Reliability-Based Design of Reinforced Concrete Beams for Simultaneous Bending, Shear, and Torsion Loadings

Designing structural members is targeted in resisting against the loads such that the safety of considered structure is maintained regarding different conditions of loading. The method existing in ACI guideline is considered using load and resistance factors regardless of random nature of design parameters.  Existing uncertainties in design parameters such as load and resistance have caused changes in safety of structure and the use of constant coefficients in different states of loading has often caused design unsafely. The present research has discussed the design of all the probabilities for reinforced concrete beams subjected to bending, shear and torsion stresses. For this, analytical relations of limit state have been developed to combine different stresses. Monte Carlo method is the method used to calculate safety measures, in which safety surface of American Concrete Institute (ACI) and different limit states have been calculated for three different sections (T-shape, rectangular shape and L-shape). The results of paper indicate that the safety index is considered in the range of 3 to 4 at different limit states. Load and resistance coefficients have been calculated in different safety indices and influence of load and resistance coefficients on American Concrete Institute (ACI) have been examined. Using the proposed method, designer enables to take an action for design by changing the conditions governing the problems such as dimensions, load and features of the section regarding the safety of structure. Further, under use of constant coefficients with sufficient information on composition of the considered loads, the designer enables to design and ratio of load and different limit states of the considered structure. Studying influence of changes of numbers in load and resistance coefficients on American Concrete Institute (ACI) has been mentioned as the major objective of the present research, indicating that resistance coefficient has more significantly influence on American Concrete Institute (ACI) in different loading compositions.    &nbsp

Experimental Design for Causal Effect Identification

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the causal effect. In this work, we consider the problem of designing the collection of interventions with the minimum cost to identify the desired effect. First, we prove that this problem is NP-hard, and subsequently propose an algorithm that can either find the optimal solution or a logarithmic-factor approximation of it. This is done by establishing a connection between our problem and the minimum hitting set problem. Additionally, we propose several polynomial-time heuristic algorithms to tackle the computational complexity of the problem. Although these algorithms could potentially stumble on sub-optimal solutions, our simulations show that they achieve small regrets on random graphs.Comment: 53 pages, 13 figures, extending the findings of our ICML2022 pape

Numerical Investigation of the Seismic Behavior of Unanchored Steel Tanks with an emphasis on the Uplift Phenomenon

Ground steel storage tanks are widely used in different industries. Regarding the significance of these structures, ensuring the proper performance of such structures in earthquakes needs evaluating their seismic performance. The present study examines the seismic behavior of an unanchored fluid storage system via ABAQUS after validation using an experimental model. Next, the uplift of the bottom sheet is studied using the accelerogram records of the 1940 El Centro and 1994 Northridge earthquakes. The overturning moment time history of the fluid storage system and the maximum overturning moments were obtained to identify their behavior. The results indicated that not bracing storage tanks leads to the uplift phenomenon. Finally, the maximum axial stress of the storage tank shell was compared with the values recommended in the design codes to control the buckling

Multiple Crack Detection using Wavelet Transforms and Energy Signal Techniques

Wavelet transforms are efficient tools for structural health monitoring (SHM) and damage detection. However, these methods are encountered with some limitations in practice. Thus, signal energy analysis is used as an alternative technique for damage detection. In this paper, discrete wavelet transforms (DWT) and Teager energy operator (TEO) is applied to the curvature of the mode shapes of the beams, and the locations of the damages are identified. The results show that in comparison with the discrete wavelet transform, the signal energy operator has better performance. This superiority in detecting the damages, especially near the supports of the beam, is obvious and has enough sensitivities in low damage intensities. Additionally, the damage detection in the cases that the response data are noisy is investigated. For this purpose, by adding low-intensity noises to the curvature of the mode shapes, the abilities of the mentioned methods are evaluated. The results indicate that each method is not individually efficient in the detection of damages in noisy conditions, but the combination of them under noisy conditions is more reliabl

Estimation of atmospheric temperature and humidity profiles from MODIS data and radiosond data using artificial neural network

The aim of this study is to test the quality of the neural network for retrieving the temperature and humidity by comparison with the radiosond values and a linear regression method. Remote sensed images give useful information about the atmosphere. In this article, MODIS data is used to retrieve temperature and humidity profiles of the atmosphere. Two methods of linear regression and artificial neural network are used to retrieve the temperature and humidity profiles. A multilayer feed-forward neural network is tested to estimate the desired geophysical profiles. Retrievals are validated by comparison with coincident radiosond profiles

