Recycling Agricultural Waste as a Part of Interior Design and Architectural History in Egypt

Egypt is defined as an agricultural country where its people put all produced crops to use, whether as food or clothing. An agricultural waste like straw, palm fronds, leaves and others are used in building and interior designing; they’re part of an individual’s lifestyle and culture. As time passed, all of this changed given that local agricultural materials were replaced with technology and new building materials. Farmers became uninterested in what happened to this waste that was burned as a means of disposal, this process has direct effects on public health and the environment.This research examines the problem of palm fronds (agricultural materials) as a wasted renewable source in Egypt. It will attempt to find methods to link these materials with Egyptian handicrafts using new treatments in manufacturing with the cradle to cradle idea to produce compressed panels, wallpapers and other objects used in interior design. This research is important because it aims to find sustainable environmental materials with modern designs using agricultural waste

Characterization and Chemical Kinetic Analysis of the Ignition of Representative Conventional and Bio-Derived Fuels

Fossil fuels are the main energy source in the world. However, they are responsible for negative environmental impacts, such as global climate change and rising sea levels. Biofuels are an environmentally friendly alternative which can substitute fossil fuels without major engine modications, especially in the transportation sector. Furans, a class of biofuels, are considered as possible alternative fuels for SI engines. They can be produced from sugars, derived from non-food biomass sources. This thesis is a contribution to fundamental characterization of their combustion properties. Reactivity trends in furan combustion are established through ignition delay measurements of selected furans; 2,5-dimethyl furan (DMF), 2-methyl furan (2-MF), and furan. The isomer effect on the ignition of alkylated furans is also investigated to understand the general trends between dimethyl and ethyl isomers of cyclic fuel components. Since near term use of biofuels involves blends with fossil fuels, the relative ignition behavior of the least reactive furan, DMF, the gasoline surrogate, iso-octane, and their blends, is investigated. Experiments are carried out in a shock tube, a reactor that can generate instantaneous high temperature and pressure conditions by means of reflected shock wave, leading to chemical reactions and subsequent ignition of a test mixture of fuel and oxidizer. Experimental results are compared with chemical kinetic model simulations and the models are analyzed to gain insight on leading chemical pathways. The experimental results for furans and iso-octane are compared to the most recent chemical kinetic models of each fuel and a combined DMF/iso-octane model is developed for the analysis of fuel blend combustion. The new blend model is used to clarify the chemical interactions during ignition of fuel blends. The thesis also considers the ignition of saturated furans. In this respect the ignition behavior of tetrahydrofuran (THF) and methyl tetrahydrofuran (MTHF) is investigated to establish relative reactivity trends. The results are put into context by comparing with the unsaturated furan, 2-MF. Cyclic fuel components of non-biofuel nature are considered. The high-temperature autoignition delay times of dimethyl and ethyl isomers of cyclohexane are carried out behind reflected shock waves to establish reactivity dierences between these dimethyl and ethyl isomers, which could further be explored in chemical kinetic modeling. The study is designed to test whether the observed trend is indicative of general reactivity differences between dimethyl and ethyl isomers of cyclic hydrocarbons, oxygenated or non-oxygenated. The ignition delay times of ECH are compared to model predictions to test the model performance. The pronounced dierences in the high-temperature ignition delay times of these isomers are clearly established using the shock tube technique and motivate further mechanistic explorations of distinguishing reaction pathways, without necessarily invoking the more complex low-temperature chemistry. With regards to model reduction, the existing Alternate Species Elimination (ASE) model reduction method is employed for the reduction of recently reported iso-octane and n-heptane models. The ASE approach is expanded into a stochastic species sampling approach, referred to as the Stochastic Species Elimination (SSE) method. The SSE method allows for a linear reduction process, and involves new features leading to reduced computational resource requirements, compared to the standard ASE method. Larger systems, such as the recent literature model of n-octanol, are approached with the SSE method with multiple species sampling, which allows for a less time consuming model reduction process. Resulting skeletal models are shown to adequately predict ignition delay times as well as flame propagation, compared to the predictions of the detailed models. The work advances understanding of biofuel combustion. The established reactivity trends between the various fuels investigated in this work is of great importance to transportation fuel technology. The resulting experimental data sets are expected to fill the gap in the understanding of furans and gasoline combustion. The combined DMF/iso-octane model is a main contribution that allows for better insight into the combustion chemistry of furans, iso-octane, and their blends. Further, the proposed SSE model reduction method contributes to the use of combustion chemistry in practical combustion analysis in the form of cost-effective reduced models

