Early postoperative outcome in open and laparoscopic appendectomy. Our comparative data analysis

INTRODUCTION: After the introduction of laparoscopic appendectomy (LA) in 1981, it is used as one of the operative methods in the treatment of acute appendicitis ever since. Some of the surgeons almost completely replaced open appendectomy (OA) by its laparoscopic alternative, while others still have doubts about its universality. Early postoperative outcome has acceptable results when these two methods are com­pared, and that is the aim of this study.PATIENTS AND METHODS: This retrospective study includes 798 patients operated for the diagnosis of acute appendicitis in period 2012 - 2016. Both OA and LA were made by four surgeons in 650 and 148 pa­tients, respectively.RESULTS: Intrahospital mortality in OA group was 0.3% (2 patients) and 0.6% in the LA group (1 patient). Early postoperative outcome was measured through the length of stay (5.1 for OA and 3.1 for LA), superfi­cial surgical site infections - 4.7% in OA versus 2.7% in LA. Postoperative intraabdominal abscess occurred in 2% (OA) and 4.05% (OA). The conversion rate was 4.7%.CONCLUSION: Open appendectomy and LA are both used as two surgical alternatives in the treatment of acute appendicitis with comparable early postoperative outcomes. Although LA is almost 100 years young­er as an operative method, OA is still widely used. The choice of the procedure should be probably based on surgeon or patient preference. Scr Sci Med 2017; 49(3): 31-3

Controlling a Fleet of Autonomous LHD Vehicles in Mining Operation

In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map

Climate Changes- Challenge, But Also an Obligation for the Education

Is there a law on environment, why hasn’t this term been precisely defined yet,why is there no harmonized meaning neither in the general, nor in the language of law. Without any doubt, our environment is composed at least from earth, water and air. It is surrounded by living organisms comprising the flora and fauna. Therefore, the definition rises from the human demands and it is in this sense that we ask a few questions. Do men create the environment of national parks? Does cities and villages with their streets and buildings represent environment? What is the case with the very distant environments? Should the term environment be restricted only to planet earth? The pollution and the soil and atmosphere degradation is dangerous for two reasons; the great speed in the case of disasters and the volume of pollution have global consequences.  The field of international law on environment comprises of three main topics. Air pollution, reduction of the ozone layer and climate changes. While the politicians and economists are debating, the scientists are unanimous in how to stop the climate changes, because the warming of the planet must be stopped. The main goal of the authors of this paper is how to create educational institutions that will generate experts in order to prevent: the planet earth to remain without the climate zones till 2100; to become a planet of hot poles; the plants and animals, and even humans to became endangered and extinct, enlarging of the tropical and subtropical zones by high temperatures; the developed countries of becoming the biggest polluters and the increase of CO2 emission in the air; China and India, as new development poles, to ask for permit to pollute the earth in the same amount as the USA and Europe without a drawback for the percent of poverty. The authors seek for answers to these questions in the insufficient cooperation between the society and the higher education institutions. How can education make the entry in the economy, in the praxis, easier; can the severe reality of the praxis, of the economy of degradations and the earth pollution enrich the research knowledge? The economic, legal, ecological, as well as engineering and scientific workers cannot allow themselves to disregard the application of their work, according to their tasks in the industry and society. In addition, the other way around, the companies must integrate the new research findings in their work programs. Only those that increase their know-how remain constantly powerful in making decisions and implementing specific concepts. The modern professor in the higher education must be familiar with the praxis, as user of the economy impulses. The consciousness toward this mutual usefulness creates a need for securing constant growth, which in turn reveals the needs of today and gives the future generations a possibility to realize their goals and it should be a foundation for the Alliance of Central and Eastern European Universities, which will enable future staff that with their knowledge will create an economy that will not pollute and degrade the planet earth

Benchmarking of Various LiDAR Sensors for Use in Self-Driving Vehicles in Real-World Environments

In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars