Miracle-dz/UniFAR-FTUs huggingface dataset:
An optimized product development process for aircraft gas turbine engines

1 BARKER I Acknowledgements I would like to thank my two thesis advisors, Professor Warren Seering and Dr. John Saabas for the many hours and patient guidance that they devoted to guiding me in the task of writing this thesis. I am also indebted to Dan Breitman, Ian McCormick and Rick Marks for sharing their vast experience of running major projects at Pratt & Whitney Canada. I am grateful to Anne Jones for transcribing all the interviews as well as helping put this thesis together, to Gerard Stack for proof reading this document and Edward Hoskin for his help in formatting this thesis. Many thanks to all my MIT classmates in particular my SDM colleagues for all the stimulating and enjoyable time we spent together. Last but not least I am grateful to my wife Shifra and my children for supporting my efforts during this program. The eventual success or failure of a project is often determined by how the program was managed from initiation until it is finally certified and introduced into the field. This Thesis will concentrate on projects that are large in nature and the success or failure of the project has a real impact on the financial well being of the company involved. Steve Eppinger and Karl Ulrich, in their book, "Product Design and Development"(1), defines Project Management as the activity of planning and coordinating resources and tasks to produce products that meet their goals. Project execution involves coordinating and facilitating the myriad of tasks required to complete a project in the face of inevitable unanticipated events and the arrival of new information. This thesis will propose and evaluate an optimum methodology to accomplish this. All projects start by a concept being sold to someone-either to an end customer or to a board of executives for approval. There is a limited time frame coupled with limited resources for the Project Management Team to fully understand all the unknowns before the Project is presented. All funds used have to be internal risk money, which is lost if the Project is not given a go ahead. At the point where the Project is sold, commitments, that must be kept in the future, are made. The Project Manager does not want to invest a lot of resources into a Program, which he doesn't know for sure will move forward. On the other hand once he makes the commitments he …
Seasonal Wind Power Potential for a Resort Island in the South China Sea

This paper presents a wind energy assessment for a resort island in the South China Sea that has a seasonal climate contributed by the monsoon seasons. The resort island selected for this study is Tioman, as it denotes the typical energy requirements of most resort islands in the South China Sea. The island depends primarily on diesel-fuel for electricity generation. However, diesel is subjected to expensive and unpredictable market values, high operation and maintenance costs, and poses environmental threats. Therefore, the potential for wind energy conversion system development is conducted in order to reduce the island’s diesel fuel dependency. The study starts with energy auditing and meteorological data collection. Subsequently, the wind energy potential is evaluated using Weibull distribution function. The results indicate that the wind speed vary according to seasons, where higher wind power can be generated during the northeast monsoon season than any other seasons.
Low Power Analog Front End for ExG Acquisition with Automatic Gain Control and Analog Classification

Cardiovascular diseases have been known to cause large number of deaths globally. For prevention and early detection of these diseases, continuous monitoring of ecg signals is required. With recent advances in IC technology, implantable ICs have seen the light of the day. Considering the im-plantable devices, power consumed by the system needs to be as less as possible without sacrificing the performance of the readout circuit.
Pediculosis Is a Risk Factor for Iron Deficiency Anaemia

Pediculosis capitis is obligate ectoparasite that lives and feeds on host blood, affecting commonly children. Lice are transmitted easily and respond to topical treatment with good personal hygiene. Chronic infestation can lead to different complications such as bacterial infection dermatitis and anaemia. Haematological complications are not reported frequently. We report a case series of five patients presented with a clear manifestation of anaemia with heavy lice infestation. Laboratory evaluation revealed microcytic hypochromic anaemia (red blood cell indices) with low serum iron levels and other causes that were excluded. All patients who were admitted received blood transfusions. There was not a possible explanation for this severe anaemia other than head lice.
Graph compilers for AI training and inference

Artificial Intelligence, the attempt to create an intelligent agent, gained popularity with the success of AlexNet for image recognition in 2012. The proposed combination of stacked neural networks (called Deep Neural network) and the use of GPUs to drastically reduce network training times compared to previous iterations, led to a boom in the use of such networks for image recognition and speech recognition.
DETECTION OF PNEUMONIA IN PATIENTS USING CHEST X-RAY IMAGES BASED ON CONVOLUTIONAL NEURAL NETWORKS

