Improvements on Seeding Based Protein Sequence Similarity Search

The primary goal of bioinformatics is to increase an understanding in the biology of organisms. Computational, statistical, and mathematical theories and techniques have been developed on formal and practical problems that assist to achieve this primary goal. For the past three decades, the primary application of bioinformatics has been biological data analysis. The DNA or protein sequence similarity search is perhaps the most common, yet vitally important task for analyzing biological data. The sequence similarity search is a process of finding optimal sequence alignments. On the theoretical level, the problem of sequence similarity search is complex. On the applicational level, the sequences similarity search onto a biological database has been one of the most basic tasks today. Using traditional quadratic time complexity solutions becomes a challenge due to the size of the database. Seeding (or filtration) based approaches, which trade sensitivity for speed, are a popular choice among those available. Two main phases usually exist in a seeding based approach. The first phase is referred to as the hit generation, and the second phase is referred to as the hit extension. In this thesis, two improvements on the seeding based protein sequence similarity search are presented. First, for the hit generation, a new seeding idea, namely spaced k-mer neighbors, is presented. We present our effective algorithms to find a good set of spaced k-mer neighbors. Secondly, for the hit generation, a new method, namely HexFilter, is proposed to reduce the number of hit extensions while achieving better selectivity. We show our HexFilters with optimized configurations

Tumor-on-a-chip platforms to study cancer-immune system crosstalk in the era of immunotherapy

Immunotherapy is a powerful therapeutic approach able to re-educate the immune system to fight cancer. A key player in this process is the tumor microenvironment (TME), which is a dynamic entity characterized by a complex array of tumor and stromal cells as well as immune cell populations trafficking to the tumor site through the endothelial barrier. Recapitulating these multifaceted dynamics is critical for studying the intimate interactions between cancer and the immune system and to assess the efficacy of emerging immunotherapies, such as immune checkpoint inhibitors (ICIs) and adoptive cell-based products. Microfluidic devices offer a unique technological approach to build tumor-on-a-chip reproducing the multiple layers of complexity of cancer-immune system crosstalk. Here, we seek to review the most important biological and engineering developments of microfluidic platforms for studying cancer-immune system interactions, in both solid and hematological tumors, highlighting the role of the vascular component in immune trafficking. Emphasis is given to image processing and related algorithms for real-time monitoring and quantitative evaluation of the cellular response to microenvironmental dynamic changes. The described approaches represent a valuable tool for preclinical evaluation of immunotherapeutic strategies

Exploring the Technical Advances and Limits of Autonomous UAVs for Precise Agriculture in Constrained Environments

In the field of precise agriculture with autonomous unmanned aerial vehicles (UAVs), the utilization of drones holds significant potential to transform crop monitoring, management, and harvesting techniques. However, despite the numerous benefits of UAVs in smart farming, there are still several technical challenges that need to be addressed in order to render their widespread adoption possible, especially in constrained environments. This paper provides a study of the technical aspect and limitations of autonomous UAVs in precise agriculture applications for constrained environments

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

InP microdisks for optical signal processing and data transmission

The performance increase in telecommunication and computing systems demands an ever increasing input-output (IO) bandwidth and IO density, which can be met by integrated photonics. Using photonic integration, much higher densities of optical components can be achieved allowing for short-range optical communication systems in, e.g., high performance computers. The key functionalities required for these optical communication systems are light generation, light modulation and light detection. In addition to this other functionalities are also desirable, such as wavelength conversion. This thesis highlights the design and fabrication of indium phosphide (InP) microdisks heterogeneously integrated on silicon-on-insulator substrates. The fabrication of the microdisks in a laboratory clean-room environment is described. These devices can fulfil the above-mentioned functions required in optical communication. Experiments are then performed on the fabricated devices dealing with these various functionalities that are required for optical communication. The lasing properties of the devices are shown and simulated with a spatiallydependent rate equation model accurately predicting the device behaviour. A detailed speed analysis is given, including a parameter extraction of the devices. The operation of the devices as detectors is highlighted. Furthermore the PhD thesis provides a deep analysis of the use of InP microdisks as modulators. Besides the forward-biased operation principle using the free-carrier plasma-dispersion effect, also a high-speed reversely biased operation mode is proposed and demonstrated experimentally. The thesis also describes various approaches on how to improve the performance of the devices, in particular when using them as lasers. Ways how to increase the output power and how to enhance the operation speed are discussed. Because the device is strongly dependent on the coupling between the resonant InP cavity and the silicon waveguide, an extensive analysis of the coupling and the influence of certain process steps on the device performance are given. The PhD thesis concludes the work carried out on InP microdisks and gives an outlook about improving the device performance with respect to specific applications and how to further improve the manufacturability of the devices. Finally, for the InP microdisk-based devices an outlook is given about suitable applications, such as on-chip optical links for instance

Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments

Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

The book describes methods of track and vertex resonstruction in particle detectors. The main topics are pattern recognition and statistical estimation of geometrical and physical properties of charged particles and of interaction and decay vertices