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We investigate the relationship between the thermal properties of a micro pulsating heat pipe (MPHP) and the internal flow characteristics. The MPHP consists of an eleven-turn closed-loop of a meandering square microchannel with a hydraulic diameter of $350\ {}μ{\rm m}$ engraved on a silicon substrate. The MPHP charged with Fluorinert FC-72 tends to exhibit higher effective thermal conductivities for the coolant temperature of $T_{\rm c} = 40\ {}^\circ\mathrm{C}$ compared to $T_{\rm c} = 20\ {}^\circ\mathrm{C}$, and provides the highest effective thermal conductivity of about $700\ {}{\rm W/(m{\cdot}K)}$ for $T_{\rm c} = 40\ {}^\circ\mathrm{C}$ and a filling ratio of 48%. Interestingly, we observe two different self-oscillation modes having different thermal conductivities, even for identical heat input rates. This tendency indicates a hysteresis of the effective thermal conductivity, which originates from the difference in the heat input rates at which the MPHP falls into and recovers from dryout. Subsequently, semantic segmentation-based image recognition is applied to the recorded flow images to identify the flow characteristics, successfully extracting four different flow patterns involving liquid slugs, liquid films, dry walls, and rapid-boiling regions. The image recognition results indicate that high effective thermal conductivities of the MPHP relate to stable self-oscillations with large amplitudes and high frequencies, along with long and thin liquid films beneficial for latent heat transfer. Finally, we perform numerical simulations of latent/sensible heat transfer via vapor plugs and of sensible heat transfer via liquid slugs using the extracted flow patterns as inputs. We find that latent heat transfer via liquid films accounts for a considerable portion of the overall heat transfer, while the sensible heat transfer via liquid slugs is much less significant.