Pneumonia is a respiratory disease which inflames one or both lungs, and lungs may fill up with fluid. This can cause fever, chills, cough with phlegm or pus. It is a harmful disease that can be fatal in some cases. It is critical to detect pneumonia early, with a model which could help doctors reduce workload and bring in more accuracy in detection of pneumonia. In this work, we propose a model which is designed for the diagnosis of pneumonia that is trained on digital chest X-ray images to accurately diagnose pneumonic lungs. In the author’s opinion, this could benefit the medical field in the near future. Keywords: CNN, Keras, Pneumonia
Elastoplastic and Damage Analysis of Trusses Subjected to Cyclic Loading

In the present paper, the Preisach model of hysteresis is extended to structural analysis of trusses damaged under cyclic loading in plastic range. Parameters for the Preisach model of cyclic plasticity are obtained from uniaxial loading experiment. Damage, as a consequence of micro cracks appearance due to alternating loading in plastic domain, is modeled using brittle elements according to Preisach procedure. Results of this research are compared with the already existing in the literature. In the paper examples of trusses under various cyclic loadings are presented.
The role of antibodies to peripheral nerve antigens in pathogenesis and laboratory evaluation of immune-mediated neuropathies

Detection of antiganglioside autoantibodies and their association with clinically defined subtypes implicate an autoimmune mechanism of peripheraland cranial nerve damage in peripheral neuropathies. Increased titer of antibodies that react with human peripheral nerve antigens have been reported in patients with motor neuropathy including Guillain-Barré syndrome,chronic inflammatory demyelinating polyneuropathy, multifocal motor neuropathy and sensory motor neuropathy. This study represents review of the data related to increased titers of anti-glucoconjugate antibodies in different autoimmune neuropathies and their correlation with existence of structural homology between bacterial and glycoconjugated structures, as a basis for understanding the immune pathological response to glycoproteins and glycolipids present in the human peripheral nerve as target antigens in autoimmune neuropathies. Evaluation of presence and increased level of autoantibodies against peripheral nerve antigens could be an important parameter in laboratory evaluation, diagnosis and prognosis of autoimmune neuropathies and contribute in more efficient therapeutic approaches in treatment of these pathological conditions. Keywords: anti-glycoconjugate antibodies, anti-ganglioside antibodies, peripheral nerves, autoimmune neuropathies
The use of deliberates practices on a mobile learning environment

Mobile learning brings the opportunity to do practices and activiti es anywhere in our daily life. However learning for expertise requires more than daily activities, it requires deliberate practices. Different than daily activities and practices, deliberate practices are specific and well designed activities for gradually gaining and improving expertise with the help of teacher led feed-backs. This paper introduces the use of deliberates practices on a mobile learning environment. This paper describes the system design and applications including both teacher and student side of the mobile learning environment. The teacher side consists of a management module for the learning objects pool creation and student monitoring. Student side consists of a content pulling module for deliberate practices and a self and personalized learning monitoring system. This paper would be helpful for teachers and instructional designers and mobile learning platform designers to understand the mechanisms behind the design practices for the notion of deliberate practices. Keywords: Mobile Learning,Deliberate Practices,Expertise;
The effect of mineral composition on direct aqueous carbonation of ultramafic mine waste rock for CO2 sequestration, a case study of Turnagain ultramafic complex in British Columbia, Canada

ABSTRACT The heterogenous mineralogy of ultramafic mine waste rocks make their carbonation rate hard to evaluate. This study investigated the effect of mineral composition on direct aqueous carbonation, through quantitative X-ray diffraction. The results show that magnesite was the main carbonated product, which was a stoichiometric conversion of forsterite. Diopside acted as a seed for quick crystallisation of magnesite. Lizardite could enhance the carbonation conversion, which reaches the optimum value when the weight ratio of lizardite to forsterite is 0.3–0.4. Sulphide in the reactant samples has a positive influence on carbonation. Brucite, magnetite and maghemite show little influence on carbonated products.
Forensic Analysis of WhatsApp SQLite Databases on the Unrooted Android Phones

WhatsApp is the most popular instant messaging mobile application all over the world. Originally designed for simple and fast communication, however, its privacy features, such as end-to-end encryption, eased private and unobserved communication for criminals aiming to commit illegal acts. In this paper, a forensic analysis of the artefacts left by the encrypted WhatsApp SQLite databases on unrooted Android devices is presented. In order to provide a complete interpretation of the artefacts, a set of controlled experiments to generate these artefacts were performed. Once generated, their storage location and database structure on the device were identified. Since the data is stored in an encrypted SQLite database, its decryption is first discussed. Then, the ways of analyzing the artefacts are revealed, aiming to understand how they can be correlated to cover all the possible evidence. In the results obtained, it is shown how to reconstruct the list of contacts, the history of exchanged textual and non-textual messages, as well as the details of their contents. Furthermore, this paper shows how to determine the properties of both the broadcast and the group communications in which the user has been involved, as well as how to reconstruct the logs of the voice and video calls. Doi: 10.28991/HIJ-2022-03-02-06 Full Text: PDF
Regulation of nitrogen fixation in Klebsiella pneumoniae: The role of Fnr in oxygen signal-transduction

