Common Field Of Application Research Articles

Enzymatic Synthesis of Ascorbic Acid-Ketone Body Hybrids

Molecular hybrids obtained by connecting two or more bioactive molecules through a metabolizable linker are used as multi-target drugs for the therapy of multifactorial diseases. Ascorbic acid, as well as the ketone bodies acetoacetate and (R)-3-hydroxybutyrate, are bioactive molecules that have common fields of application in the treatment and prevention of neurodegenerative diseases and cardiac injuries as well. In spite of this, the preparation of ascorbic acid ketone body hybrids is uncovered by the literature. Herein, we report the lipase-catalyzed condensation of methyl acetoacetate with ascorbic acid, which affords the 6-O-acetoacetyl ascorbic acid in quantitative yield. The same approach, employing the methyl (R)-3-hydroxybutyrate in place of the methyl acetoacetate, allows the preparation of the 6-O-(R)-3-hydroxybutyryl ascorbic acid in 57% yield. A better result (90% overall yield) is achieved through the lipase-catalyzed coupling of ascorbic acid with methyl (R)-3-O-methoxymethyl-3-hydroxybutyrate followed by the cleavage of the MOM protecting group. The two novel products are fully characterized and additional information on the antioxidant activity of the new products is also given.

New End-to-End Strategy Based on DeepLabv3+ Semantic Segmentation for Human Head Detection.

In the field of computer vision, object detection consists of automatically finding objects in images by giving their positions. The most common fields of application are safety systems (pedestrian detection, identification of behavior) and control systems. Another important application is head/person detection, which is the primary material for road safety, rescue, surveillance, etc. In this study, we developed a new approach based on two parallel Deeplapv3+ to improve the performance of the person detection system. For the implementation of our semantic segmentation model, a working methodology with two types of ground truths extracted from the bounding boxes given by the original ground truths was established. The approach has been implemented in our two private datasets as well as in a public dataset. To show the performance of the proposed system, a comparative analysis was carried out on two deep learning semantic segmentation state-of-art models: SegNet and U-Net. By achieving 99.14% of global accuracy, the result demonstrated that the developed strategy could be an efficient way to build a deep neural network model for semantic segmentation. This strategy can be used, not only for the detection of the human head but also be applied in several semantic segmentation applications.

Lee and Carter go Machine Learning: Recurrent Neural Networks

In this tutorial we introduce recurrent neural networks (RNNs), and we describe the two most popular RNN architectures. These are the long short-term memory (LSTM) network and gated recurrent unit (GRU) network. Their common field of application is time series modeling, and we demonstrate their use on a mortality rate prediction problem using data from the Swiss female and male populations.

Procedural modeling of architecture with round geometry

Creation of procedural 3D building models can significantly reduce the costs of modeling, since it allows for generating a variety of similar shapes from one procedural description. The common field of application for procedural modeling is modeling of straight building facades, which are very well suited for shape grammars—a special kind of procedural modeling system.In order to generate round building geometry, we present a way to set up different coordinate systems in shape grammars. Besides Cartesian, these are primarily cylindrical and spherical coordinate systems for generation of structures such as towers or domes, that can procedurally adapt to different dimensions and parameters. The users can apply common splitting idioms from shape grammars in their familiar way for creating round instead of straight geometry.The second enhancement we propose is to provide a way for users to give high level inputs that are used to automatically arrange and adapt parts of the models.

Relation Between Level Set and Truncated Pluri-Gaussian Methodologies for Facies Representation

Truncated Gaussian/pluri-Gaussian representations and level set representations are two methodologies for implicit representation that can be applied to large-scale subsurface structures. Identification of facies in a petroleum reservoir from dynamic well data is a common field of application for these representation methodologies. No comparison of the methodologies has appeared in the literature to date. The paper seeks to improve on this situation by comparing selected level set and truncated Gaussian/pluri-Gaussian representations in detail. Strong similarities are found, in the sense that every truncated Gaussian/pluri-Gaussian representation considered has a level set counterpart. Furthermore, the transition from a truncated Gaussian/pluri-Gaussian representation to the corresponding level set representation is easily accessible. In addition to the comparison aspect, this paper also introduces a novel level set representation—the hierarchical level set representation—that removes a difficulty present in existing level set representations in a shape estimation setting. It is shown that the hierarchical level set representation corresponds to a well-known truncated pluri-Gaussian representation.

