Investigation on activation characterization, secondary electron yield, and surface resistance of novel quinary alloy Ti-Zr-V-Hf-Cu non-evaporable getters.

The performance of next-generation particle accelerators has been adversely affected by the occurrence of electron multipacting and vacuum instabilities. Particularly, minimization of secondary electron emission (SEE) and reduction of surface resistance are two critical issues to prevent some of the phenomena such as beam instability, reduction of beam lifetime, and residual gas ionization, all of which occur as a result of these adverse effects in next-generation particle accelerators. For the first time, novel quinary alloy Ti-Zr-V-Hf-Cu non-evaporable getter (NEG) films were prepared on stainless steel substrates by using the direct current magnetron sputtering technique to reduce surface resistance and SEE yield with an efficient pumping performance. Based on the experimental findings, the surface resistance of the quinary Ti-Zr-V-Hf-Cu NEG films was established to be 6.6 × 10-7 Ω m for sample no. 1, 6.4 × 10-7 Ω m for sample no. 2, and 6.2 × 10-7 Ω m for sample no. 3. The δmax measurements recorded for Ti-Zr-V-Hf-Cu NEG films are 1.33 for sample no. 1, 1.34 for sample no. 2, and 1.35 for sample no. 3. Upon heating the Ti-Zr-V-Hf-Cu NEG film to 150 °C, the XPS spectra results indicated that there are significant changes in the chemical states of its constituent metals, Ti, Zr, V, Hf, and Cu, and these chemical state changes continued with heating at 180 °C. This implies that upon heating at 150 °C, the Ti-Zr-V-Hf-Cu NEG film becomes activated, showing that novel quinary NEG films can be effectively employed as getter pumps for generating ultra-high vacuum conditions.

Predicting severity of acute appendicitis with machine learning methods: a simple and promising approach for clinicians.

BACKGROUNDS: Acute Appendicitis (AA) is one of the most common surgical emergencies worldwide. This study aims to investigate the predictive performances of 6 different Machine Learning (ML) algorithms for simple and complicated AA. METHODS: Data regarding operated AA patients between 2012 and 2022 were analyzed retrospectively. Based on operative findings, patients were evaluated under two groups: perforated AA and none-perforated AA. The features that showed statistical significance (p < 0.05) in both univariate and multivariate analysis were included in the prediction models as input features. Five different error metrics and the area under the receiver operating characteristic curve (AUC) were used for model comparison. RESULTS: A total number of 1132 patients were included in the study. Patients were divided into training (932 samples), testing (100 samples), and validation (100 samples) sets. Age, gender, neutrophil count, lymphocyte count, Neutrophil to Lymphocyte ratio, total bilirubin, C-Reactive Protein (CRP), Appendix Diameter, and PeriAppendicular Liquid Collection (PALC) were significantly different between the two groups. In the multivariate analysis, age, CRP, and PALC continued to show a significant difference in the perforated AA group. According to univariate and multivariate analysis, two data sets were used in the prediction model. K-Nearest Neighbors and Logistic Regression algorithms achieved the best prediction performance in the validation group with an accuracy of 96%. CONCLUSION: The results showed that using only three input features (age, CRP, and PALC), the severity of AA can be predicted with high accuracy. The developed prediction model can be useful in clinical practice.

The Effects of Different Anticavity Agents and Er:YAG Laser Usage on Enamel Surface Microhardness.

PURPOSE: The purpose of this study was to perform an in vitro evaluation of the protective effects of anticavity agents applied to enamel, by themselves and in combination with Er:YAG. MATERIALS AND METHODS: In this study 150 extracted third molars were used. Measurements were made using DIAGNOdent, and samples with scores of 0-13 were included in the study. These were divided into 15 groups (n = 20). Use of the agents sodium fluoride (NaF), tricalcium phosphate (Ca3PO4), titanium tetrafluoride (TiF4), Tooth Mousse (CPP-ACP), MI Paste Plus (CPP-ACP), and NovaMin (bioactive glass), individually and then in combination with Er:YAG laser, was assessed based on their effects on microhardness values. After treatment, the groups were exposed to a demineralisation solution. Statistical analyses were conducted using SPSS 20.0 package software. RESULTS: The highest test result value was observed in the TFL (TiF4/Er:YAG laser) group. Statistically significant differences were determined among all the groups (p <0.05). When the groups in which the agents were applied alone were compared with those involving combined use of Er:YAG laser, combined use provided significantly higher microhardness values, with the exception of the TML group (Tooth Mousse/Er:YAG laser) (p <0.05). CONCLUSION: Within the limits of this study, the combined use of remineralisation agents and Er:YAG laser elicited better results than using the agents alone. The most effective remineralisation agent was TiF4/Er:YAG laser, which may be considered an alternative method for protecting the enamel against demineralisation.