Polygonizer: An auto-regressive building delineator

In geospatial planning, it is often essential to represent objects in a vectorized format, as this format easily translates to downstream tasks such as web development, graphics, or design. While these problems are frequently addressed using semantic segmentation, which requires additional post-processing to vectorize objects in a non-trivial way, we present an Image-to-Sequence model that allows for direct shape inference and is ready for vector-based workflows out of the box. We demonstrate the model's performance in various ways, including perturbations to the image input that correspond to variations or artifacts commonly encountered in remote sensing applications. Our model outperforms prior works when using ground truth bounding boxes (one object per image), achieving the lowest maximum tangent angle error.Comment: ICLR 2023 Workshop on Machine Learning in Remote Sensin

Feasibility and safety of PIPAC combined with additional surgical procedures: PLUS study.

PIPAC (Pressurized IntraPeritoneal Aerosol Chemotherapy) is a minimally invasive approach relying on physical principles for improving intraperitoneal drug delivery, including optimizing the homogeneity of drug distribution through an aerosol. Feasibility and safety of the new approach are now consolidated and data on its effectiveness are continuously increasing. Although any surgical procedure associated with PIPAC had always been discouraged due to the high risk of complications, surgical practice is constantly changing: with growing expertise, more and more surgical teams associate PIPAC with surgery. PLUS study is part of the retrospective international cohort studies including 10 centers around the world (India, Italy, France, Germany, Belgium, Russia, Saudi Arabia, Switzerland) and 96 cases of combined approaches evaluated through a propensity score analysis. the procedures most frequently associated with PIPAC were not only adhesiolysis, omentectomy, adnexectomy, umbilical/inguinal hernia repairs, but also more demanding procedures such as intestinal resections, gastrectomy, splenectomy, bowel repair/stoma creation. Although the evidence is currently limited, PLUS study demonstrated that PIPAC associated with additional surgical procedures is linked to an increase of surgical time (p < 0.001), length of stay (p < 0.001) and medical complication rate (p < 0.001); the most frequently reported medical complications were mild or moderate in severity, such as abdominal pain, nausea, ileus and hyperthermia. No difference in terms of surgical complications was registered; neither reoperation or postoperative deaths were reported. these results suggest that PIPAC can be safely combined in expert centers with additional surgeries. Widespread change of practice should be discouraged before the results of ongoing prospective studies are available

Consensus statement for treatment protocols in pressurized intraperitoneal aerosol chemotherapy (PIPAC)

Objectives: Safe implementation and thorough evaluation of new treatments require prospective data monitoring and standardization of treatments. Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is a promising alternative for the treatment of patients with peritoneal disease with an increasing number of suggested drug regimens. The aim was to reach expert consensus on current PIPAC treatment protocols and to define the most important research topics. Methods: The expert panel included the most active PIPAC centers, organizers of PIPAC courses and principal investigators of prospective studies on PIPAC. A comprehensive literature review served as base for a two-day hybrid consensus meeting which was accompanied by a modified three-round Delphi process. Consensus bar was set at 70% for combined (strong and weak) positive or negative votes according to GRADE. Research questions were prioritized from 0 to 10 (highest importance). Results: Twenty-two out of 26 invited experts completed the entire consensus process. Consensus was reached for 10/10 final questions. The combination of doxorubicin (2.1 mg/m(2)) and cisplatin (10.5 mg/m(2)) was endorsed by 20/ 22 experts (90.9%). 16/22 (72.7%) supported oxaliplatin at 120 with potential reduction to 90 mg/m(2) (frail patients), and 77.2% suggested PIPAC-Ox in combination with 5-FU. Mitomycin-C and Nab-paclitaxel were favoured as alternative regimens. The most important research questions concerned PIPAC conditions (n=3), standard (n=4) and alternative regimens (n=5) and efficacy of PIPAC treatment (n=2); 8/14 were given a priority of >= 8/10. Conclusions: The current consensus should help to limit heterogeneity of treatment protocols but underlines the utmost importance of further research

