Digitally fabricated low cost housing: material, joint and prototype

Motivated by the global housing deficit and limited natural resources, this study aims to utilize digital fabrication technologies coupled with local sustainable materials in the quest for alternative, adequate low-cost housing solutions for the less fortunate population, mainly in developing countries. The thesis is structured into two main parts: a theoretical and an empirical study. The theoretical part identifies the research problem and lays the foundation of knowledge, as well as defines the motivating questions, aim, objectives, scope, methodology and tools used throughout the thesis. An overview of fundamental concepts of mechanisation, standardisation, prefabrication, mass housing, and mass customisation is provided. Different types of prefabricated housing are presented followed by a discussion of select architect-led and industry-led early precedents in prefabrication. The theoretical part also includes an analysis of state-of-the-art built projects or prototypes of digitally fabricated houses. Through this analysis, how these prototypes respond to housing problems is addressed and an observation is made of how these built projects can be categorised into main streams or different trends. After defining the potentials and limitations of these precedents, a number of design criteria or design guidelines are proposed forming the basis for the proposition of a housing system that addresses these drawbacks under the name “Housing System 01”. The second part of the thesis is a Design-Build-Evaluate empirical study in which the proposed housing system combining concepts of complete off-site prefabrication with modular parametric localised digital fabrication is outlined. Given the necessity of cost reductions, an integral joining system (snap-fit) using an agricultural residue panel material is tested as the principal method for the construction of wall assemblies. The study proves that by using integral joints, it is possible to involve the end-user of the housing unit in the construction activities promoting the concept of “Self-Build”, as the simplicity of the system allows for the participation of end-users with no previous construction expertise thereby decreasing cost. A set of mechanical tests are performed to characterise wheat straw panels and then snap-fit joints are dimensioned within the elastic limits of this specific material. Three partial wall assembly prototypes are built. One axial compression test is performed on one of the prototypes. The tests show that the material and the joint system promise to provide a viable construction system as an alternative low-cost housing solution. Further optimisation and more physical structural testing are needed to address more complex forces and loading scenarios

