ความผันแปรของการเข้าสู่พื้นที่ของหอยสองฝาต่างถิ่น Mytilopsis adamsi Morrison, 1946 บริเวณหาดแก้วลากูน จังหวัดสงขลา

Thesis (M.Sc., Ecology)--Prince of Songkla University, 200

The influence of mussel-modified habitat on Fucus serratus L. a rocky intertidal canopy-forming macroalga

The influence of habitat modification by Mytilus edulis L. on the settlement and development of Fucus serratus populations was investigated on rocky shores of the Isle of Anglesey, North Wales. Settlement of fucoids was higher inside mussel habitat than outside on one of two shores studied. The effect of microhabitat on survival of fucoid germlings was examined by transplanting the germlings into and outside mussel habitats, each with and without the exclusion of grazers. Observation showed that periwinkles and top shells were abundant in mussel habitat, while limpets dominated bare rock. Exclusion of grazers greatly enhanced the survival of fucoid germlings in both habitats, indicating that while mussel habitat supports a different grazer assemblage to bare rock, both assemblages are important in limiting fucoid recruitment. The risk of dislodgement was assessed and compared between fucoids growing on mussel shells and bare rock. In situ pull-tests showed that less force was required to detach large fertile thalli growing on mussel shells than those growing on the rock. Adhesion was generally broken between the mussel and the rock rather than between the holdfast and the mussel. These observations indicate that mussels provide an unstable substrate for mature fucoids. Overall results suggest that a negative effect of mussel-modified habitat on fucoids is profound in adults; but the effect is context-dependent in juveniles and can be positive at settlement. Results from a survey on population structure of fucoids across two shores showed that there were greater numbers of large fertile fucoids growing directly attached to rock than on mussel shells, while there was no difference for juvenile fucoids confirming the experimental results. Moreover thalli larger than 60 cm were found only on the rock but not on shells. This finding suggests that a mussel dominated habitat may have a significant impact on reproductive output in fucoid populations

Community level effects of variable recruitment of a key species Mytilus edulis L. in the rocky intertidal

Variation in recruitment is known to affect species demography and population dynamics. There is scant information, however, on how variation in recruitment influences community composition and processes. In the rocky intertidal, mytilid mussels have long been recognised as an important foundation species which can influence the dynamics of the entire community. Although numerous studies have demonstrated the effects of recruitment and post-recruitment processes on structure and dynamics of mussel populations, as well as the effect of mussels as a habitat engineering on community of rocky shores, the understanding of how variation in mussel recruitment might affect community level structure and processes remains unclear. In this Ph.D. research project I used the mussel Mytilus edulis L. as a model species to investigate the effects of variation in recruitment and post-recruitment processes on adult abundance and distribution on rocky shores around the Isle of Anglesey, North Wales, an area known for intense spatial variation in recruitment. I also examined how community composition of key taxa varied in relation to the presence of mussel-modified habitat. Particular emphasis was placed on how mussel-modified habitat influences the abundance and distribution of the dominant canopy-forming fucoid algae Fucus serratus L. which occupies a similar position on the low shore as mussel beds.Recruitment appeared to be a determinant of adult abundance and distribution at the mesoscale (1000s of metres) but not at the smaller, within-shore scale (10s of metres). The relative abundance of adult mussels among three geographically defined coastlines of Anglesey (west, north, and east) reflected the abundance of the recruits. The absence of mussel beds on the west coast of the island can be explained by a combination of low levels of recruitment, poor food supply, probably poor environmental condition, and intense predation. At the community level, community composition varied according to the existence of mussel-modified habitat at different scales. The difference was significant at 1000s of metre scale, significant in one of the two years studied at 100s of metre scale, and not significant at 10s of centimetre scale. Abundance of sessile taxa on primary substrates was lower where mussel habitat dominates, while abundance of mobile species except limpets was higher in the presence of mussel habitat. For mussel-fucoid interactions, mussel habitat influenced fucoids of different life-history phases in different ways. A negative effect of mussel-modified habitat on fucoids was profound in adults but the effect was context-dependent in juveniles and can be positive at settlement. There was a greater number of large fertile fucoids growing directly attached to rock than on mussel shells. This suggests that mussel dominated habitat may have a significant impact on reproductive output in fucoid populations as the abundance of reproducing thalli was reduced. Overall, a series of surveys and experiments in my thesis demonstrates that recruitment of the foundation species M. edulis is an important determinant for community composition on rocky shore

Temperature-Dependent Sex Determination of Green Turtle, Chelonia Mydas, in the Andaman Sea

February 20-21, 2012, BANGKOK, THAILANDA study on the effect of incubation temperature on sex determination of green turtle, Chelonia mydas, was conducted at Hu-Yong Island, a member of the Similan Islands National Park, in the Andaman Sea. Five nests were collected in March 2009 and relocated to the nesting area. Incubation temperatures from each nest were recorded every 30 minutes using temperature data loggers fixed into the middle of each nest. Sexes of dead hatchlings were determined using a tissue histological method. The results showed that the incubated temperature of all nests ranged between 27.96 – 35.86 OC, while the mean temperatures taken during the middle third period of each nest ranged from 29.11 ± 0.41OC to 30.67 ± 0.73OC. The warmest incubation temperature (30.67 ± 0.73oC) produced 94.12% female turtles, while the coolest incubation temperature (29.11 ± 0.41oC) produced 63.64% females. Thesex ratio of the green turtle at Hu-Yong Island during dry season was 4 females to 1 male