THE EFFECT OF CAVITATION WATER TREATMENT ON YEAST GROWTH

В работе проанализировано влияние обработки дистиллированной воды гидродинамической кавитацией на рост дрожжей культуры Candida valida.The paper analyzes the effect of treatment of distilled water by hydrodynamic cavitation on the growth of the Candida valida culture yeast

Deep Learning in Remote Sensing

This thesis presents a study into Deep Learning with a domain specific lens of Remote Sensing. In particular, the aims are aligned with tasks that are of practical utility for residential solar system (PV) analysis and adaptation, in addition to disaster relief planning and fields in which remote sensing is necessary to map urban landscapes. We present 5 studies which each have their own particular focus. Initially we study the ability by which we may detect and localize PV systems with the help of aerial imagery. We leverage pre-trained models from Germany and explore their out-of-the-box utility for inference in Denmark. The second component of our thesis revolves around the vectorization of building shapes using aerial or satellite imagery. We explore deep generative models in the form of auto-regressive conditional recurrent neural networks and transformer models, and demonstrate state of the art performance on proprietary acquired data for single residential homes as well as benchmark datasets inferring multiple objects from one image. Finally we demonstrate the ability by which we may infer 3D shapes using aerial imagery. By leveraging an auto-regressive deep generative model, we find that we are capable of learning 3D points and surfaces from just a single image per building. We believe our studies in this thesis may provide a strong argument for further study of autoregressive deep generative models in the remote sensing context, and perhaps one day become a natural component in 3D building foundation models

Calculation of Neutron Production Rates and Spectra from Compounds of Actinides and Light Elements

The code NEDIS allows the calculation of neutron production rate and continuous energy spectra due to (α,n) reaction on Li, Be, B, C, O, F, Ne, Na Mg, Al, Si, P, S, Cl, Ar, K, and Ca. It accounts for anisotropic angular distribution of neutrons of (α,n) reaction in centre-of- mass system and dimensions of alpha emitting source material particles. Spontaneous fission spectra are calculated with evaluated half-life, spontaneous fission branching, ν- averaged per fission, and Watt spectrum parameters. The results of calculations by NEDIS can be used as input for Monte Carlo simulation for materials that will be used in radiation shielding and for underground neutron experiment

Calculation of Neutron Production Rates and Spectra from Compounds of Actinides and Light Elements

The code NEDIS allows the calculation of neutron production rate and continuous energy spectra due to (α,n) reaction on Li, Be, B, C, O, F, Ne, Na Mg, Al, Si, P, S, Cl, Ar, K, and Ca. It accounts for anisotropic angular distribution of neutrons of (α,n) reaction in centre-of- mass system and dimensions of alpha emitting source material particles. Spontaneous fission spectra are calculated with evaluated half-life, spontaneous fission branching, ν- averaged per fission, and Watt spectrum parameters. The results of calculations by NEDIS can be used as input for Monte Carlo simulation for materials that will be used in radiation shielding and for underground neutron experiment

Determination of Dynamic Characteristics for Predicting Electrical Load Curves of Mining Enterprises

The calculation of electrical loads is the first and most significant stage in the design of the power supply system. It is essential to make the right choice when choosing the power electrical equipment: transformers, power lines, and switching devices. Underestimation or overestimation of the calculated values can lead to large losses and an increase in capital costs. Therefore, the reliability of the results plays a key role. The use of energy-saving technologies and energy-efficient electrical equipment leads to a change in the nature and level of power consumption, which must be taken into account when determining the electrical loads. The existing methods leave out dynamic characteristics of electrical load curves, so the calculated values are overestimated by up to 40%. This study shows a load calculation method with the normalized correlation functions and its parameters at the level of the individual and group electricity consumers. As a result, the difference between the calculated and experimental values does not exceed 5%