Efficient Code for Relativistic Quantum Summoning

Summoning retrieves quantum information, prepared somewhere in spacetime, at another specified point in spacetime, but this task is limited by the quantum no-cloning principle and the speed-of-light bound. We develop a thorough mathematical framework for summoning quantum information in a relativistic system and formulate a quantum summoning protocol for any valid configuration of causal diamonds in spacetime. For single-qubit summoning, we present a protocol based on a Calderbank-Shor-Steane code that decreases the space complexity for encoding by a factor of two compared to the previous best result and reduces the gate complexity from scaling as the cube to the square of the number of causal diamonds. Our protocol includes decoding whose gate complexity scales linearly with the number of causal diamonds. Our thorough framework for quantum summoning enables full specification of the protocol, including spatial and temporal implementation and costs, which enables quantum summoning to be a well posed protocol for relativistic quantum communication purposes.Comment: 15 pages, 7 figure

Generating UML class diagram from source codes using multi-threading technique

The traditional Software Development Life Cycle (SDLC) often includes four phases: analysis, design, implementation, and testing. Reverse engineering is the process of moving back those phases by analyzing the software system and then representing it at the higher levels of abstractions. The reverse engineering software process generates high level information from the implementation phase. This information includes generating several diagrams and specification documents that describe the implemented software. The UML class diagram represent a valuable source of information even after the delivery of the software. Class diagram extraction can be done either from software’s source code, or from the executable file. In the case of source code, a review of the current tools shows that many researchers have been extracting the UML class diagram from an object-oriented source code based on the sequential processing approach. In this research, a proposed approach for extracting a class diagram from the source code is presented. The proposed approach relies on multi-threading technique in the class diagram extraction which is representing the parallel processing. The motivation behind using multi-threading technique is that, it gives an advantage of faster processing to any software because the threads of the program naturally lend themselves to truly concurrent execution. In this research, a class diagram extraction using multi-threading technique is designed and implemented using the C# programming language. The implemented approach is tested on three case studies that contain several types of entities and relationships between them. Testing results show that the time needed to extract class diagram using multi-threading technique for the tested three cases is less than the time needed in extracting the same class diagram without using multi-threading technique

Applications of Machine Learning Methods in Health Outcomes Research: Heart Failure in Women

There is robust evidence that heart failure (HF) is associated with substantial mortality, morbidity, poor health-related quality of life, healthcare utilization, and economic burden. Previous research has revealed that there are sex differences in the epidemiology, etiology, and disease burden of HF. However, research on HF among women, especially postmenopausal women, is limited. To fill the knowledge gap, the three related aims of this dissertation were to: (1) identify knowledge gaps in HF research among women, especially postmenopausal women, using unsupervised machine learning methods and big data (i.e., articles published in PubMed); (2) identify emerging predictors (i.e., polypharmacy and some prescription medications) of incident HF among postmenopausal women using supervised machine learning methods; (3) identify leading predictors of HF-related emergency room use among postmenopausal women using supervised machine learning methods with data from a large commercial insurance claims database in the United States. This study utilized machine learning methods. In the first aim, non-negative matrix factorization algorithms were used to cluster HF articles based on the primary topic. Clusters were independently validated and labeled by three investigators familiar with HF research. The most understudied area among women was atrial fibrillation. Among postmenopausal women, the most understudied topic was stress-induced cardiomyopathy. For the second and third aims, a retrospective cohort design and Optum’s de-identified Clinformatics® Data Mart Database (Optum, Eden Prairie, MN), de-identified health insurance claims data, were used. In the second aim, multivariable logistic regression and three classification machine learning algorithms (cross-validated logistic regression (CVLR), random forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms) were used to identify predictors of incident HF among postmenopausal women. The associations of the leading predictors to incident HF were explored with an interpretable machine learning SHapley Additive exPlanations (SHAP) technique. The eight leading predictors of incident HF consistent across all models were: older age, arrhythmia, polypharmacy, Medicare, chronic obstructive pulmonary disease (COPD), coronary artery disease, hypertension, and chronic kidney disease. Some prescription medications such as sulfonylureas and antibiotics other than fluoroquinolones predicted incident HF in some machine learning algorithms. In the third aim, a random forest algorithm was used to identify predictors of HF-related emergency room use among postmenopausal women. Interpretable machine learning techniques were used to explain the association of leading predictors to HF-related emergency room use. Random forest algorithm had high predictive accuracy in the test dataset (Area Under the Curve: 94%, sensitivity: 93%, specificity: 77%, and accuracy: 0.81). We found that the number of HF-related emergency room visits at baseline, fragmented care, age, insurance type (Health Maintenance Organization), and coronary artery disease were the top five predictors of HF-related emergency room use among postmenopausal women. Partial dependence plots suggested positive associations of the top predictors with HF-related emergency room use. However, insurance type was found to be negatively associated with HF-related emergency room use. Findings from this dissertation suggest that machine learning algorithms can achieve comparable and better predictive accuracy compared to traditional statistical models