In Klebsiella pneumoniae transcriptional activity of NifA is modulated by NifL in response to combined nitrogen or molecular oxygen. NifL a flavoprotein, which is redox-sensitive, apparently mediates the oxygen signal towards NifA through a conformational switch. We recently showed that in a fnr null mutational K. pneumoniae strain NifL does not receive the signal for anaerobiosis, resulting in an inhibitory conformation of NifL. Indicating, Fnr seems to be involved in the signal transduction pathway, directly or indirectly. We proposed that fnr-dependent genes, the products of which function to relieve NifL inhibition by reducing the FAD moiety of NifL, resulting in a non-inhibitory conformation. We further hypothized that members of the anaerobic electron transport chain could be involved in this signal transduction. Interestingly, in a anerobic and nitrogen limited K. pneumoniae fnr-null mutant 95% of NifL protein is located in the cytoplasm, contrarely to the conditions in the wild type, where 55% of NifL is found in the membrane fraction. In the mutant strain, the spatial gap between NifL and NifA, which allows NifA to enhance transcription of the nif-genes, is abolished.In K. pneumoniae wild type strains under oxygen limitation NifL is mainly located at the cytoplasmic membrane and recieves electrons leading to a reduced FAD cofactor, which allows NifL to retain the non-inhibitory conformation. Consequently, we started experiments to reduce oxidized NifL using reduced inside out vesicles and quinone derivatives in the presence of NADH. We clearly demonstrated that both membrane vesicles and quinone derivatives are highly potential in electron transduction from NADH towards NifL. Indicating that electrons from the anaerobic respiratory chain, which are mainly found in the quinone pools in the cytoplasmic membrane are used to reduce the FAD moiety of NifL resulting in a non-inhibitory conformation of the protein. These findings were confirmed by K. pneumoniae strains carrying null mutations of anaerobic reductases, for example NADH-oxidoreductase. These mutant strains failed to relieved NifL inhibition or showed reduced nifH-lacZ transcription levels in the appropriate genetic backgrounds.We favor a model in which NifL is membrane associated under anaerobic and nitrogen limited conditions and recieves electrons from the anaerobic respiratory chain, especially from the reduced quinone pools, resulting in a non-inhibitory conformation.
Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University’s research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria. ac.uk/policies.html
Long noncoding RNA MEG3 activates neuronal necroptosis in Alzheimer’s disease

Neuronal cell loss is a defining feature of Alzheimer’s disease (AD), but it remains unclear how neurons die and how this relates to other defining characteristics of the disease1. Existing in vivo AD models only partially recapitulate the neuropathology of AD with very mild or no neuronal cell loss. Here we demonstrate that human neurons xenografted in mouse brain exposed to amyloid pathology develop sarkosyl-insoluble tau filaments, positive Gallyas silver staining, release phosphorylated tau (P-tau181) into the blood, and display considerable neuronal cell loss, providing a model for the induction of full Tau pathology by simple exposure to amyloid pathology in AD. The alterations are specific to human neurons and contrast with the mild effects exhibited in mouse neurons. A core transcriptional program in the human neurons is characterized by strong upregulation of MEG3, a neuron-specific long noncoding RNA. MEG3 is also strongly upregulated in neurons from AD patients in situ. MEG3 expression alone is sufficient to induce necroptosis in human neurons in vitro. Orally administered small molecule receptor-interacting protein (RIP) kinase -1 and -3 inhibitors rescued the neuronal cell loss in this novel AD model. Thus, xenografted human neurons are uniquely sensitive to amyloid pathology, recapitulate all the defining neuropathological features of AD, and ultimately die by necroptosis.
Research and Production Status of Dual Phase Steels for Automobiles

Dual phase steels are developed rapidly in automobile industry because of their excellent mechanical properties and formability and they have become ideal automobile steels.At present,there exists a comparative gap between China and foreign countries both in theory research and practice production of dual phase steels.Research status and direction of dual phase steels are introduced.It is pointed out that more attention should be paid to the research of high strength,galvanization and grain refinement of dual phase steels to suit the rapid increase requirements of dual phase steels for automobiles.
Critical success factors of adapting heritage buildings: an exploratory study

