Texture and color enhancement imaging (TXI) may improve the visibility of gastric tumors and allow their early detection. However, few reports have examined the utility of TXI. Between June 2021 and October 2022, 56 gastric tumors in 51 patients undergoing endoscopic submucosal dissection at Fukuchiyama City Hospital were evaluated preoperatively using conventional white light imaging (WLI), narrow-band imaging (NBI), and TXI modes 1 and 2. The color differences of the tumors and surrounding mucosae were evaluated using the CIE 1976 L*a*b color space, Additionally, the visibility scores were scaled. Of the 56 gastric tumors, 45 were early gastric cancers, and 11 were adenomas. Overall, the color difference in TXI mode 1 was considerably higher compared to WLI (16.36 ± 7.05 vs. 10.84 ± 4.05; p < 0.01). Moreover, the color difference in early gastric cancers was considerably higher in TXI mode 1 compared to WLI, whereas no significant difference was found in adenomas. The visibility score in TXI mode 1 was the highest, and it was significantly higher compared to WLI. Regarding adenomas, the visibility score in TXI mode 1 was also significantly higher compared to that in WLI. TXI may provide improved gastric tumor visibility.

In this study, six individual machine learning (ML) models and a stacked ensemble model (SEM) were used for daytime visibility estimation at Bangkok airport during the dry season (November-April) for 2017-2022. The individual ML models are random forest, adaptive boosting, gradient boosting, extreme gradient boosting, light gradient boosting machine, and cat boosting. The SEM was developed by the combination of outputs from the individual models. Furthermore, the impact of factors affecting visibility was examined using the Shapley Additive exPlanation (SHAP) method, an interpretable ML technique inspired by the game theory-based approach. The predictor variables include different air pollutants, meteorological variables, and time-related variables. The light gradient boosting machine model is identified as the most effective individual ML model. On an hourly time scale, it showed the best performance across three out of four metrics with the ρ = 0.86, MB = 0, ME = 0.48 km (second lowest), and RMSE = 0.8 km. On a daily time scale, the model performed the best for all evaluation metrics with ρ = 0.92, MB = 0.0 km, ME = 0.3 km, and RMSE = 0.43 km. The SEM outperformed all the individual models across three out of four metrics on an hourly time scale with ρ = 0.88, MB = 0.0 km, (second lowest), and RMSE = 0.75 km. On the daily scale, it performed the best with ρ = 0.93, MB = 0.02 km, ME = 0.27 km, and RMSE = 0.4 km. The seasonal average original (VISorig) and meteorologically normalized visibility (VISnorm) decrease from 2017 to 2021 but increase in 2022. The rate of decrease in VISorig is double than rate of decrease in VISnorm which suggests the effect of meteorology visibility degradation. The SHAP analysis identified relative humidity (RH), PM2.5, PM10, day of the season year (i.e., Julian day) (JD), and O3 as the most important variables affecting visibility. At low RH, visibility is not sensitive to changes in RH. However, beyond a threshold, a negative correlation between RH and visibility is found potentially due to the hygroscopic growth of aerosols. The dependence of the Shapley values of PM2.5 and PM10 on RH and the change in average visibilities under different RH intervals also suggest the effect of hygroscopic growth of aerosol on visibility. A negative relationship has been identified between visibility and both PM2.5 and PM10. Visibility is positively correlated with O3 at lower to moderate concentrations, with diminishing impact at very high concentrations. The JD is strongly negatively related to visibility during winter while weakly associated positively later in summer. Findings from this research suggest the feasibility of employing machine learning techniques for predicting visibility and understanding the factors influencing its fluctuations.