Strong genetic subdivision in Leptobrachium hendricksoni (Anura: Megophryidae) in Southeast Asia

Many biodiversity hotspots are located in areas with a complex geological history, like Southeast Asia, where species diversity may still be far underestimated, especially in morphologically conservative groups like amphibians. Recent phylogenetic studies on the frog genus Leptobrachium from Southeast Asia revealed the presence of deeply divergent mitochondrial clades in Leptobrachium hendricksoni from Malaysia and Sumatra but populations from Thailand have not been studied so far. In this study, we re-evaluate patterns of intraspecific genetic diversity in L. hendricksoni based on the analysis of combined sequences of mitochondrial 12S and 16S genes (1310 base pairs) including for the first time samples from southern Thailand. Thai populations of L. hendricksoni formed a distinct clade with respect to populations from central and southern Malaysia and Sumatra. High sequence divergence between lineages from Thailand, Malaysia and Sumatra suggests the possible presence of cryptic species in L. hendricksoni. Divergence within L. hendricksoni dates back to the late Miocene, around 6 Mya, when lineages from Thailand, north Malaysia and Sumatra split from a lineage in south Malaysia, at about the same time as rising sea levels isolated the Thai-Malay peninsula. Subsequent splits took place later in the Pliocene, around 4.5 and 2.6 Mya. Our results highlight the role of geological history in promoting population divergence and speciation.We would like to thank Graduate School, Prince of Songkhla University, Hat Yai, Thailand for providing Thesis Financial Support (Graduate School, 2015). This research would not be possible without National Park, Wildlife and Plant Conservation Department from Thailand, who kindly provided the permit for Conducting Study/Research in the Protected Areas. G. Draškić was supported by Balassi Insitute Scholarship of the Hungarian Scholarship Board Office, Budapest, Hungary. J. Vörös was supported by the Bolyai János Research Scholarship of the Hungarian Academy of Sciences (BO/00579/14/8).Peer Reviewe

AI-Assisted Assessment of Wound Tissue with Automatic Color and Measurement Calibration on Images Taken with a Smartphone

Wound assessment is essential for evaluating wound healing. One cornerstone of wound care practice is the use of clinical guidelines that mandate regular documentation, including wound size and wound tissue composition, to determine the rate of wound healing. The traditional method requires wound care professionals to manually measure the wound area and tissue composition, which is time-consuming, costly, and difficult to reproduce. In this work, we propose an approach for automatic wound assessment that incorporates automatic color and measurement calibration and artificial intelligence algorithms. Our approach enables the comparison of images taken at different times, even if they were taken under different lighting conditions, distances, lenses, and camera sensors. We designed a calibration chart and developed automatic algorithms for color and measurement calibration. The wound area and wound composition on the images were annotated by three physicians with more than ten years of experience. Deep learning models were then developed to mimic what the physicians did on the images. We examined two network variants, U-Net with EfficientNet and U-Net with MobileNetV2, on wound images with a size of 1024 × 1024 pixels. Our best-performing algorithm achieved a mean intersection over union (IoU) of 0.6964, 0.3957, 0.6421, and 0.1552 for segmenting a wound area, epithelialization area, granulation tissue, and necrotic tissue, respectively. Our approach was able to accurately segment the wound area and granulation tissue but was inconsistent with respect to the epithelialization area and necrotic tissue. The calibration chart, which helps calibrate colors and scales, improved the performance of the algorithm. The approach could provide a thorough assessment of the wound, which could help clinicians tailor treatment to the patient’s condition

Development of deep learning framework for anatomical landmark detection and guided dissection line during laparoscopic cholecystectomy

Background: Bile duct injuries during laparoscopic cholecystectomy can arise from misinterpretation of biliary anatomy, leading to dissection in improper areas. The integration of a deep learning framework into laparoscopic procedures offers the potential for real-time anatomical landmark recognition, ensuring accurate dissection. The objective of this study is to develop a deep learning framework that can precisely identify anatomical landmarks, including Rouviere's sulcus and the liver base of segment IV, and provide a guided dissection line during laparoscopic cholecystectomy. Methods: We retrospectively collected 40 laparoscopic cholecystectomy videos and extracted 80 images form each video to establish the dataset. Three surgeons annotated the bounding boxes of anatomical landmarks on a total of 3200 images. The YOLOv7 model was trained to detect Rouviere's sulcus and the liver base of segment IV as anatomical landmarks. Additionally, the guided dissection line was generated between these two landmarks by the proposed algorithm. To evaluate the performance of the detection model, mean average precision (mAP), precision, and recall were calculated. Furthermore, the accuracy of the guided dissection line was evaluated by three surgeons. The performance of the detection model was compared to the scaled-YOLOv4 and YOLOv5 models. Finally, the proposed framework was deployed in the operating room for real-time detection and visualization. Results: The overall performance of the YOLOv7 model on validation set and testing set were 98.1 % and 91.3 %, respectively. Surgeons accepted the visualization of guide dissection line with a rate of 95.71 %. In the operating room, the well-trained model accurately identified the anatomical landmarks and generated the guided dissection line in real-time. Conclusions: The proposed framework effectively identifies anatomical landmarks and generates a guided dissection line in real-time during laparoscopic cholecystectomy. This research underscores the potential of using deep learning models as computer-assisted tools in surgery, providing an assistant tool to accommodate with surgeons