Simulating a Heat And Moisture transfer Panel (HAMP) for maintaining space humidity

The main objective of this thesis research is to test the applicability of a novel heat and moisture transfer panel (HAMP) in an office building to control the space humidity. A HAMP is a panel that uses a liquid desiccant to add or remove heat and moisture to or from a space. This thesis research uses the TRNSYS computer package to model an office building in four different cities representing four climatic conditions. The cities are Saskatoon, Saskatchewan; Chicago, Illinois; Phoenix, Arizona; and Miami, Florida; representing cold-dry, cool-humid, hot-dry, and hot-humid climates, respectively. The HAMP is employed in the office building with a radiant ceiling panel (RCP) system. Three other HVAC systems are examined and compared to the system employing the HAMP. The systems are: a conventional all-air system, a RCP system with 100% outdoor air, a RCP system with a parallel dedicated outdoor air system (DOAS), and the RCP system with the HAMP and 100% outdoor air. In the latter, the HAMP covers 10% of the ceiling area and uses lithium chloride solution as the liquid desiccant at different temperatures and concentrations. The results show that the HAMP is able to control the space humidity within the control limits in all climates. The HAMP also shows the ability to provide better humidity control than the other systems as it directly responds to the space latent loads. The HAMP is able to control the relative humidity between 26% RH and 62%, 24% RH and 57% RH, 27% RH and 60%, and 40% RH and 62% RH in Chicago, Saskatoon, Phoenix, and Miami, respectively. The HAMP is able to achieve a relative humidity of 35% in Chicago, Saskatoon, and Phoenix for 14%, 13%, and 20% of the working hours of the year, respectively. It is also able to achieve a relative humidity of 60% in Chicago, and Miami 10% and 55% of the working hours of the year, respectively. The results also show the potential of the RCP system with the HAMP to reduce the total energy consumed by a conventional all-air system in the hot climates by 40%, and 54% in Miami and Phoenix respectively, and in the cold climates by 14% and 23% in Saskatoon and Chicago, respectively

Efficaciousness of Mindfulness Interventions for Trauma Using Psychophysiological Measures: A Review

In recent decades the efficaciousness of mindfulness has been proven in a wide variety of contexts, but some crucial populations remain understudied. This review critically examines the literature on mindfulness in individuals with trauma using psychophysiological measures. Psychophysiological measures offer critical insight into this intersection of mindfulness and trauma due to the known somatic components in each, as well as serving as an objective response. Mindfulness-based treatments seem to show great promise in treating trauma, however there are significant limitations in the literature. Future studies should standardize the minimum length of treatment, utilize gender-balanced and ethnically diverse samples, and introduce psychophysiological measures such as heart rate variability

Development of Reduced Chemical Kinetic Models for the Numerical Simulation of Combustion and Emissions Behavior of Representative Conventional and Bio-derived Fuels

