A survey questionnaire was sent to 254 churches in the United States. An analysis of the answers of those giving a positive reply indicates that a great apostasy has taken place regarding the true Christian fast. Only a few small, independent churches seem to even approach Christ's ordained fast.It is claimed that great health benefits arise from wise periodic fasting. A physiological section analyzes the effects of fasting.A historical section presents the most important teachings and happenings of Gandhi, early reformers and practioneers, native races of America, U.S. presidents and state governments, early Christian history, and all large world religions.

<p>The mechanical behavior of tissues at the macroscale is tightly coupled to cellular activity at the microscale and tuned by microstructure at the mesoscale. Dermal wound healing is a prominent example of a complex system in which multiscale mechanics regulate restoration of tissue form and function. In cutaneous wound healing, a fibrin matrix is populated by fibroblasts migrating in from a surrounding tissue made mostly out of collagen. Fibroblasts both respond to mechanical cues such as fiber alignment and stiffness as well as exert active stresses needed for wound closure. </p> <p>To model wound healing mechanobiology, we first develop a multiscale model with a two-way coupling between a microscale cell adhesion model and a macroscale tissue mechanics model. Starting from the well-known model of adhesion kinetics proposed by Bell, we extend the formulation to account for nonlinear mechanics of fibrin and collagen and show how this nonlinear response naturally captures stretch-driven mechanosensing. We then embed the new nonlinear adhesion model into a custom finite element implementation of tissue mechanical equilibrium. Strains and stresses at the tissue level are coupled with the solution of the microscale adhesion model at each integration point of the finite element mesh. In addition, solution of the adhesion model is coupled with the active contractile stress of the cell population. The multiscale model successfully captures the mechanical response of biopolymer fibers and gels, contractile stresses generated by fibroblasts, and stress-strain contours observed during wound healing. We anticipate this framework will not only increase our understanding of how mechanical cues guide cellular behavior in cutaneous wound healing, but will also be helpful in the study of mechanobiology, growth, and remodeling in other tissues. </p> <p>Next, we develop another multiscale model with a bidirectional coupling between a microscale cell adhesion model and a mesoscale microstructure mechanics model. By mimicking the generation of fibrous network in experiment, we established a discrete fiber network model to simulate the microstructure of biopolymer gels. We then coupled the cell adhesion model to the discrete model to obtain the solution of microstructure equilibrium. This multiscale model was able to recover the volume loss of fibrous gels and the contraction from cells in the networks observed in experiment. We examined the influence of RVE size, stiffness of single fibers and stretch of the gels. We expect this work will help bridge the activity of cell to the microstructure and then to the tissue mechanics especially in wound healing. We hope this work will provide more rigorous understanding in the study of mechanobiology.</p> <p>At last, we established a computational model to accurately capture the mechanical response of fibrin gels which is a naturally occurring protein network that forms a temporary structure to enable remodeling during wound healing and a common tissue engineering scaffold due to the controllable structural properties. We formulated a strategy to quantify both the macroscale (1–10 mm) stress-strain response and the deformation of the mesoscale (10–1000 microns) network structure during unidirectional tensile tests. Based on the experimental data, we successfully predict the strain fields that were observed experimentally within heterogenous fibrin gels with spatial variations in material properties by developing a hyper-viscoelastic model with non-affined evolution under stretching. This model is also potential to predict the macroscale mechanics and mesoscale network organization of other heterogeneous biological tissues and matrices.</p>

No / This work investigates in detail several methodologies to improve the optimal control of discontinuous processes. It shows that whenever a batch dynamic optimization is solved, the optimum is related to the control methodology adopted and the result is a sub-optimum since other more (or apparently less!) appealing control methodologies might lead to "better" optimal solutions. The selection of the best control methodology for the dynamic optimization is broached for batch reactors using gPROMS models builder 3.5.2 for dynamic modeling and BzzMath 6.0 optimizers to handle control and optimization issues.

Background: The train communication network is vulnerable to intrusion assaultsbecause of the openness of the ethernet communication protocol. Therefore, an intru-sion detection system must be incorporated into the train communication network.There are many algorithms available in Machine Learning(ML) to develop the Intru-sion Detection System(IDS). Majorly, depending on the accuracy and execution timeof the algorithm, it is decided as the best. Performance metrics like F1 score, preci-sion, recall, and support are compared to see how well the algorithm fits the modelwhile training. The following thesis will detect the anomalies in the Train ControlManagement System(TCMS) and then the comparison of various algorithms will beheld in order to declare the accurate algorithm. Objectives: In this thesis work, we aim to research anomaly detection in a train’sreal-time ethernet using an IDS. The main objectives of this thesis include per-forming Principal Component Analysis(PCA) and feature selection using RandomForest(RF) for simplifying the complexity of the dataset by reducing dimensionalityand extracting significant features. Followed by, choosing the most consistent algo-rithm for anomaly detection from the selected algorithms by evaluating performanceparameters, especially accuracy and execution time after training the models usingML algorithms. Method: This thesis necessitates one research methodology which is experimen-tation, to answer our research questions. For RQ1, experimentation will help usgain better insights into the dataset to extract valuable and essential features as apart of feature selection using RF and dimensionality reduction using PCA. RQ2also uses experimentation because it provides better accuracy and reliability. Afterpre-processing, the data will be used to train the algorithms and will be evaluatedusing various methods. Results: In this study, we have analysed data using EDA, reduced dimensionalityand feature selection using PCA and RF algorithm respectively. We used five su-pervised machine learning methods namely, Support Vector Machine(SVM), NaiveBayes, Decision Tree, K-nearest Neighbor(KNN), and Random Forest(RF). Aftertesting and utilizing the "KDDCup 1999" pre-processed dataset from the Universityof California Irvine(UCI) ML repository, Decision Tree model has been concludedas the best-performing algorithm with an accuracy of 98.89% in 0.098 seconds, incomparison to other models. Conclusions: Five models have been trained using the five ML techniques foranomaly detection using an IDS. We concluded that the decision tree trained modelhas optimal performance with an accuracy of 98.89% and time of 0.098 seconds