Photonik-unterstützte Kommunikation mit hohen Datenraten

The escalating demand for higher data rates and wider bandwidths in communication networks is being driven by the emergence of new applications. This growth extends beyond communications to include essential requirements for broad-bandwidth devices in various fields, including radar, sensing, and measuring systems. The increasing bandwidths, in addition to the sampling rate, may pose challenges for the electronic digital-to-analog converter (DACs) and analog-to-digital converters (ADCs) in digital systems. These challenges include the utilization of vast digital signal processing, leading to high-power consumption and increased costs. Photonics-assisted high-data rate communication may offer promising alternatives because photonics devices provide wide bandwidth, low-power consumption, and immunity against electromagnetic interferences. The main purpose of this thesis is to explore new methods to generate and detect high-bandwidth signals by low-bandwidth electronics based on optical signal processing. Those methods should be featured by the extremely small size and low-power consumption. The research in this thesis is divided into four main parts. The first part introduces the concept of generating high-bandwidth signals with higher-spectral efficiency from low-bandwidth DACs with lower-spectral efficiency. The method combines the use of electronics and photonics. By electronics, low-bandwidth sub-DACs are employed to generate signals with wide-bandwidth and low-spectral efficiency through the use of electrical orthogonal sampling with sinc-pulse sequences in N parallel branches. In photonics, higher spectral efficiency can be produced from M branches at different optical powers. The second part proposes a concept for detecting high-bandwidth wireless signals by a low-bandwidth photonics-assisted receiver. The idea is based on down-converting the input high-bandwidth wireless signals into low-bandwidth sub-signals using optical orthogonal sampling. It relies on multiplication rather than switching, which avoids introducing aperture jitter and improves the Q-factor for detection. The third part of this thesis presents a silicon ring modulator-based compact photonic sampler with low-power consumption. The sampler can sample various microwave signals by sinc-pulse sequences. The generation of the sinc-pulse sequence and sampling occur simultaneously within the same optical ring modulator. The proposed sampler can sample high-bandwidth signals with low-bandwidth electronics. The last section of this thesis describes a novel concept for the generation and detection of an optical superchannel. The transmitter system employs a comb source and cascaded optical ring modulators. Each modulator works as a filter, selecting one wavelength from the comb lines, and as a modulator, modulating k time division channels on the chosen wavelength. This process generates a rectangular optical superchannel from all wavelengths together. The transmitter does not require the employment of optical filters or delay lines, making it simple and compact. At the receiver side, an optical ring modulator can be utilized with the local oscillator (LO) to separate the generation of the sinc-pulse sequence from sampling. This is to prevent the suppression of the optical carrier. The concepts outlined in the first to fourth sections can be combined together to generate and detect high-bandwidth signals with low-bandwidth electronics. An extremely compact system with very low-power consumption can be achieved by employing optical ring modulators, resulting in low-cost systems. The proposed system is applicable to various fields, including radar, sensing, instrumentation, communications, and data centers.Die steigende Nachfrage nach höheren Datenraten und größeren Bandbreiten in Kommunikationsnetzwerken wird durch das Aufkommen neuer Anwendungen vorangetrieben. Das Wachstum erstreckt sich über die Kommunikation hinaus und umfasst Bereiche wie Radaranwendungen, Sensorik und Messtechnik. Die zunehmenden Bandbreiten und Abtastraten stellen Herausforderungen für elektronische Digital-analog-Wandler (DACs) und Analog-digital-Wandler (ADCs) in digitalen Systemen dar. Vor allem die umfangreiche digitale Signalverarbeitung, die zu einem hohen Energieverbrauch und erhöhten Kosten führt, ist dabei ein Problem. Die photonikgestützte Hochgeschwindigkeits-Kommunikation ist eine vielversprechende Alternative, da diese höhere Bandbreiten sowie einen geringen Energieverbrauch ermöglicht und immun gegenüber elektromagnetischer Interferenz ist. Das Hauptziel der Arbeit ist es, auf Basis optischer Signalverarbeitung neue Konzepte zur Generierung und Detektion hochbandbreitiger Signale durch elektronische, niederbandbreitige Geräte zu entwickeln. Die Konzepte sollen sich durch durch Kompaktheit und einen geringen Energieverbrauch auszeichen. Die Forschung dieser Arbeit ist in vier Hauptteile unterteilt. Im ersten Teil wird eine Methode vorgestellt, hochbandbreitige Signale mit hoher spektraler Effizienz mithilfe von niedrigbandbreiten DACs mit geringer spektraler Effizienz zu erzeugen. Die Methode verbindet Elektronik und Photonik. Elektrisch werden DACs in N parallelen Zweigen genutzt, um Signale mit großer Bandbreite und spektraler Effizienz mittels einer elektrischen, orthogonalen Abtastung mit Sinc-Puls-Sequenzen zu generieren. Photonisch ist eine höhere spektrale Effizienz durch M Zweige mit verschiedenen optischen Leistungen realisierbar. Im zweiten Teil wird ein Konzept zum Empfang hochbandbreitiger Drahtlos-Signale vorgeschlagen, die auf einem photonikgestützten Empfänger mit kleiner Bandbreite beruht. Es basiert auf der Herunterkonvertierung der Eingangs-Signale in niedrigbandbreitige Signale durch optisches, orthogonales Abtasten. Dabei wird auf Multiplikation statt auf Schaltprozesse gesetzt, um den Apertur-Jitter zu vermeiden und somit den Q-Faktor bei der Detektion anzuheben. Im dritten Teil der Arbeit wird ein kompakter photonischer Sampler auf Basis eines Siliziumringmodulators mit geringem Energieverbrauch präsentiert. Der Sampler tastet beliebige Radiofrequenzsignale mit Sinc-Puls-Sequenzen ab. Die Erzeugung der Sinc-Puls-Sequenz und die Abtastung erfolgen gleichzeitig im selben optischen Ringmodulator. Der Sampler kann hochbandbreitige Signale mittels niedrigbandbreitiger Elektronik sampeln. Im letzten Abschnitt der Arbeit wird ein neues Konzept zur Erzeugung und Detektion eines optischen Superkanals beschrieben. Der Sender verwendet eine Kammquelle und hintereinandergeschaltete optische Ringmodulatoren. Jeder Modulator fungiert als Filter, der eine Wellenlänge aus dem Kamm auswählt und als Modulator, der k zeitlich verschachtelte Kanäle auf die gewählte Welle moduliert. Mittels aller Wellenlängen wird ein rechteckiger, optischer Superkanal generiert. Der Sender braucht keine optischen Filter oder Verzögerungsglieder, was ihn einfach und kompakt macht. Zum Empfang wird ein optischer Ringmodulator mit Lokaloszillator (LO) genutzt, um die Sinc-Puls-Sequenz-Erzeugung von der Abtastung zu trennen und die Unterdrückung des optischen Trägers zu verhindern. Die vom ersten bis vierten Abschnitt dargestellten Methoden können kombiniert werden, um hochbandbreitige Signale mit niedrigbandbreitiger Elektronik zu erzeugen und zu empfangen. Ein kompaktes System mit sehr geringem Energieverbrauch kann mit optischen Ringmodulatoren realisiert werden, sodass es kostengünstig umsetzbar ist. Das System lässt sich für Radaranwendungen, Sensorik, Messtechnik, Kommunikation sowie in Rechenzentren einsetze

