<p>The construction industry contributes significantly to the GDP of the United States, attributing to its growth at an unprecedented rate. Efficient planning on all stages of construction is the only way to combat dynamic obstructions and deliver projects on time. The first element involved in the planning phase deals with the layout of the Construction Site. It significantly regulates the pace at which construction operations function and directly affects the time, cost, and safety linked to the successful delivery of the target project. Hence, it is paramount to ensure that every component of the construction site maneuvers with the utmost productivity. One such equipment that occupies significant attention while carrying out the CSLP process is Tower Crane. Tower crane optimization is pivotal to ensure proper lifting and handling of materials, and warrant conflict-free work zones. This research, therefore, aims to optimize its position by maximizing the lift ability. To achieve the goals, Generative Design- a paradigm that integrates the constructive features of mathematical and visual optimization techniques, is used to develop a relatively comprehensible prototype. The first part of the research, thus, utilized Generative Design on two construction sites- one from the United States and one from India. After implementing the visual programming algorithm, an improvement of 40% was warranted in the lift score. A pool of potential alternatives was explored and supplemented by the trade-off illustrations. The concept of trade-off was substantiated by allowing a framework for prioritization of lift cycles, and facilitating a holistic decision-making process. To evaluate the usability, 12 participants were chosen based on their previous experience with tower crane operations. The participants witnessed a live demonstration of the algorithm, answered a Likert scale questionnaire, and appeared for an open-ended interview to provide feedback about the proposed Generative Design technique. After carrying out narrative analysis for the usability aspect- it has been unanimously observed that the technique has extreme efficiency of usage and can evidently prevent the occurrence of errors. The study concludes by providing recommendations to augment the significance and usability of Generative Design for tower crane position optimization. </p><br>

The theme of this diploma thesis is the architectural study of the complex of the Farm of 3D Printers in Jaroslavice. The technology of 3D printing at its speed of development has far outweighed the response to its needs. It lacks a new systematically planned building typology corresponding to the requirements of farms. Farms adapt to the spaces. The main aim of the work is to introduce the possibility of turning the situation and adapting the premises to the farms. The thesis follows the urban design of the restructuring of the Jaroslavice landscape elaborated in the previous semester. The project respects established principles at microregion level in the form of emphasis on self-sufficiency, population integrity or the use of current technologies. The land is located on the southern part of Jaroslavice. There are 3 agricultural buildings located on the property, which until 2010, when a photovoltaic power plant was built, operated in conjunction with a neighboring agricultural court. After the power plant was built, the bonds were irreversibly broken. Buildings are in a very poor condition and mutual cooperation no longer works. The existing solution replaces and shows the possibility of using solar energy in a different way. Thus, the construction cartridge works with a hybrid typology where the 3D production area is combined with the maximum solar gains of the photovoltaic panels. Generative methods have been used to design dominantly either for finding a form in terms of achieving maximum solar gains or after verifying the efficiency of the structure. The proposal has several scenarios of possible development. There are four different stages of growth and the linkage of production areas. Printers are able to replicate themselves at such a rate that they can expect rapid growth. The proposal uses controlled growth methods to simulate complex development under the conditions of maximum solar radiation. Visual distraction and overheating are also solved by atypical sunsets on the exterior façade. Thin-film photovoltaic panels are used on the sun, so it is able to produce electricity besides the shield. The energy-efficient shape along with the great advantage of the layout solution, instead of the corridor disposition, is a basic cell on the central plan view. This makes it possible to control and operate more of the machines more efficiently. The production site forwards counts full robot automation.

The rise of additive manufacturing has enabled new degrees of freedom in terms of design and functionality. In this context, this contribution addresses the design and characterization of structural unit cells that are intended as building blocks of highly porous lattice structures with tailored properties. While typical lattice structures are often composed of gyroid or diamond lattices, this study presents stackable unit cells of different sizes created by a generative design approach tomeet boundary conditions such as printability and homogeneous stress distributions under a given mechanical load. Suitable laser powder bed fusion (LPBF) parameterswere determined forAlSi10Mg to ensure high resolution and process reproducibility for all considered unit cells. Stacks of unit cells were integrated into tensile and pressure test specimens for which the mechanical performance of the cells was evaluated. Experimentally measured material properties, applied process parameters, and mechanical test results were employed for calibration and validation of finite element (FE) simulations of both the LPBF process as well as the subsequent mechanical characterization. The obtained data therefore provides the basis to combine the different unit cells into tailored lattice structures and to numerically investigate the local variation of properties in the resulting structures. / Durch die Einführung der Additiven Fertigung können neue Freiheitsgrade in Bezug auf Gestaltungsfreiheit und Funktionalität erreicht werden. In diesem Zusammenhang adressiert dieser Beitrag das Design und die Charakterisierung struktureller Einheitszellen als Bausteine für hochgradig poröse Gitterstrukturen mit maßgeschneiderten Eigenschaften. Während typische Gitterstrukturen oft auf Gyroid- oder Diamantstrukturen basieren, präsentiert dieser Beitrag stapelbare Einheitszellen unterschiedlicher Größe, die durch einen generativen Designansatz erstellt wurden. Hierdurch sollen verschiedene Randbedingungen wie eine gute Druckbarkeit und homogene Spannungsverteilung unter gegebenen mechanischen Lasten erreicht werden. Um eine hohe Auflösung und Reproduzierbarkeit der Einheitszellen zu erreichen, wurden für den verwendeten Werkstoff AlSi10Mg geeignete Druckparameter für das Laserstrahlschmelzen (LPBF) ermittelt. Stapel von Einheitszellen wurden in Zug- und Druckproben integriert, anhand derer die mechanische Stabilität der Zellen ermittelt wurde. Experimentell bestimmte Materialeigenschaften, die verwendeten Prozessparameter und die Ergebnisse der mechanischen Untersuchungen wurden anschließend für die Kalibrierung und Validierung Finiter Elemente (FE) Simulationen herangezogen, wobei simulationsseitig sowohl der Prozess des Laserstrahlschmelzens als auch die nachgelagerte mechanische Charakterisierung berücksichtigt wurden. Die hier präsentierten Ergebnisse sollen als Basis sowohl für eine gezielte Anordnung der Einheitszellen zu maßgeschneiderten Gitterstrukturen dienen als auch für die numerische Auswertung der lokal variierenden Eigenschaften der somit resultierenden Strukturen.

