Population Size and Home Range Estimates of Domestic Cats (Felis catus) on Mara Islet, Jeju, in the Republic of Korea (제주 마라도에 서식하는 고양이(Felis catus)의 개체군 크기 및 행동권 추정)
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- Korean Journal of Environment and Ecology
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- v.34 no.1
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- pp.9-17
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- 2020
Domestic cats (Felis catus) introduced to insular environments can be invasive predators that often threaten endemic species and cause biodiversity loss or local extinction on the island. This study was conducted from March to July 2018 to understand the population size, home range, and spatial use of cats introduced to Mara Islet (N 33° 07', E 126° 16') in Jeju Special Governing Province, the Republic of Korea. Observation records based on their natural marks revealed that there were 20 adult cats on Mara Islet. A capture-recapture method also estimated 20 adult individuals (95% confidence interval: 20-24 individuals). According to our telemetry study on ten adults deployed with GPS-based telemetry units, the home range size was 12.05±6.99 ha (95% KDE: kernel density estimation), and the core habitat size was 1.60±0.77 ha (50% KDE). There were no significant differences in the home range and core habitat sizes by sex. The home range of domestic cats overlapped with the human residential area, where they might secure easy foods. Five of ten tracked cats were active at potential breeding colonies for the Crested Murrlet (Synthliboramphus wumizusume), and six approached potential breeding areas of the Styan's Grasshopper Warbler (Locustella pleskei), suggesting the predation risk of the two endangered species by cats. This study provides novel information on the population size and home range of introduced cats on Mara Islet which is an important stopover site of migratory birds as well as a breeding habitat of the two endangered avian species. Reducing the potential negative impacts of the introduced cats on migratory birds and the endangered species on Mara Islet requires monitoring of the predation rate of birds by cats, the population trends of cats and endangered breeding birds as well as the effective cat population control and management.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
Globally, 1.3 million people develop colon cancer every year, and 600,000 people die each year it. In Korea, colorectal carcinoma was associated with the highest death rate, accounting for 8,380 people, among solid cancers in 2015. Among the various methods for the diagnosis and study of colorectal carcinoma, the results obtained by cytogenetic and molecular genetic methods were compared. Detection rate was 47% in 18q, 40% in 17p, 27% in 22q, and 17% in 10q via CGH; detection rate was 57% in D18S59, 50% in D18S68, 50% in TP53CA, 47% in D18S6940% in D22S274, 37% in D22S283, 27% in D10S187, and 23% in D10S541 with LOH. Microsatellite marker matching rates were 100% in D22S274, 100% in D22S283, 100% in D10S186, 100% in D10S187, 100% in D10S541, 93% in D18S69, 93% in D18S68, 92% in TP53CA, and 89% in D18S59. The agreement rate between the two methods was 94.4% based on positive results using CGH. Based on the advantages of CGH, which was the ability to obtain information regarding the entire tumor genome at once, this experiment could identify the region with significant deletion using CGH and the more limited region LOH, with a completely different approach. LOH in the recurrent high-risk group, 18q21, was helpful in the selection of treatment modalities and in prognostic estimation as well as making the most appropriate decision for treatment. Therefore, it is suggested that LOH with surgical site tissues could be one of the treatment methods for recurrent high-risk group among patients with colorectal carcinoma.
As Mt. Backdu is expected to erupt, the social and economic impacts of the eruption on the Korean peninsula as well as on the world become a research topic of interest. If the volcano erupts, South Korea can be directly impacted by volcanic ash, which will bring out secondary damages in various ways. Given that the direct damage is a basis to estimate indirect and secondary damages, this paper was to review a method to estimate direct damages, called catastrophe risk models, and estimate the direct damages of available eruption scenarios of Mt. Baekdu. Based on the results, the damages by volcanic ash will occur mostly around Gangwon province if the Mt. Backdu erupts. Thus the inventory lists and their damage functions of Gangwon provinces were collected. In particular agricultural and forestry products were surveyed based on the land use. Direct damages were estimated using volcanic ash distribution of eruption scenarios, inventory information and their damage functions. In result, a scenario in winter caused the damage of 299.8 billion KRW (20.4% of total agricultural production in 2010) and 28.9 billion KRW (9.0% of total forestry production in 2010) in agriculture and forestry, respectively. The damages in agriculture was larger, and it is due to the damage functions which show the agricultural products are more vulnerable to volcanic ash than forestry products. Also the agricultural production (1,471.7 billion KRW in 2010) are more than 4.5 times the forestry production (322.3 billion KRW in 2010) in Gangwon province. Inje and Gangnung had the most damages in the scenario in winter. Inje had the most damage due to the thick ash deposit (8.5 mm in average) despite the low production. On the other hand, Goseong had a low damage compared to the ash thickness larger than 20mm, owing to the low production. The direct damage estimated through this process can be used to estimate indirect damages.
This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.
Manganese is an essential element in the body. It is mainly deposited in the liver and to a lesser degree in the basal ganglia of the brain and eliminated through the bile duct. Rapid turnover of managanese in the body makes it difficult to evaluate the manganese exposure in workers, esecially in those with irregular or intermittent exposure, like welders. Therefore, conventional biomarkers, including blood and urine manganese can provide only a limited information about the long-tern or cumulative exposure to manganese. Introduction of magnetic resonance imaging (MRI) made a progress in the assessment of manganese exposure in the medical conditions related to manganese accumulation, e. g. hepatic failure and long-term total parenteral nutrition. Manganese shortens spin-lattice(T1) relaxation time on MRI due to its paramagnetic property, resulting in high signal intensity (HSI) on T1-weighted image(T1W1) of MRI. Manganese deposition in the brain, therefore, can be visualizedas an HSI in the globus pallidus, the substantia nigra, the putamen and the pituitary. clinical and epidemiologic studies regarding the MRI findings in the cases of occupational and non-occupational manganese exposure were reviewed. relationships between HSI on T1W1 of MRI and age, gender, occupational manganese exposure, and neurological dysfunction were analysed. Relationships betwen biological exposure indices and HSI on MRE werealso reviewed. Literatures were reviewed to establish the relationships between HSI, Manganese deposition in the brain, pathologic findings, and neurological dysfunction. HSI on T1W1 of MRI reflects regional manganese deposition in the brain. This relationship enables an estimation of regional manganese deposition in the brain by analysing MR signal intensity. Manganese deposition in the brain can induce a neuronal loss in the basal ganglia but functional abnormality is supposed to be related to the cumulative exposure of manganese in the brain, use of brain MRI for the assessment of exposure in a group of workers seems to be hardly rationalized, while ti can be a useful adjunct for the evaluation of manganese exposure int he cases with suspected manganese-related health problems.
Surface air temperature (