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The aim of this study was to quantitatively assess the residual adhesive on orthodontic ceramic bracket-removed dental surface. In orthodontic process, ceramic bracket was repeated debonding physically, then the adhesive remained on the dental surface. The residual adhesive caused a lack of adhesive strength between dental and ceramic bracket. Since commonly used adhesive in orthodontics is translucent, residual adhesive is hard to be detected with conventional microscopes. Therefore, 1310 nm center wavelength swept-source OCT system based on laboratory customized image processing algorithm was used for the precise detection of residual adhesive on tooth surface. The algorithm separates residual adhesive from dental surface by comparing the height of adjacent B-scan images, while providing color-scaled images emphasizing the thickness information of residual adhesive. Finally, the acquired results were compared with microscopic and adhesive remnant index scoring gold standards, while the comparison confirmed the potential merits and the improvements of the proposed method over gold standards.

Humans process a plethora of sensory information that is provided by various entities in the surrounding environment. Among the five major senses, technology for touch, haptics, is relatively young and has relatively limited applications largely due to its need for physical contact. In this article, we suggest a new way for non-contact haptic stimulation that uses laser , which has potential advantages such as mid-air stimulation, high spatial precision and long working distance. We demonstrate such tactile stimulation can be enabled by laser-induced thermoelastic effects by means of physical and perceptual studies, as well as simulations. In the physical study, the mechanical effect of laser on a human skin sample is detected using low-power radiation in accordance with safety guidelines. Limited increases (< ~2.5 °C) in temperature at the surface of the skin, examined by both thermal camera and the Monte Carlo simulation, indicate that laser does not evoke heat-induced nociceptive sensation. In the human EEG study, brain responses to both mechanical and laser stimulation are consistent, along with subjective reports of the non-nociceptive sensation of laser stimuli.

Freezing of gait (FOG), increasing the fall risk and limiting the quality of life, is common at the advanced stage of Parkinson's disease, typically in old ages. A simple and unobtrusive FOG detection system with a small calculation load would make a fast presentation of on-demand cueing possible. The purpose of this study was to find a practical FOG detection system. A sole-mounted sensor system was developed for an unobtrusive measurement of acceleration during gait. Twenty patients with Parkinson's disease participated in this study. A simple and fast time-domain method for the FOG detection was suggested and compared with the conventional frequency-domain method. The parameters used in the FOG detection were optimized for each patient. The calculation load was 1,154 times less in the time-domain method than the conventional method, and the FOG detection performance was comparable between the two domains (P=0.79) and depended on the window length (P<0.01) and dimension of sensor information (P=0.03). A minimally constraining sole-mounted sensor system was developed, and the suggested time-domain method showed comparable FOG detection performance to that of the conventional frequency-domain method. Three-dimensional sensor information and 3-4-second window length were desirable. The suggested system is expected to have more practical clinical applications.

By using gene expression data, gastric cancer is divided into subtypes associated with distinct molecular alterations and clinical prognosis. Gastric cancer, a leading cause of cancer-related deaths, is a heterogeneous disease. We aim to establish clinically relevant molecular subtypes that would encompass this heterogeneity and provide useful clinical information. We use gene expression data to describe four molecular subtypes linked to distinct patterns of molecular alterations, disease progression and prognosis. The mesenchymal-like type includes diffuse-subtype tumors with the worst prognosis, the tendency to occur at an earlier age and the highest recurrence frequency (63%) of the four subtypes. Microsatellite-unstable tumors are hyper-mutated intestinal-subtype tumors occurring in the antrum; these have the best overall prognosis and the lowest frequency of recurrence (22%) of the four subtypes. The tumor protein 53 (TP53)-active and TP53-inactive types include patients with intermediate prognosis and recurrence rates (with respect to the other two subtypes), with the TP53-active group showing better prognosis. We describe key molecular alterations in each of the four subtypes using targeted sequencing and genome-wide copy number microarrays. We validate these subtypes in independent cohorts in order to provide a consistent and unified framework for further clinical and preclinical translational research.

Pleural effusion and hypoalbuminaemia frequently occur after hepatectomy. Despite the emphasis on the safety of donors, little is known about the impact of postoperative albumin level on pleural effusion in liver donors. We retrospectively assessed 2316 consecutive liver donors from 2004 to 2014. The analysis of donors from 2004 to 2012 showed that postoperative pleural effusion occurred in 47.4% (970/2046), and serum albumin levels decreased until postoperative day 2 (POD2) and increased thereafter. In multivariable analysis, the lowest albumin level within POD2 (POD2ALB) was inversely associated with pleural effusion (OR 0.28, 95% CI 0.20–0.38; P  < 0.001). POD2ALB ≤3.0 g/dL, the cutoff value at the 75th percentile, was associated with increased incidence of pleural effusion after propensity score (PS) matching (431 pairs; OR 1.69, 95% CI 1.30–2.21; P  < 0.001). When we further analysed data from 2010 to 2014, intraoperative albumin infusion was associated with higher POD2ALB ( P  < 0.001) and lower incidence of pleural effusion ( P  = 0.024), compared with synthetic colloid infusion after PS matching (193 pairs). In conclusion, our data showed that POD2ALB is inversely associated with pleural effusion, and that intraoperative albumin infusion is associated with a lower incidence of pleural effusion when compared to synthetic colloid infusion in liver donors.