Modularity in artificial neural networks

Artificial neural networks are deep machine learning models that excel at complex artificial intelligence tasks by abstracting concepts through multiple layers of feature extraction. Modular neural networks are artificial neural networks that are composed of multiple subnetworks called modules. The study of modularity has a long history in the field of artificial neural networks and many of the actively studied models in the domain of artificial neural networks have modular aspects. In this work, we aim to formalize the study of modularity in artificial neural networks and outline how modularity can be used to enhance some neural network performance measures. We do an extensive review of the current practices of modularity in the literature. Based on that, we build a framework that captures the essential properties characterizing the modularization process. Using this modularization framework as an anchor, we investigate the use of modularity to solve three different problems in artificial neural networks: balancing latency and accuracy, reducing model complexity and increasing robustness to noise and adversarial attacks. Artificial neural networks are high-capacity models with high data and computational demands. This represents a serious problem for using these models in environments with limited computational resources. Using a differential architectural search technique, we guide the modularization of a fully-connected network into a modular multi-path network. By evaluating sampled architectures, we can establish a relation between latency and accuracy that can be used to meet a required soft balance between these conflicting measures. A related problem is reducing the complexity of neural network models while minimizing accuracy loss. CapsNet is a neural network architecture that builds on the ideas of convolutional neural networks. However, the original architecture is shallow and has wide layers that contribute significantly to its complexity. By replacing the early wide layers by parallel deep independent paths, we can significantly reduce the complexity of the model. Combining this modular architecture with max-pooling, DropCircuit regularization and a modified variant of the routing algorithm, we can achieve lower model latency with the same or better accuracy compared to the baseline. The last problem we address is the sensitivity of neural network models to random noise and to adversarial attacks, a highly disruptive form of engineered noise. Convolutional layers are the basis of state-of-the-art computer vision models and, much like other neural network layers, they suffer from sensitivity to noise and adversarial attacks. We introduce the weight map layer, a modular layer based on the convolutional layer, that can increase model robustness to noise and adversarial attacks. We conclude our work by a general discussion about the investigated relation between modularity and the addressed problems and potential future research directions

Analytical approaches to physicochemical characterization of colloid drug carriers

Der Einsatz von kolloidalen Trägern bei der Arzneimittelverabreichung wächst seit Jahrzehnten. Auf dem Gebiet der Pharmazie schaffte das einen Bedarf nach besserem Verständnis von physikalischen und physiko-chemischen Eigenschaften solcher, oft komplexen, kolloidalen Systeme. Das Ziel dieser Arbeit ist dieses Verständnis zu fördern und neue, einfache Techniken zu etablieren, die für die Entwicklung und Charakterisierung von kolloidalen Arzneimittelträgern nützlich sind. Kapitel 1 enthält eine kurze Einführung. Im Kapitel 2 wird ein neuer Ansatz zur Analyse potenziometrischer Daten vorgeschlagen. Solche Daten werden beispielhaft an Suspensionen von arznei-mittelbeladenen Lipidvesikeln erklärt und illustriert. Unser Model berücksichtigt erstmalig korrekt die elektrostatische, Coulomb’sche Wechselwirkung, die gemeinsam mit der hydrophoben Wechselwirkung für Verbindung zwischen Arzneimittelmolekülen und den Trägern sorgt. Kapitel 3 befasst sich mit der Transformation von Vesikeln in die Mizellen, die aus Phosphatidylcholin–Cholat-Gemischen bestehen, und zwar unter besonderer Berücksichtigung von Krümmungseffekten in der Lipiddoppelschicht. Das resultierende Bild der Vesikel-Mizellen-Transformation ist reicher und komplexer als zuvor bekannt. Im Kapitel 4 untersuche ich die Möglichkeit der Verwendung von UV/Vis Spektroskopie zur Charakterisierung von submikroskopischen Arzneimittelträgern, wie zum Beispiel Lipidvesikeln. Meine Ergebnisse implizieren, dass die experimentellen Trübheitsspektren ausreichende Information enthalten, um daraus schnelle, genaue und viskositätsunabhängige Charakteristika von submikroskopischen Teilchen ableiten zu können. Die fortschrittlichen analytischen Methoden, die im Rahmen dieser Arbeit entwickelt und untersucht wurden, eignen sich gut für die Anwendung in der pharmazeutischen Forschung und in der Qualitätskontrolle aber auch zur Charakterisierung von kolloidalen Trägern im Allgemeinen.von Mustafa Mohammed Abdelaziz Elsaye