The study addresses two of the main challenges facing combustion modeling for transportation fuels: simultaneous simulation of non-related combustion problems and reducing the computational cost of the modeling process itself. To address the first challenge, researchers determine a characteristic flame time from thermal diffusivity and laminar burning velocity. Researchers examine parametric dependence of flame time and ignition delay time on pressure, temperature and equivalence ratio for methane, based on validated chemical kinetic mechanisms. The study reveals flame time and ignition delay time show similar temperature dependence, flame time has stronger dependence on equivalence ratio and weaker dependence on pressure than ignition delay time. The study also establishes a correlation to predict flame time, and subsequently, burning velocity, based on knowledge of the relevant auto ignition time. Differences between methane, propane and ethanol are also explored. Researchers address the second challenge in a chemical kinetic modeling study of the high-temperature ignition behavior of Tetrahydrofuran (THF), a promising second-generation transportation biofuel. The study implements a Stochastic Species Elimination (SSE) reduction approach to develop multiple skeletal versions of a detailed chemical kinetic model of THF from the literature based on ignition delay time simulations at various pressures and temperatures. The developed skeletal versions are combined into a global skeletal model. The study uses ignition delay time simulations using detailed and skeletal models, with good agreement observed at higher temperatures. Next, researchers use sensitivity analysis to identify the most important reactions responsible for the performance of the skeletal model. Finally, they perform reaction rate parameter modification for such reactions in order to improve the agreement of detailed and reduced model predictions with literature experimental ignition data. This work contributes toward improved understanding and modeling of the oxidation kinetics of conventional and bio-derived transportation biofuels, as well as the estimation of laminar burning velocity that can be encountered in turbulent combustion simulations. This would ultimately contribute into the design of cleaner and more efficient transportation systems, and support the testing and adoption of novel fuels as additives and/or replacement to conventional non-renewable fossil fuel

Understanding and Addressing Arab-American Mental Health Disparities

The landscape of mental healthcare and focus on disparities research in the United States has vastly improved in recent years. However, Arab-Americans continue to be a commonly overlooked group within the scope of the research. This trend is especially worrisome given detrimental factors for Arab-Americans that have arisen as a factor of 9/11 and in the scope of the 2016 United States Presidential Election. This work explores barriers to accessing formal mental health care and offers recommendations to reconcile them for Arab-Americans. The present study completes this through a review of the literature and an interview conducted by the author of a panel of mental health professionals at a community health organization in order to gain a contemporary perspective of the issue. Salient suggestions that arise from this study are reducing stigma in the community by incorporating increased usage of primary care and religious providers as well as family therapies; the allocation of Arabic-speaking translators to clinics or a focus on hiring Arabic-speaking practitioners; supporting safety-net insurance funding; increased education on what psychotherapy and mental illness are; and pushing the necessity of professional training in the culture, religion, and preferences of Arab-Americans

Traffic classification and prediction, and fast uplink grant allocation for machine type communications via support vector machines and long short-term memory

Abstract. The current random access (RA) allocation techniques suffer from congestion and high signaling overhead while serving machine type communication (MTC) applications. Therefore, 3GPP has introduced the need to use fast uplink grant (FUG) allocation. This thesis proposes a novel FUG allocation based on support vector machine (SVM) and long short-term memory (LSTM). First, MTC devices are prioritized using SVM classifier. Second, LSTM architecture is used to predict activation time of each device. Both results are used to achieve an efficient resource scheduler in terms of the average latency and total throughput. Furthermore, a set of correction techniques is introduced to overcome the classification and prediction errors. The Coupled Markov Modulated Poisson Process (CMMPP) traffic model is applied to compare the proposed FUG allocation to other existing allocation techniques. In addition, an extended traffic model based CMMPP is used to evaluate the proposed algorithm in a more dense network. Our simulation results show the proposed model outperforms the existing RA allocation schemes by achieving the highest throughput and the lowest access delay when serving the target massive and critical MTC applications

LoRaWAN-enabled Smart Campus: The Dataset and a People Counter Use Case

IoT has a significant role in the smart campus. This paper presents a detailed description of the Smart Campus dataset based on LoRaWAN. LoRaWAN is an emerging technology that enables serving hundreds of IoT devices. First, we describe the LoRa network that connects the devices to the server. Afterward, we analyze the missing transmissions and propose a k-nearest neighbor solution to handle the missing values. Then, we predict future readings using a long short-term memory (LSTM). Finally, as one example application, we build a deep neural network to predict the number of people inside a room based on the selected sensor's readings. Our results show that our model achieves an accuracy of $95 \: \%$ in predicting the number of people. Moreover, the dataset is openly available and described in detail, which is opportunity for exploration of other features and applications