OBJECTIVE: This study aims to evaluate the effectiveness of the Piezosurgery® device in endoscopic-assisted correction of trigonocephaly. Trigonocephaly is a type of craniosynostosis characterized by a triangular-shaped forehead due to the premature fusion of the metopic suture. Traditional open cranial vault reconstruction, although common, is invasive and poses risks. The study explores a less invasive alternative using ultrasonic microvibrations for bone cutting, potentially reducing soft tissue damage and improving surgical outcomes.
METHODS: The Piezosurgery® device was employed in endoscopic trigonocephaly correction surgeries performed on patients under 4 months old at the French Referral Center for Craniosynostosis in Lyon. The technique involves making a small skin incision and performing osteotomies from the anterior fontanel to the glabella. A rigid 0° endoscope provides visibility, and the Piezosurgery® device enables precise bone cutting while preserving the dura mater. Post-surgery, patients were discharged within 3 days and required to wear a remodeling helmet for 6-8 months.
RESULTS: The use of Piezosurgery® device allowed precise osteotomies with minimal soft tissue damage. No dura mater injuries occurred in the patient series. The procedure was efficient, with an average duration of 80 min, and blood loss was minimal, reducing the need for blood transfusions. The endoscopic approach facilitated shorter surgical times and reduced postoperative infection risks. Enhanced visibility during surgery, due to cavitation effects, improved the accuracy of bone cuts. The technique demonstrated promising safety and esthetic outcomes, although it incurred higher costs compared to traditional methods.
CONCLUSIONS: Piezosurgery® device provides a safe and effective method for minimally invasive endoscopic correction of trigonocephaly. The device\'s ability to selectively cut bone while preserving soft tissues offers significant advantages, despite longer surgical times and higher costs. This technique represents a viable alternative to traditional open surgery, promoting better clinical outcomes and reduced recovery times.

The growing visibility of the LGBTQ community and the demand for their rights, also in the educational context, have led, among other things, to a higher focus on the experiences of teachers and the role they play when facing homophobia and promoting diversity and respect. In this sense, lesbian, gay and bisexual (LGB) teachers could experience their sexual orientation and its visibility as a problem. However, specific knowledge about these experiences is limited, also in Physical Education (PE). This study explores these experiences through data collected from 24 in-depth interviews with Primary and Secondary LGB PE teachers in Spain. The results align with the international literature, highlighting that disclosing their sexual orientation is a key aspect of participants\' experience. Although teachers agree on the advantages of \"coming out of the closet,\" LGB PE teachers define their strategies based on contextual elements such as fear of the families\' reaction, the type of school, or the training received. They develop strategies such as ignoring homophobic acts, reacting against them, or using them educationally. Overall, homophobia in the educational context affects them emotionally. As a conclusion, it is essential to improve training, engage allies, and involve the entire educational community in the fight against homophobia.

Flower colour is an important mediator of plant-pollinator interactions. While the reflectance of light from the flower surface and background are governed by physical properties, the perceptual interpretation of such information is generated by complex multilayered visual processing. Should quantitative modelling of flower signals strive for repeatable consistency enabled by parameter simplification, or should modelling reflect the dynamic way in which bees are known to process signals? We discuss why colour is an interpretation of spectral information by the brain of an animal. Different species, or individuals within a species, may respond differently to colour signals depending on sensory apparatus and/or individual experience. Humans and bees have different spectral ranges, but colour theory is strongly rooted in human colour perception and many principles of colour vision appear to be common. We discuss bee colour perception based on physiological, neuroanatomical and behavioural evidence to provide a pathway for modelling flower colours. We examine whether flower petals and floral guides as viewed against spectrally different backgrounds should be considered as a simple colour contrast problem or require a more dynamic consideration of how bees make perceptual decisions. We discuss that plants such as deceptive orchids may present signals to exploit bee perception, whilst many plants do provide honest signalling where perceived saturation indicates the probability of collecting nutritional rewards towards the centre of a flower that then facilitates effective pollination.

Research on air pollution, one of the most common environmental factors, has primarily focused on its effects on physical, mental, and cognitive health. However, air pollution-induced achromatic color of an environment, which is a prominent feature of air pollution, has received little attention. This study explored the visual effects of air pollution on the variety-seeking purchase behavior of consumers through two scenario-based experiments and primed manipulation (Study 1 and Study 2) and one natural experiment using data from a local fruit chain store (Study 3). Study 1 tested the main effect of air pollution on the variety-seeking behavior and found that primed air pollution increased variety-seeking when consumers purchased beverages. Study 2 broadened the category and tested the mechanism, and the results indicated that primed air pollution increased the variety of purchased chocolates and demonstrated the mediating effect of the need for arousal. Study 3 tested the boundary condition and extended the external validity with actual purchases. The results revealed that severe air pollution increased the purchased SKUs by 22.9% and visibility reduced the moderation effect. This research extended the literature on the visual effect of air pollution by providing evidence of the effects of air pollution on variety-seeking behavior through the need for arousal. And, product managers could leverage the results by offering a greater variety of goods on days with air pollution to increase sales.