In this work, the formulation and the implementation of innovative methodological paradigms for the design of unconventional array architectures for future generation communication systems has been addressed. By exploiting the potentialities of the codesign strategy for elementary radiators in an irregularly clustered array architectures and by introducing an innovative capacity-driven design paradigm, the proposed methodologies allow to effectively design unconventional array architectures with optimal trade-offs in terms of performance and complexity/costs. The codesign synthesis strategy is proposed to solve the arising massive multi-objective design problem aimed at fitting the multiple objectives and requirements on the "free-space" performance of the array architecture. Afterward, the capacity-driven design paradigm is formulated and implemented for the design of MIMO array architectures to maximize the quality of the communication system in first place instead of considering "free-space" figures-of-merit. A set of numerical results has been provided (i) to validate the proposed paradigms in real-application scenarios and (ii) to provide insights on the effectiveness, the limitations and the potentialities of proposed design methodologies.

The methodologies for English language teaching and the roles os ESP and EIL are discussed. Additionally, the role of culture and learning theories for prefessional training are presented. This framework is applied to two pilot programs and the results are debated. Consequently, a new framework is designed that includes new methodologies and places a greater importance on the role of EIL.

Background and Objectives Oral anticoagulants (OACs) are among Canada's most frequently prescribed drugs and a top cause of medication-related serious harm leading to emergency department visits, hospitalizations, and fatalities. During the preparation to launch a Canadian Institutes of Health Research (CIHR)-funded randomized controlled trial (RCT) called "Improving Anticoagulant Safety at Hospital Discharge: A Randomized Trial," we faced some issues. First, as the RCT addresses OAC management, we needed to determine the barriers and facilitators for optimal OAC management, which were not identified in our literature search. Second, there is no core outcome set (COS) specific for OACs and the choice of outcomes and their measurement for the trial was not obvious. Finally, the drug-drug interactions between the OACs and other medications are not fully understood, particularly with regards to important clinical outcomes. Identifying the interacting medications and their interaction effect size, is vital to guarantee the safety of patients. To address these issues, the objectives of this thesis were: (1) to determine the barriers and facilitators for optimal OAC management, (2) to define the potential list for the COS of OACs, and (3) to explore the drug-drug interaction of OACs. Methods Several research approaches, including a systematic review, a systematic survey, a scoping review, a population-based retrospective cohort study with time varying methods, and a qualitative study were applied in this thesis. First, we applied both a synthesis review and qualitative research to explore the barriers and facilitators for OACs management to guarantee the evidence's robustness. Next, we used a systematic survey to address the lack of consensus on outcomes used and their v definitions for OAC treatment clinical trials. Finally, we used a systematic review and planned a population-based study to address drug-drug interaction related to OACs. Methodologic challenges and innovation In the scoping review (Chapter 2: Barriers and facilitators to optimal oral anticoagulant management: a scoping review) and the focus group study (Chapter 3: Perceptions on patient education to improve oral anticoagulant management) we employed a qualitative approach. The main methodological challenge for both the scoping review and the focus group focused on the rigorous way to synthesize the themes. In Chapter 4, we used a systematic survey to explore the outcome list for OAC management research. The primary methodological challenge referred to the outcome reporting in the included studies. Not all outcomes performed in the trials can be reported for the space limitation or potential publication bias. In Chapters 5 and 6, a systematic review with meta-analysis and an observational protocol were used to explore the drug-drug interaction for OACs. The main methodological challenge for Chapter 5 was how to evaluate the drug-drug interaction (DDI) evidence systematically. The main methodological challenge for Chapter 6 is to address confounding and bias in a population-based protocol on DOACs drug-drug interaction. Conclusion In summary, this standard thesis describes five different background projects to prepare for an OAC management RCT. The papers contribute to the literature by using several research methodologies to provide useful evidence for OAC management and OAC research. / Thesis / Candidate in Philosophy / Oral anticoagulants (OACs) (blood thinners) are among Canada's most frequently prescribed drugs and a top cause of severe medication-related harm. The objectives of this thesis include (1) to determine the barriers and facilitators for optimal OAC management, (2) to define a potential list for the core outcome set of OACs, and (3) to explore the drug-drug interaction of OACs. First, we applied a scoping review and a qualitative study to explore the barriers and facilitators for OACs management. Then we conducted a systematic survey to address the lack of consensus on outcomes and their definitions for OAC treatment clinical trials. Finally, we used a systematic review and planned a population-based study to address drug-drug interaction related to OACs. Different research approaches, including a systematic review, a systematic survey, a scoping review, a population-based study, and a qualitative study, were involved in this thesis.

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