning applications and human mobility research.

Coreoleuciscus aeruginos (Teleostei: Cypriniformes: Cyprinidae), a new species from the Seomjin and Nakdong rivers, Korea.

Coreoleuciscus splendidus was first reported as a monotypic species. Recent morphological and genetic studies have revealed that the species is represented by two disjunct and distinct lineages. The two lineages of C. splendidus include populations inhabiting the Han and Geum rivers in the East Korea Subdistrict and populations inhabiting the Seomjin and Nakdong rivers in the South Korea Subdistrict. In this study, significant differences were found between these two independent lineages through a high degree of genetic divergence in the mitochondrial cytochrome c oxidase subunit I gene as well as conspicuous morphological differences in body coloration and shapes of black stripes on dorsal, anal and caudal fin rays. These morphological and genetic differences provide supporting evidence that the populations in the South Korea Subdistrict represent a new species, Coreoleuciscus aeruginos.