Causal Effect Identification in Uncertain Causal Networks

Causal identification is at the core of the causal inference literature, where complete algorithms have been proposed to identify causal queries of interest. The validity of these algorithms hinges on the restrictive assumption of having access to a correctly specified causal structure. In this work, we study the setting where a probabilistic model of the causal structure is available. Specifically, the edges in a causal graph exist with uncertainties which may, for example, represent degree of belief from domain experts. Alternatively, the uncertainty about an edge may reflect the confidence of a particular statistical test. The question that naturally arises in this setting is: Given such a probabilistic graph and a specific causal effect of interest, what is the subgraph which has the highest plausibility and for which the causal effect is identifiable? We show that answering this question reduces to solving an NP-complete combinatorial optimization problem which we call the edge ID problem. We propose efficient algorithms to approximate this problem and evaluate them against both real-world networks and randomly generated graphs.Comment: 27 pages, 9 figures, NeurIPS 2023 conference, causal identification, causal discovery, probabilistic model

A Methodological Study of the Views of Katz and Phillips about Religious Experience

Discussing the scope of religious experience has been one of the most important topics since the eighteenth century, and from that period until now, thinkers in various fields of study such as philosophy of religion, modern theology, theology and psychology of religion and ... Has drawn various opinions in these periods about its nature and nature, the scope of its studies, its function in human life and the essence of religion or its truth or falsity. Among other things, the phenomenologists and philosophers of religion have drawn dimensions and characteristics for religion, one of which is the empirical dimension of religion. Moral, legal, and ideological precepts may contribute to the emergence of certain emotions, such as astonishment, fear, and humility, and give rise to a wonderful and exhilarating experience, such as the presence of God or the transcendent, or the glorification of mystical beings and mystical and inner experiences. Become another, to be "quite distinct" from external experiences. Because people in many different religious traditions claim to experience God, Nirvana, or Brahman, and feel that such experiences give meaning and direction to their lives. It can be acknowledged that religious experience is one of the most important issues in the psychology of religion and the philosophy of religion. In the thought of constructivists such as Pradfoot and Katz, who mostly emphasize the explanation of religious experience in its mystical dimension, they believe that the nature of religious experience is influenced by the network of beliefs and mental concepts of the subject and there are no empty experiences of beliefs and concepts. On the other hand, in Phillips's approach, religious claims, although they do not have a cognitive and narrative aspect, but to explain the statements, one can look at their application in one's social life; In other words, in order to understand religious claims, we must know the areas of life forms and pay attention to the rules of the game of religion, which is a correct belief related to a person's way of life. In the present study, while examining the methodology of these views, we try to explain and examine the views of Katz and Phillips on religious experience

A The Evaluation of Knowledge Management in Supply Chain Using EFQM Framework, Fuzzy Multi-Attribute Decision Making and Multi-Objective Programming

One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM enabler isevaluated by fuzzy DEMATEL-ANP. In addition, Analytical Hierarchy Process (AHP) isapplied to evaluate the importance of each KM enabler in knowledge sharing amongsupply chain people. In the research, the multi-objective mixed integer programming isused to optimize knowledge management and select KM strategy in each part of SC.Likewise, it is approved to select suitable members of SC for Research and Development(R&D) unit of SC. Results show that each part of SC should focus on developing someKM enablers, and selection of a suitable strategy. These results also emphasis theeffectiveness of each KM enabler and their development in selecting of suitable membersfor R&D unit of SC

The Effects of Punica granatum

Background. We compared the efficacy of P. granatum (P) flower extract with that of silver sulfadiazine (SSD) for treating thermal burn injuries in rats. Methods. Ten Wistar rats in each group were topically given base cream, normal saline, cream containing 1% SSD, or creams containing 5% or 10% Punica granatum flower extract. The treatments were administered once daily until complete wound healing was observed. The wound area and healing time were assessed. In addition, percentage wound contraction and histopathological characteristics such as neovascularization and collagen formation were determined. The tannin content in P. granatum extract was determined. Results. The decrease in the average size of wounds on day 15 of the treatment was higher in rats treated with creams containing P. granatum extract than in rats treated with cream containing SSD (2.8±0.9 cm2 versus 8.4±3.2 cm2). The wounds completely healed on day 25 of the treatment in rats treated with creams containing P. granatum flower extract compared with those in rats treated with the other agents. Conclusion. These results indicated that P. granatum flower extract promoted wound healing in rats and could be used for managing burn injuries

Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-Adjusted life-years for 29 cancer groups, 1990 to 2017 : A systematic analysis for the global burden of disease study

Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.Peer reviewe