Daviesbraun3479

This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO) deep neural networks for the outdoor advertisement panel detection problem by handling multiple and combined variabilities in the scenes. GW806742X research buy Publicity panel detection in images offers important advantages both in the real world as well as in the virtual one. For example, applications like Google Street View can be used for Internet publicity and when detecting these ads panels in images, it could be possible to replace the publicity appearing inside the panels by another from a funding company. In our experiments, both SSD and YOLO detectors have produced acceptable results under variable sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex background and multiple panels in scenes. Due to the difficulty of finding annotated images for the considered problem, we created our own dataset for conducting the experiments. The major strength of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable when the publicity contained inside the panel is analyzed after detecting them. On the other side, YOLO produced better panel localization results detecting a higher number of True Positive (TP) panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models with different types of semantic segmentation networks and using the same evaluation metrics is also included.The oxidative photocyclization of aromatic Schiff bases was investigated as a potential method for synthesis of phenanthridine derivatives, biologically active compounds with medical applications. Although it is possible to prepare the desired phenanthridines using such an approach, the reaction has to be performed in the presence of acid and TEMPO to increase reaction rate and yield. The reaction kinetics was studied on a series of substituted imines covering the range from electron-withdrawing to electron-donating substituents. It was found that imines with electron-withdrawing substituents react one order of magnitude faster than imines bearing electron-donating groups. The 1H NMR monitoring of the reaction course showed that a significant part of the Z isomer in the reaction is transformed into E isomer which is more prone to photocyclization. The portion of the Z isomer transformed showed a linear correlation to the Hammett substituent constants. The reaction scope was expanded towards synthesis of larger aromatic systems, namely to the synthesis of strained aromatic systems, e.g., helicenes. In this respect, it was found that the scope of oxidative photocyclization of aromatic imines is limited to the formation of no more than five ortho-fused aromatic rings.Due to concerns about frequent applications of spinosad and other broad spectrum insecticides for managing spotted-wing drosophila (Drosophila suzukii Matsumura, SWD), we investigated the use of essential oils as an alternative to current insecticides. Essential oils from a number of plant species have been studied for their attraction and deterrence of SWD. However, these botanical products have not been thoroughly tested in the field. We conducted laboratory and field studies to determine the efficacy of botanical products, including lavender (Lavandula angustifolia Mill.) oil, catnip (Nepeta cataria L.) oil, KeyPlex Ecotrol® PLUS, and KeyPlex Sporan® EC2 on preventing SWD infestation in raspberry (Rubus idaeus L.) and blueberry (Vacciniumcorymbosum L.) crops. In a two-choice laboratory bioassay, lavender oil, Ecotrol, and Sporan treatments deterred SWD from a yeast-cornmeal-sugar based fly diet. In the field trials, raspberry fruit treated with Ecotrol had lower SWD infestation (6%), compared to the control (17%), and was comparable to spinosad (6%). No differences were seen in blueberry infestation. The combination of essential oils in Ecotrol may work to decrease SWD fruit infestation under certain conditions in the field, however more research is needed on the longevity of these products.It is essential to combine current state-of-the-art technologies such as additive manufacturing with current ecological needs. Due to the increasing demand for non-toxic biodegradable materials and products, human society has been searching for new materials. Consequently, it is compulsory to identify the qualities of these materials and their behavior when subjected to various external factors, to find their optimal solutions for application in various fields. This paper refers to the biodegradable Polylactic acid (PLA)-based filament (commercially known as Extrudr BDP (Biodegradable Plastic) Flax) compared with the biodegradable composite material PLA-lignin filament whose constituent's trade name is Arboblend V2 Nature as a lignin base material and reinforcement with Extrudr BDP Pearl, a PLA based polymer, 3D printed by Fused Deposition Modeling technology. Certain mechanical properties (tensile strength, bending strength and DMA-Dynamic Mechanical Analysis) were also determined. The tribology behavior (friction coefficient and wear), the structure and the chemical composition of the biodegradable materials were investigated by SEM-Scanning Electron Microscopy, EDX-Energy Dispersive X-Ray Analysis, XRD-X-Ray Diffraction Analysis, FTIR-Fourier Transform Infrared Spectrometer and TGA-Thermogravimetric Analysis. The paper also refers to the influence of technological parameters on the 3D printed filaments made of Extrudr BDP Flax and the optimization those of technological parameters. The thermal behavior during the heating of the sample was analyzed by Differential scanning calorimetry (DSC). As a result of the carried-out research, we intend to recommend these biodegradable materials as possible substituents for plastics in as many fields of activity as possible.For on-farm welfare assessment many automatic methods have been developed to detect indicators of reduced welfare. However, there is still a need to integrate data from single sources to obtain a complete picture of the welfare of an animal. This review offers a basis for developing integrated automatic systems to assess dairy cow welfare by providing an overview of the main issues that challenge cow welfare (e.g., lameness) and of well-established indicators that could detect these issues on the farm. Based on a literature review of 4 reviews on cow welfare in general and 48 reviews on single welfare issues, we identified 18 different major welfare issues and 76 matching indicators that could be detected automatically on the farm. Several indicators, e.g., feed intake, showed a consistent association with welfare across many different issues. Although some of these indicators are discussed critically, this means there are many indicators that potentially could detect reduced welfare in general. Other types of indicators could detect one specific welfare issue, e.