Multimodal Magnetic Resonance and Near-Infrared-Fluorescent Imaging of Intraperitoneal Ovarian Cancer Using a Dual-Mode-Dual-Gadolinium Liposomal Contrast Agent.

The degree of tumor removal at surgery is a major factor in predicting outcome for ovarian cancer. A single multimodality agent that can be used with magnetic resonance (MR) for staging and pre-surgical planning, and with optical imaging to aid surgical removal of tumors, would present a new paradigm for ovarian cancer. We assessed whether a dual-mode, dual-Gadolinium (DM-Dual-Gd-ICG) contrast agent can be used to visualize ovarian tumors in the peritoneal cavity by multimodal MR and near infra-red imaging (NIR). Intraperitoneal ovarian tumors (Hey-A8 or OVCAR3) in mice enhanced on MR two days after intravenous DM-Dual Gd-ICG injection compared to controls (SNR, CNR, p < 0.05, n = 6). As seen on open abdomen and excised tumors views and confirmed by optical radiant efficiency measurement, Hey-A8 or OVCAR3 tumors from animals injected with DM-Dual Gd-ICG had increased fluorescence (p < 0.05, n = 6). This suggests clinical potential to localize ovarian tumors by MR for staging and surgical planning, and, by NIR at surgery for resection

Technical solutions of ventilation schemes in inhabited and public buildings with external fences of the raised tightness

In the work are presented possible variants of technological schemes for an effective utilization in systems of ventilation of high-rise buildings with external protecting designs of the raised tightness to which the preference is given systems combined heat and air delivery, combined with ventilation

Flood Prediction using MLP, CATBOOST and Extra-Tree Classifier

Flooding can be one of the many devastating natural catastrophes, resulting in the annihilation of life and damaging property. Additionally, it can harm farmland and kill growing crops and trees. Nowadays, rivers and lakes are being destroyed, and the natural water reservoirs are converted into development sites and buildings. Due to this, even just a bit of rain can cause a flood. To minimize the number of fatalities, property losses, and other flood-related issues, an early flood forecast is necessary. Therefore, machine learning methods can be used for the prediction of floods.To forecast the frequency of floods brought on by rainfall, a forecasting system is built using rainfall data. The dataset is trained using various techniques like the MLP classifier, the CatBoost classifier, and the Extra-Tree classifier to predict the occurrence of floods. Finally, the three models' performances are compared and the best model for flood prediction is presented. The MLP, Extra-Tree, and CatBoost models achieved accuracy of 94.5%, 97.9%, and 98.34%, respectively, and it is observed that CatBoost performed well with high accuracy to predict the occurrence of floods

Density asymmetry and wind velocities in the orbital plane of the symbiotic binary EG Andromedae

Context. Non-dusty late-type giants without a corona and large-scale pulsations represent objects that do not fulfil the conditions under which standard mass-loss mechanisms can be applied efficiently. The driving mechanism of their winds is still unknown. Aims. The main goal of this work is to match the radial velocities of absorbing matter with a depth in the red giant (RG) atmosphere in the S-type symbiotic star EG And. Methods. We measured fluxes and radial velocities of ten FeI absorption lines from spectroscopic observations with a resolution of ~30 000. At selected orbital phases, we modelled their broadened profiles, including all significant broadening mechanisms. Results. The selected FeI absorption lines at 5151 - 6469A, originate at a radial distance ~1.03 RG radii from its centre. The corresponding radial velocity is typically ~1 km/s , which represents a few percent of the terminal velocity of the RG wind. The high scatter of the radial velocities of several km/s in the narrow layer of the stellar atmosphere points to the complex nature of the near-surface wind mass flow. The average rotational velocity of 11 km/s implies that the rotation of the donor star can contribute to observed focusing the wind towards the orbital plane. The orbital variability of the absorbed flux indicates the highest column densities of the wind in the area between the binary components, even though the absorbing neutral material is geometrically more extended from the opposite side of the giant. This wind density asymmetry in the orbital plane region can be ascribed to gravitational focusing by the white dwarf companion. Conclusions. Our results suggest that both gravitational and rotational focusing contribute to the observed enhancement of the RG wind towards the orbital plane, which makes mass transfer by the stellar wind highly efficient.Comment: 12 pages, 10 figure