Purpose – The loss of heritage buildings should be avoided as they provide a tangible example of a period of life that is now gone. Adaptive re-use enables buildings to be given a second life, enabling them to live on when they may have been previously underutilized. Changing the capacity, function or performance of underutilized buildings for a different purpose, or to suit new conditions, or making use of pre-existing structural elements has become necessary to preserve heritage buildings. The purpose of this paper is to identify the critical success factors (CSF) for the adaptive re-use of heritage buildings. Design/methodology/approach – Identification of CSF for adaptive re-use can provide asset owners, developers and key stakeholders with the knowledge needed to ensure a project is delivered successfully. Due to a lack of research in the area of CSF for heritage buildings, an exploratory approach was undertaken. Semi-structured interviews were undertaken with stakeholders to solicit their views as t.
What Matters Most in Demand Model Specifications: A Comparison of Outputs

This paper examines the impact of specific travel demand modeling (TDM) disaggregation techniques in the context of small- to medium-sized communities. While larger metropolitan regions have incorporated behavioral disaggregation into the traditional four-step modeling framework, small- to medium-sized communities, now also facing plaguing congestion, typically rely on less sophisticated TDM frameworks. This paper focuses on evaluating specific TDM improvement strategies for predictive power and flexibility with case studies based on the Tyler, Texas network and zone system. Model results suggest that adding time-of-day disaggregation, particularly in conjunction with multi-class assignment, to a basic TDM framework has the most significant impacts on TDM outputs. Other model improvements shown to impact TDM outputs include adding a logit mode choice model (particularly in networks with higher shares of non- auto trips) and incorporating a congestion feedback loop (from the assignment step back to the trip distribution step). For resource-constrained communities, this paper’s results illuminate which model improvements offer the best prediction and model flexibility for various settings and scenarios, allowing for more thoughtful (and cost-effective) specification decisions.
Ultra-Low Loss 600V - 1200V GaN Power Transistors for High Efficiency Applications

An emerging generation of high voltage (600V - 1200V) GaN HEMTs are compared to the best in class existing technologies and are shown to maintain a significant advantage in switching performance. Compared to the latest available GaN and Si superjunction MOSFET at 650V, these GaN devices show > 5X lower switching energies with an Ron Qg product less than 1 nC Omega. These GaN devices are extended to show > 1200V breakdown voltages and have switching losses 4X lower than even SiC MOSFETs with similar ratings.
Analysing Food Innovation Drivers: Chefs’ Perspectives

ABSTRACT This study has two main objectives. First, to investigate the various attributes influencing food innovation. Second, to analyze the relationships of different factors and their implication on food innovation in India’s restaurants (fine dining &multi-cuisine). A quantitative methodology with exploratory and confirmatory analysis was conducted. Data collection was conducted by questionnaire (n356) survey. Both descriptive and inferential statistics were used to analyze the data. Descriptive statistics were used to identify factors influencing food innovation among the chefs, and inferential statistics were used to analyze the significant relationship among the factors influencing food innovation. Results show that food innovation is influenced by recipe development, menu merchandising, customer satisfaction, and advertising. This study also underlines the significant relationships that exist among different factors which impact food innovation.
A Method for Automatic Lane Detection using a Deep Network

Lane detection is amongst the most important operations during the automatic driving process. This process aims to detect lane lines to control the vehicle’s direction in a specific lane on the road and it can be effective in preventing accidents. Besides being online, the most requirement for lane detection methods in automatic driving is their high accuracy. The use of deep learning to create fully automated systems in lane detection has been done extensively. Automated learning-based methods used for road lane detection are often of supervised type. One of the disadvantages of these methods, despite their excellent accuracy, is that they need a set of labeled data, which limits the development procedure of the lane detection system, and most importantly establishing a standard set of labeled data is very timedemanding. The recommended solution is to use appropriate learning approaches that can be used to achieve the relative accuracy of the supervised approaches and to improve their speed. It also enables us to use different datasets without a constraint label that the tagged dataset would create in the algorithm development relative to the new dataset. In this research, we present an automatic semi-supervised learning method using deep neural networks to extract the data of lane lines, using labeled (mask for detected lines) and unlabeled datasets. The results demonstrate the suitable accuracy of the adopted method according to the proposed approach and also improves its computational complexity due to the significant reduction in the number of teachable network parameters. doi: 10.5829/ije.2022. 35.04a. 20