Evaluating a Treatment Manual for Music Therapy in Adult Outpatient Oncology Care

Music therapy is a prevalent treatment for people with a life-threatening illness, with inpatient oncology care being one of the most common fields of application. A recently published review on this topic shows that studies examining the effects of active music therapy treatments in an outpatient setting are still rare. Based on the Phase Model of Psychotherapy Outcome, a treatment manual has been developed for outpatient music therapy cancer care, consisting of 20 individual sessions. The aim of this study was to evaluate the effectiveness of the procedures of this manual by comparing prescores and postscores of 20 patients’ self-reported general therapy outcome, quality of life, and subjective pain intensity ratings. Results show that the intervention led to a significant improvement on all 3 dependent measures. Effect sizes ranged from medium to large. The authors conclude that it is necessary to further expand outpatient cancer care in Germany and to integrate music therapy as an effective treatment into these areas.

Luminescence dating: basics, methods and applications

Abstract. Luminescence dating is a tool frequently used for age determination of Quaternary materials such as archaeological artefacts, volcanic deposits and a variety of sediments from different environmental settings. The present paper gives an overview of the physical basics of luminescence dating, the necessary procedures from sampling to age calculation, potential problems that may interfere with correct age calculation as well as procedures to identify and resolve those problems. Finally, a brief summary of the most common fields of application is given ranging from artefacts to the variety of different sediments suitable for luminescence dating.

Using CAVE technology for educating and training residents

Problem: Three-dimensional models are quite common now, but are still restricted to a 2-dimensional view by a screen or beamer. We use CAVE technology for education of complex anatomical findings and for surgical simulation. Methods: We create models by segmentation of datasets using the “3D-Slicer.” For the small structures in the temporal bone we used an experimental cone-beam Volume CT prototype that offers 160 micron isotropic resolutions. The CAVE is a Virtual Reality Center (VRC) which allows real-time visualization of interactive, complex graphical data in a walkable room. The graphical visualization is achieved by rear-panel beamers on 3 walls and a projection surface on the floor. Multiple users can interact in this virtual surrounding with different types of graphical data by rotating, zooming, or performing any programmable function. Results: Teaching pathologic findings or surgical planning in challenging cases are the most common fields of application. We use this technology for students’ and residents’ learning difficult anatomic findings. By simulating different pathways we can experience the changes of the anatomy or pathology, which is presented in its variations to the surgeons’ view. Conclusion: Using CAVE technology for medical imaging is the next step of 3D visualization. Most advantages are in the field of education because of the possibility for several dozen individuals to see 3D models simultaneously and to interact with real patients’ data (in other words, allowing a “hands-on effect”). Significance: By using virtual reality we presume to optimize the learning curve of students and especially residents, who are in the first training stages of acquiring the skill of surgery. Another possibility of training surgeons is to simulate the surgeons’ view through a microscope, which is harder because of the loss of landmarks. Walking around the model helps to train the “mental eye” and improves the surgical skills of young surgeons. Support: None reported.

A Framework for Simulation Model Management

The paper notes that manufacturing industry as the most common field of application for discrete-event simulation, with impact on a wide range of business decisions, yet weaknesses have been found in simulation practice in the field. In the context of increasing use by non-specialists under time-pressure, the paper argues that more emphasis in simulation software development needs to be given to model management, rather than to further refinements in model creation, and describes a pilot framework for guiding users through the overall simulation process.