Establishment of bioanalytical workflows for the quality assessment of formulated proteins

Proteins and peptides contribute to a significant class of therapeutic agents in the pharmaceutical market. Over the last decades, they gained growing interest due to their safety and specificity compared to small molecule drugs. Around 20% of the approved moieties by the Food and Drug Administration (FDA) in the last decade are of biological origin, such as antibodies, enzymes, peptides, and amino acids. One of the factors to be considered during the handling of proteins and peptides, especially on a large scale, is their stability. The sensitive nature of these biomolecules could lead to a loss of activity in cases of improper handling or storage. Therefore, biotechnologists focused on developing different formulation techniques to provide adequate protection and stabilization for the target protein or peptide. The design of a pharmaceutical formulation is a tailored mission according to the nature of the targeted protein, route of administration, and required mode of release. Furthermore, testing of the formulated protein is required to investigate the original characteristics of the protein and its stability after the formulation process. Thus, numerous analytical techniques and methods were developed and optimized for protein and peptide analysis. In the present thesis, the analysis of formulated proteins by employing different techniques and assessment of their stability was executed. The first aim of the present work was to develop bioanalytical workflows for the analysis of formulated proteins. Lysozyme was selected as a model protein in different formulations that were based on hot-melt extrusion as one of the appropriate methods for protein stabilization in the solid state. Analytical characterization of the lysozyme extrudates was performed to test identity, purity, and biological activity based on chromatographic, electrophoretic, and spectrofluorimetric methods. These validated methods were adapted into a workflow that was followed to test the stability of lysozyme hot-melt extrudates over six months of storage according to the guidelines of the International Council for Harmonization (ICH) Topic Q1A (R2). The second objective was focused on analysing the stability and structural integrity of the tested protein which is directly linked to its function. Thereby, the disulfide connectivity, one of the most important posttranslational modifications, in a protein or a peptide plays an essential role in maintaining the correct folding and, in turn, activity. In order to evaluate the protein’s folding state, validated methods are required, however, a lack of bioanalytical standards to test conformational isomerism based on disulfide bonds in a protein structure was obvious. Therefore, a series of standards were designed and validated according to the ICH M10 and Q14 guidelines and model peptides were generated to evaluate the developed bioanalytical standards. These standards were further applied for the elucidation of the connectivity in selected disulfide-rich peptides and proteins by application of optimized workflows and protocols using the developed standards. The objectives are extensively described and studied in the following chapters including the results (the respective manuscripts are enclosed in the appendix), which can be considered as a milestone in the development of bioanalytical methods for testing protein characteristics to evaluate their sequential, structural, and functional integrity in the pure and formulated state

Discovery and Validation of New Regulatory RNA Elements in Chlamydia trachomatis

Chlamydia trachomatis is an obligate intracellular bacterium that exhibits a unique biphasic developmental cycle that can be disrupted by growth in the presence of IFN-g and b-lactams, giving rise to an abnormal growth state termed persistence. Relatively little is known about the regulatory mechanisms that control temporal gene expression during the developmental cycle or the control of persistence and reactivation. Here we have examined the expression of a newly defined family of non-coding RNAs (ncRNAs) that are differentially expressed during the developmental cycle and the induction of persistence and reactivation (Using IFNγ and Carbenicillin). Non-coding RNAs were initially identified using an intergenic tiling microarray and were confirmed by Northern blotting. A group of 10 ncRNAs were mapped and characterized and compared to the previously described chlamydial ncRNAs (IhtA, pCHL antisense transcripts). The 5’ and 3’ ends of the ncRNAs were determined using an RNA circularization procedure. Promoter predictions indicated that all ncRNAs were expressed from s66 promoters and 9 ncRNAs contained non-templated 3’ poly-A or poly-AG additions. Expression of ncRNAs was studied by Northern blotting during i) the normal developmental cycle, ii) IFN-g-induced persistence, and iii) carbenicillin-induced persistence. Differential temporal expression during the developmental cycle was seen for all ncRNAs and distinct differences in expression were seen during IFN-g and carbenicillin-induced persistence and reactivation. Two of the studied ncRNAs were cis acting antisense molecules (CTIG270 and CTIG153). Expression of CTIG270 in a surrogate E. coli system along with its target gene ftsI proved that it was an antisense RNA, and it effectively controlled ftsI availability. A screening system was developed to determine the targets of potential trans-acting ncRNAs. The screen was composed of two compatible plasmids, a high copy effector plasmid expressing the ncRNA and a low/medium copy target plasmid expressing chlamydial library. Target plasmid contained translational fusion between chlamydial library and a positive/negative selection fusion system (ccdB/CAT fusion/TEV protease). The selection process to identify potential targets for ncRNAs was carried out over two stages. Stage one was to eliminate self ligated plasmids and non translational fusions, in this phase, only CAT+ ccdB resistant cells survived chloramphenicol selection i.e. cells representing true translational fusions survived antibiotic selection. Plasmids enriched for by stage one selection were subjected to stage two selection. In stage two ccdB sensitive cells were double transformed with both target plasmid and effector plasmid. Only in instances when ncRNA inhibits translation of ccdB would cells survive this selection. Stage two selection enriched for target(s) of ncRNA under test. We show in details the construction of this screening system and its functional aspect