We inaugurate a program of “mass production” of microlensing planets discovered in 2021 KMTNet data, with the aim of laying the basis for future statistical studies. While we ultimately plan to quickly publish all 2021 planets meeting some minimal criteria, the current sample of four was chosen simply on the basis of having low initial estimates of the planet–host mass ratio, q. It is therefore notable that two members of this sample suffer from a degeneracy in the normalized source radius ρ that arises from different morphologies of closely spaced caustics. All four planets (KMT-2021-BLG-1391, KMT-2021-BLG-1253, KMT-2021-BLG-1372, KMT-2021-BLG-0748) have well-characterized mass ratios, q, and therefore are suitable for mass-ratio frequency studies. Both of the ρ degeneracies can be resolved by future adaptive optics (AO) observations on 30 m class telescopes. We provide general guidance for such AO observations for all events in anticipation of the prospect that they will revolutionize the field of microlensing planets.

We report a free-floating planet (FFP) candidate identified from the analysis of the microlensing event KMT-2023-BLG-2669. The lensing light curve is characterized by a short duration (≲3 days) and a small amplitude (≲0.7 mag). From the analysis, we find an Einstein timescale of t E ⋍ 0.33 days and an Einstein radius of θ E ⋍ 4.41 μas. These measurements enable us to infer the lens mass as M=8M⊕πrel/0.1mas−1 , where π rel is the relative lens–source parallax. The inference implies that the lens is a sub-Neptune- to Saturn-mass object, depending on its unknown distance. This is the ninth isolated planetary mass microlens with θ E < 10 μas, which is a useful threshold for an FFP candidate. We conduct extensive searches for possible signals of a host star in the light curve, but find no strong evidence for the host. We investigate the possibility of using late-time high-resolution imaging to probe for possible hosts. In particular, we discuss the case of finite-source point-lens FFP candidates, for which it would be possible to search for very-wide-separation hosts immediately, although such searches are “high risk, high reward.”

Planet-formation theories suggest the presence of free-floating planets (FFPs) that are ejected from their formation sites. While these planets emit very little light, they can be identified through gravitational microlensing. Here, we report the discovery of a FFP candidate in the microlensing event KMT-2024-BLG-3237. The observed light curve exhibits strong finite-source effects characterized by a small amplitude (≲0.9 mag) and a short timescale (≲3 days). The analysis yields an Einstein timescale of tE = 0.54 ± 0.02 days and an angular Einstein radius of θE = 6.30 ± 0.48 μas. The measurements make it possible to estimate the lens mass as M≃102M⊕(πrel/16μas)−1 , where πrel is the relative lens-source parallax. Depending on the unknown πrel, the lens could be a Neptune-mass planet (πrel ≃ 0.1 mas) or a Saturn-mass planet (πrel ≃ 16 μas). A Bayesian analysis yields the lens mass M=67.3−42.5+103.2M⊕ and the lens distance DL=7.34−2.11+0.96kpc . This lens is thirteenth isolated microlens with a measurement of θE < 10 μas. We find that additional searches for possible signatures of a lens host do not show significant evidence for the host.

To conduct a comprehensive demographic study of microlensing planets, it is essential to detect all planetary signals that exceed a predefined threshold through a detailed analysis of survey data. We reanalyzed previous data from the Korea Microlensing Telescope Network survey to search for weak planetary signals in lensing events involving faint source stars. For events with potential short-term anomalies identified in the initial search, we validated the signals using rereduced data and conducted detailed modeling of the anomalous events. This process led to the discovery of four planetary events: KMT-2017-BLG-2197, KMT-2022-BLG-1790, KMT-2022-BLG-2076, and KMT-2023-BLG-2209. For all these events, the modeling resulted in two solutions due to the well-known inner–outer degeneracy. The estimated masses of the planets and their hosts are approximately (Mp/MJ, Mh/M⊙) ∼ (0.36, 7.9) for KMT-2017-BLG-2197L, ∼(0.6, 1.7) for KMT-2022-BLG-1790L, ∼(0.67, 0.9) for KMT-2022-BLG-2076L, and ∼(0.73, 0.8) for KMT-2023-BLG-2209L. The planetary systems KMT-2017-BLG-2197L and KMT-2022-BLG-1790L are likely located in the Galactic bulge, while KMT-2022-BLG-2076L and KMT-2023-BLG-2209L are more likely situated in the disk.

Traditional microlensing event vetting methods require highly trained human experts, and the process is both complex and time consuming. This reliance on manual inspection often leads to inefficiencies and constrains the ability to scale for widespread exoplanet detection, ultimately hindering discovery rates. To address the limits of traditional microlensing event vetting, we have developed LensNet, a machine learning pipeline specifically designed to distinguish legitimate microlensing events from false positives caused by instrumental artifacts, such as pixel bleed trails and diffraction spikes. Our system operates in conjunction with a preliminary algorithm that detects increasing trends in flux. These flagged instances are then passed to LensNet for further classification, allowing for timely alerts and follow-up observations. Tailored for the multiobservatory setup of the Korea Microlensing Telescope Network and trained on a rich data set of manually classified events, LensNet is optimized for early detection and warning of microlensing occurrences, enabling astronomers to organize follow-up observations promptly. The internal model of the pipeline employs a multibranch Recurrent Neural Network architecture that evaluates time-series flux data with contextual information, including sky background, the full width at half-maximum of the target star, flux errors, point-spread function quality flags, and air mass for each observation. We demonstrate a classification accuracy above 87.5% and anticipate further improvements as we expand our training set and continue to refine the algorithm.