暂无摘要。

Aerosol liquid water content (ALWC) affects the mass loading, optical properties, and toxicity of aerosols. However, the measurement of ALWC is very rare due to its requirement of sophisticated instruments and its high operational costs. In this work, we improved on our previous simple, low-cost method by using a combination of one real-time fine particulate matter (PM2.5) monitor and two turbidimeters and successfully applied these for the direct measurement of ALWC in PM2.5 in Nanjing during the summer of 2023. The average ALWC during this measurement period occupied ~1/6 of the total PM2.5 mass, and this contribution was even greater with the elevation in the PM2.5 concentration. The ALWC was, as anticipated, closely related to the relative humidity (RH) and PM2.5 concentrations, but it did not always increase with the air quality index (AQI) due to the fact that polluted periods in summer were often governed by high O3 levels, not PM2.5 levels. The ALWC also had a great impact on visibility; it could decrease the visibility rapidly to hazy conditions when the dry PM2.5 was not high (~30 μg m-3) or the AQI was \"good\" (75~100), indicating that the air quality classified as \"good\" using the dry PM2.5 concentration might actually be \"lightly polluted\" if the ALWC is included. We also found that the air mass originating from Northeast China had the lowest PM2.5 mass concentration yet the highest ALWC values due to its high RH. Moreover, the quantification of ALWC levels can help us understand the solubility/bioavailability and thus the toxic effects of some specific components (for example, heavy metals or organics). Moreover, the influence of ALWC on air quality classifications should also be considered in the assessment of the health effects of air pollution and in public health early warning and protection.

BACKGROUND: Elderly nursing home residents are vulnerable to infection from micro-organisms. Hand hygiene is considered one of the most important measures to prevent transmission.
OBJECTIVE: To determine the effect of increased accessibility to alcohol-based hand rub (ABHR) in nursing home wards by monitoring hand hygiene compliance (HHC) among healthcare workers (HCWs).
METHODS: An 11-month intervention study was conducted in a Danish six-ward nursing home. Data were collected using an automatic hand hygiene monitoring system (AHHMS). After a baseline period, one extra ABHR dispenser was placed in each of the 150 apartments. Baseline HHC was compared with the HHC during an immediate intervention period and a long-term intervention period.
RESULTS: A total of 159 HCWs were included. The AHHMS registered 341,078 hand hygiene opportunities. Overall baseline HHC was 31% (95% confidence interval: 30-32). A significant +18% absolute immediate effect (first five months) (95% CI: 17-19; P < 0.0001) and +13 percentage points (95% CI: 11-14; P < 0.0001) long-term effect (another four months) were recorded. HCWs working day shifts and short-term employees had a higher baseline HHC than HCWs working evening/night shifts. However, HCWs working night shifts achieved the greatest long-term effect with a mean +27 percentage point difference (P < 0.0001).
CONCLUSIONS: Placing an additional ABHR dispenser strategically within staff workflow significantly increased HHC among HCWs, demonstrating a noteworthy effect. The study is the first to report the effect on nursing home dispenser accessibility as a single intervention and to show a significant unmet potential.

Building fires can be considered a risk to the health and safety of occupants. Environmental factors in building fires might affect the speed of an evacuation. Therefore, in this study participants (N = 153) were tested in an experimental design for the effects of (1) a fire alarm, (2) darkness and (3) the use of emergency exit signs on building evacuation time. In addition, the effects of age and gender on evacuation time were investigated. The main results indicate that the combination of a fire alarm, darkness and not illuminated emergency exit signs had a significant negative influence on evacuation time, namely an increase in evacuation time of 26.6% respectively 28.1%. Another important finding is that age had a significant negative effect on evacuation time. The increase in evacuation time was at least 30.4% for participants aged 56 years or older compared to participants aged 18-25 years. For gender no significant effect was found. Building and safety managers can use these results by including longer evacuation time considerations - based on darkness and older age - in their evacuation plans. Future research should focus further on investigating the effects of personal and psychological characteristics on evacuation behaviour and evacuation time.