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The combined effects of several complex phenomena cause the deterioration of elements in steel hydraulic structures (SHSs) within the US lock system: corrosion, cracking and fatigue, impact and overloads. Predicting the future condition state of these structures by the use of current condition state inspection data can be achieved through the probabilistic chain deterioration model. The purpose of this study is to derive the transition probability matrix using final elements modeling of a miter gate.

If predicted accurately, this information would yield benefits in determining the need for rehabilitation or replacement of SHS. However, because of the complexity and difficulties on obtaining sufficient inspection data, there is a lack of available condition states needed to formulate proper transition probability matrices for each deterioration case.

This study focuses on using a three-dimensional explicit finite element analysis (FEM) of a miter gate that has been fully validated with experimental data to derive the transition probability matrix when the loss of flexural capacity in a corroded member is simulated.

New methodology using computational mechanics to derive the transition probability matrices of navigation steel structures has been presented.

The difficulty of deriving the transition probability matrix to perform a Markovian analysis increases when limited amount of inspection data is available. The used state of practice FEM to derive the transition probability matrix is not just necessary but also essential when the need for proper maintenance is required but limited amount of the condition of the structural system is unknown.

This paper aims to review recent literature results on the equilibrium problem and the strengthening design of masonry vaults.

A Lumped Stress Method (LSM) is considered within the Heyman’s safe theorem, based on the definition of thrust surface of a masonry curved structure. In particular, the static problem of the vault is formulated by introducing a membrane continuous of the studied masonry structure to associate with a spatial truss through a nonconforming variational approximation of the thrust surface and membrane stress potential. A tensegrity approach based on a minimal mass design strategy, different strengths in tension and compression of the material is discussed within the strengthening strategy of masonry vaults.

The numerical results have highlighted the efficacy of the two numerical approaches to assess the vulnerability of existing structures and design optimal strengthening interventions of these structures.

The presented models can represent fast and useful tools to assess the vulnerability of existing structures and design optimal strengthening interventions with composite materials of these structures.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South Konawe District, Southeast Sulawesi Province in Indonesia.

Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the relationships between variables through direct and indirect influence testing.

The findings reveal that career patterns influence neutrality and organizational performance. Neutrality of the state civil apparatus in politics mediates career patterns and local government organizational performance. The findings indicate that, first, promotions most significantly influence the organization’s neutrality and performance. Second, demotions have the least influence on the organization’s robustness and performance.

This paper is among the first to examine the relationships amongst career patterns, neutrality, and organizational performance. Recommendations are provided to improve neutrality and organizational performance, that is, the need to increase promotions and reduce demotions.

This study aims to measure and further compare the countries in terms of the achievement in the degree of financial inclusion over the study period and between income groups considering 26 nations from Asia for the period 2013-2017.

While measuring the degree of financial inclusion, the study prepares an index using weighted arithmetic mean and the inverse of the Euclidean distance method. Further, comparison between the study period and between the income groups has been made using the dependent samples t-test as well as the Wilcoxon signed-rank test and independent samples t-test, respectively.

The study extends empirical insights by laying out the ranks for the countries considered for each of the study periods individually as well as in terms of mean financial inclusion scores for the study period. Further, comparison in terms of mean financial inclusion scores shows significant differences between the income groups, whereas the differences between the study periods turn out to be non-significant.

Less availability of intended variables over time restricts the predictive capability of sketching the phenomena in a true sense and claims further an exhaustive research to pursue in the future.

With the declining trend except for 2016-2017 in the achievement of financial inclusion scores over time, the study suggests emphasizing the initiatives targeted to include the excluded within the ambit of the formal financial system, which somehow seems unstable.

The novelty of the study lies in the portrayal of a measure that seems representative of the scale for development with deeper insight.

This paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock market index and cryptocurrencies. It investigates the relevant impact of RavenPack COVID sentiment on the dynamic of stock market indices and conventional cryptocurrencies as well as their Islamic counterparts during the onset of the COVID-19 crisis.

The authors rely on the methodology of Diebold and Yilmaz (2012, 2014) to construct network-associated measures. Then, the wavelet coherence model was applied to explore co-movements between GCC stock markets, cryptocurrencies and RavenPack COVID sentiment. As a robustness check, the authors used the time-frequency connectedness developed by Barunik and Krehlik (2018) to verify the direction and scale connectedness among these markets.

The results illustrate the effect of COVID-19 on all cryptocurrency markets. The time variations of stock returns display stylized fact tails and volatility clustering for all return series. This stressful period increased investor pessimism and fears and generated negative emotions. The findings also highlight a high spillover of shocks between RavenPack COVID sentiment, Islamic and conventional stock return indices and cryptocurrencies. In addition, we find that RavenPack COVID sentiment is the main net transmitter of shocks for all conventional market indices and that most Islamic indices and cryptocurrencies are net receivers.

This study provides two main types of implications: On the one hand, it helps fund managers adjust the risk exposure of their portfolio by including stocks that significantly respond to COVID-19 sentiment and those that do not. On the other hand, the volatility mechanism and investor sentiment can be interesting for investors as it allows them to consider the dynamics of each market and thus optimize the asset portfolio allocation.

This finding suggests that the RavenPack COVID sentiment is a net transmitter of shocks. It is considered a prominent channel of shock spillovers during the health crisis, which confirms the behavioral contagion. This study also identifies the contribution of particular interest to fund managers and investors. In fact, it helps them design their portfolio strategy accordingly.

By observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.

In the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.

It is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.

The Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.