Solutions and Formulae for Some Systems of Difference Equations

This paper is written to provide some solutions to the following systems of difference equations: where the initial data are arbitrary non zero real numbers

Modularity in artificial neural networks

Artificial neural networks are deep machine learning models that excel at complex artificial intelligence tasks by abstracting concepts through multiple layers of feature extraction. Modular neural networks are artificial neural networks that are composed of multiple subnetworks called modules. The study of modularity has a long history in the field of artificial neural networks and many of the actively studied models in the domain of artificial neural networks have modular aspects. In this work, we aim to formalize the study of modularity in artificial neural networks and outline how modularity can be used to enhance some neural network performance measures. We do an extensive review of the current practices of modularity in the literature. Based on that, we build a framework that captures the essential properties characterizing the modularization process. Using this modularization framework as an anchor, we investigate the use of modularity to solve three different problems in artificial neural networks: balancing latency and accuracy, reducing model complexity and increasing robustness to noise and adversarial attacks. Artificial neural networks are high-capacity models with high data and computational demands. This represents a serious problem for using these models in environments with limited computational resources. Using a differential architectural search technique, we guide the modularization of a fully-connected network into a modular multi-path network. By evaluating sampled architectures, we can establish a relation between latency and accuracy that can be used to meet a required soft balance between these conflicting measures. A related problem is reducing the complexity of neural network models while minimizing accuracy loss. CapsNet is a neural network architecture that builds on the ideas of convolutional neural networks. However, the original architecture is shallow and has wide layers that contribute significantly to its complexity. By replacing the early wide layers by parallel deep independent paths, we can significantly reduce the complexity of the model. Combining this modular architecture with max-pooling, DropCircuit regularization and a modified variant of the routing algorithm, we can achieve lower model latency with the same or better accuracy compared to the baseline. The last problem we address is the sensitivity of neural network models to random noise and to adversarial attacks, a highly disruptive form of engineered noise. Convolutional layers are the basis of state-of-the-art computer vision models and, much like other neural network layers, they suffer from sensitivity to noise and adversarial attacks. We introduce the weight map layer, a modular layer based on the convolutional layer, that can increase model robustness to noise and adversarial attacks. We conclude our work by a general discussion about the investigated relation between modularity and the addressed problems and potential future research directions

Health Related Quality of Life in Egyptian Children and Adolescents with Epilepsy

Background: Childhood epilepsy is one of the most significant and prevalent neurological condition in the developing years. The aim of the study was to explore the current status of health related quality of life (HR-QOL) in Egyptian children and adolescents with epilepsy using (WHOQOL-BREF) questionnaire. Patients and Methods: This case control study was carried out in Pediatric Neurology Unit and Outpatient Clinic in Department of Pediatrics  at Zagazig University Children's Hospital on 110 children, divided into 2 groups, case group included 55 children with epilepsy and control group included 55 apparently healthy children without epilepsy of matched age, sex and social class. All the children were subjected to history taking, clinical examination and assessment of QOL. Results: There was a significant decrease in all domains and total score of WHOQOL-Bref questionnaire in the case group. There was a significant  –ve correlation between age and psychological domain score, also between number of school failure  and both psychological and environmental  domain. Disease duration and treatment duration were negatively significantly correlated with all QOL domains. A significant +ve correlation was  found between social class score and  both general and environmental domain. There was a significant decrease in general and environmental  domain score  between cases with generalized and partial seizers compared to cases with absent seizers. Conclusion: Diminished  QOL is common in children with epilepsy than other children. Patients with epilepsy had lower mean scores of all domains of QOL, especially those with frequent fits, those with long duration, and in patients with generalized fits