Primary Health Care Service in Saudi Arabia Old Dominion University Saudi Students Prospectives

The main goal of this study was to answer the following objectives: 1. To examine the level of satisfaction including accessibility, quality of care, doctor\u27s treatment, and health information provided with the Primary Health Care Services in Saudi Arabia; 2. To find how the Old Dominion University Saudi students compared these services with U.S. health care services; 3. To determine Old Dominion University Saudi student\u27s views and recommendations for changes that would be helpful to generate other ways for improving current practices of Primary Health Care in Saudi Arabia

THz Electronics for Data Centre Wireless Links - the TERAPOD Project

This paper presents an overview of the terahertz (THz) resonant tunneling diode (RTD) technology that will be used as one of the approaches towards wireless data centres as envisioned on the eU H2020 TERAPOD project. We show an example 480 gm × 680 gm THz source chip at 300 GHz employing a 4 gm × 4 gm RTD device with 0.15 mW output power. We also show a basic laboratory wireless setup with this device in which up to 2.5 Gbps (limited by equipment) was demonstrated

Bank Recourse to the Beneficiary Post Implementation Irrevocable Documentary Letter of Credit Contract )A Comparative Study(

It is hard to imagine, at least materially, that either of the business transaction parties adhere to his/her commitments spontaneously. This is due to the fears inflicted on both parties, which consequently resulted in the creation of distrust between both parties. Therefore, it was better to devise a method represented by legal and institutional forms that will ensure availing guarantees for two remotely separated persons in terms of place. Thus, each party will start implementing his/her obligations with no fear of the non fulfillment of the other party. For these reasons, and in connection with the documents, the documentary letter of credit was devised, which was made into several forms, dependent on the angle through which it is viewed. It is, in terms of the bank adherence power, confirmed or not confirmed; and in terms of the involvement of many banks in the transaction, it is reinforced or not reinforced; still in terms of whether or not terminable, it is revocable or irrevocable. Contrary to the revocable letter of credit, which the bank opens, under the order of the buyer, for the beneficiary of the seller, he/she leaves for him/herself the choice of revocability, any time in this letter of credit, without arranging any commitment by the bank toward the beneficiary; the irrevocable letter of credit represents to the beneficiary not only the possibility of getting the price of the goods from the bank that opened the L/C, but also provides to him/her an quasi absolute guarantee that the bank will honor the payment of the price of the goods, once he/she presents the required documents and honored all the conditions duly stipulated in the L/C. But before this final, irrevocable, non-amendable undertaking (except under the agreement of all the parties), there is a problematic issue that is raised: “ To what extent is the bank capable to recourse to the beneficiary following the implementation of the documentary letter of credit contract?” This study tackled this problematic issue through the illustration of the legal position of the bank in terms of its relation with the beneficiary of the irrevocable documentary letter of credit, post implementatio

Applicability of a Picosecond Laser for Micro-Polishing of Metallic Surfaces

An increasing number of recent technological advancements is linked to the adoptions of ultra-short pulsed picosecond (ps) lasers in various material processing applications. The superior capability of this laser is associated with precise control of laser-material interaction resulted from extremely short interaction time. In this context, the present study explored the applicability of a ps laser in laser micro-polishing (LµP) of Inconel 718 (IN718) and AISI H13 tool steel. The melting regime ‒ a mandatory phase for LµP ‒ was determined experimentally by the variation of focal offset to attain desired laser fluence. The finite element formulation of heat transfer equation and its solution were also estimated in order to develop a theoretical foundation for the heat transfer mechanism in ps laser-material interaction. The initial one dimensional (1D) line polishing experiments were performed on ground IN718 and H13 tool steel samples with the parameters related to the melting regime of corresponding material. The knowledge of this initial experimental investigation was later utilized to prepare the surface topography by micromilling with a specific step-over and scallop height, followed by LµP experiments with the same set of aforementioned parameters. The performance of LµP was evaluated by average surface roughness (Ra) spectrum at different spatial wavelength intervals along the laser path trajectory. Additionally, statistical measures, such as power spectral density (PSD) function, transfer function (TF) and material ratio (MR) curve were analyzed in order to establish the process parameters resulting the best possible surface quality. From the analysis of this experimental investigation, surface quality improvement up to 78.5% and 75.7% were reported for the spatial wavelength interval of 50‒100 µm for IN718 and H13 tool steel respectively. As a next step, two dimensional (2D) areal polishing of micromilled IN718 and H13 tool steel were performed, where surface quality improvement up to 69.32% and 77.28% were observed for the spatial wavelength interval of 50‒100 µm for IN718 and H13 tool steel, respectively. Overall, ps LµP was found to be an effective way of enhancing desired surface quality as demonstrated by the reduction of surface asperities as well as their volumetric uniform redistributions