<p>Protein malfunction can cause human diseases, which makes the protein a target in the process of drug discovery. In-depth knowledge of how protein functions can widely contribute to the understanding of the mechanism of these diseases. Protein functions are determined by protein structures and their dynamic properties. Protein dynamics refers to the constant physical movement of atoms in a protein, which may result in the transition between different conformational states of the protein. These conformational transitions are critically important for the proteins to function. Understanding protein dynamics can help to understand and interfere with the conformational states and transitions, and thus with the function of the protein. If we can understand the mechanism of conformational transition of protein, we can design molecules to regulate this process and regulate the protein functions for new drug discovery. Protein Dynamics can be simulated by Molecular Dynamics (MD) Simulations.</p> <p>The MD simulation data generated are spatial-temporal and therefore very high dimensional. To analyze the data, distinguishing various atomic interactions within a protein by interpreting their 3D coordinate values plays a significant role. Since the data is humongous, the essential step is to find ways to interpret the data by generating more efficient algorithms to reduce the dimensionality and developing user-friendly visualization tools to find patterns and trends, which are not usually attainable by traditional methods of data process. The typical allosteric long-range nature of the interactions that lead to large conformational transition, pin-pointing the underlying forces and pathways responsible for the global conformational transition at atomic level is very challenging. To address the problems, Various analytical techniques are performed on the simulation data to better understand the mechanism of protein dynamics at atomic level by developing a new program called Probing Long-distance interactions by Tapping into Paired-Distances (PLITIP), which contains a set of new tools based on analysis of paired distances to remove the interference of the translation and rotation of the protein itself and therefore can capture the absolute changes within the protein.</p> <p>Firstly, we developed a tool called Decomposition of Paired Distances (DPD). This tool generates a distance matrix of all paired residues from our simulation data. This paired distance matrix therefore is not subjected to the interference of the translation or rotation of the protein and can capture the absolute changes within the protein. This matrix is then decomposed by DPD</p> <p>using Principal Component Analysis (PCA) to reduce dimensionality and to capture the largest structural variation. To showcase how DPD works, two protein systems, HIV-1 protease and 14-3-3 σ, that both have tremendous structural changes and conformational transitions as displayed by their MD simulation trajectories. The largest structural variation and conformational transition were captured by the first principal component in both cases. In addition, structural clustering and ranking of representative frames by their PC1 values revealed the long-distance nature of the conformational transition and locked the key candidate regions that might be responsible for the large conformational transitions.</p> <p>Secondly, to facilitate further analysis of identification of the long-distance path, a tool called Pearson Coefficient Spiral (PCP) that generates and visualizes Pearson Coefficient to measure the linear correlation between any two sets of residue pairs is developed. PCP allows users to fix one residue pair and examine the correlation of its change with other residue pairs.</p> <p>Thirdly, a set of visualization tools that generate paired atomic distances for the shortlisted candidate residue and captured significant interactions among them were developed. The first tool is the Residue Interaction Network Graph for Paired Atomic Distances (NG-PAD), which not only generates paired atomic distances for the shortlisted candidate residues, but also display significant interactions by a Network Graph for convenient visualization. Second, the Chord Diagram for Interaction Mapping (CD-IP) was developed to map the interactions to protein secondary structural elements and to further narrow down important interactions. Third, a Distance Plotting for Direct Comparison (DP-DC), which plots any two paired distances at user’s choice, either at residue or atomic level, to facilitate identification of similar or opposite pattern change of distances along the simulation time. All the above tools of PLITIP enabled us to identify critical residues contributing to the large conformational transitions in both HIV-1 protease and 14-3-3σ proteins.</p> <p>Beside the above major project, a side project of developing tools to study protein pseudo-symmetry is also reported. It has been proposed that symmetry provides protein stability, opportunities for allosteric regulation, and even functionality. This tool helps us to answer the questions of why there is a deviation from perfect symmetry in protein and how to quantify it.</p>

<p dir="ltr">The primary purpose of this thesis is to propose and demonstrate BioGRNsemble, a modular and flexible approach for inferencing gene regulatory networks from RNA-Seq data. Integrating the GENIE3 and GRNBoost2 algorithms, this ensembles-of-ensembles method attempts to balance the outputs of both models through averaging, before providing a trimmed-down gene regulatory network consisting of transcription and target genes. Using a Drosophila Eye Dataset, we were able to successfully test this novel methodology, and our validation analysis using an online database determined over 3500 gene links correctly detected, albeit out of almost 530,000 predictions, leaving plenty of room for improvement in the future.</p>