Time Of Settlement Research Articles

Deep Neural Networks for Predicting the Settlement of Earth Dams Based on the InSAR Outputs

Earth dams play a crucial role in water resource management, necessitating effective maintenance to ensure prolonged functionality and safety. Monitoring these dams traditionally involves methods such as surveying and instrumentation. However, challenges arise from equipment malfunctions and absences, especially in dams affected by environmental changes. In response to these challenges, the cost-effective and adaptable nature of Interferometric Synthetic Aperture Radar (InSAR) has made it a preferred choice for monitoring. Despite their advantages, traditional numerical models like finite element methods have limitations in predicting deformation comprehensively, particularly due to intricate, non-linear correlations involving material type and environmental conditions. To overcome these limitations, this research employs deep learning techniques, specifically Long Short-Term Memory (LSTM) network, to capture intricate relationships and accurately predict dam behavior. Time series data from InSAR, representing settlement, are decomposed into trend and seasonal components using Artificial Neural Networks (ANN) for trend prediction. Furthermore, an LSTM network is utilized to handle the complexity of the seasonal component and its correlation with environmental factors. This network incorporates settlement, precipitation, temperature, and reservoir water level time series as inputs, thereby enhancing prediction accuracy. The research outcome presents a robust solution that holds the promise of increased accuracy and efficiency in predicting, monitoring, and serving as an early warning system for earth dam deformations over time. Such advancements are crucial for ensuring the safety and integrity of critical infrastructure in the face of evolving environmental conditions.

Outer membrane vesicles from commensal microbes contribute to the sponge Tedania sp. development by regulating the expression level of apoptosis-inducing factor (AIF)

The transition from the swimming larval stage to the settlement stage represents a significant node in the marine sponge developmental process. Previous research has shown that the outer membrane vesicles (OMVs) from the bacterial species Tenacibaculum mesophilum associated with the sponge Tedania sp. influence larval settlement: low concentrations of OMVs increase the attachment rate, whereas high concentrations decrease the attachment rate. Here, by comparing the transcriptomes of sponge larvae in filtered seawater (FSW group) and in FSW supplemented with OMVs (FSW-OMV group), the results indicated that bacterial OMVs affected larval settlement by modulating the expression levels of apoptosis-inducing factor (AIF) in the host. Subsequently, quantitative real-time PCR revealed a decrease in aif expression near the time of settlement (SE) compared to that in the control group. RNA interference (RNAi) was used to target the aif gene, and the rate of larval settlement was significantly reduced, confirming the inhibitory effect of high concentrations of OMVs. Moreover, small RNA (sRNA) sequencing of OMVs revealed the existence of abundant AIF-sRNAs of 30 nt, further suggesting that one pathway for the involvement of sponge-associated bacteria in host development is the transport of OMVs and the direct function of cargo loading.

Identification and Classification of Herbal Medicine Marketing Problems from the Perspective of Manufacturers, Pharmaceutical Distribution Companies, Pharmacies, and Consumers in Iran

Background: Despite the increase in the desire to consume herbal medicines and the growing concern of people about their health, as well as the increase in the number of specialized herbal medicine manufacturing companies and pharmacies, these products still have a small market share in the domestic market. Therefore, this research seeks to identify and categorize the marketing problems of herbal medicines with a systemic approach from the perspectives of actors active in this chain (companies producing herbal medicines, pharmaceutical distribution companies, pharmacies and consumers) and provide practical solutions to improve these problems. Methods: The current research is exploratory in nature and qualitative in type. To better identify the marketing problems of herbal medicines, semi-structured interviews were used, and using purposive and snowball sampling methods, interviews were conducted with knowledgeable people in 14 manufacturing companies, 13 pharmaceutical distribution companies, 22 pharmacies and 40 consumers of herbal medicines in 2022. Quantitative content analysis was also used to analyze the text of the interviews. Results: The identified problems are in three short-term, medium-term and long-term time frames, and from another perspective, these problems are located at the three organizational, industrial and macro level. About half of the marketing problems of herbal medicines are located in the three houses of the matrix, i.e. in the houses of organization-mid-term (16 %), industry-short-term (15 %) and organization-short-term (14 %). Also, based on the normalized data, about half of the marketing problems of herbal medicines are related to the non-availability of these medicines (7.7 %), lack of scientific visits by doctors (6.8 %), lack of appropriate and sufficient advertising (6.2 %), returns due to expiration dates (5 %), lack of confidence in the effectiveness (4.8 %), low offers and discounts (4.4 %), high prices (4.1 %), difficulty in collecting claims (3.6 %), low variety of products (2.9 %) and long production time (2.8 %). Conclusion: The government managers of the country can address macro-level issues by controlling the inflation rate, accelerating the settlement time of insurance and government organizations with distribution companies, reducing the time of collecting claims, and raising public awareness regarding herbal medicines. In the industry sector, there is a need to establish national distribution companies for herbal medicines and enhance the research, supply, production, and distribution processes. It is also important to improve the collaboration between manufacturers and pharmacies, as well as facilitate communication with international scientific societies. At the organizational level, managers can boost productivity by enhancing the quality of products and packaging, conducting scientific visits, and publishing credible scientific articles to convince doctors and consumers about the benefits of herbal medicines

Prediction intervals for concrete face sandy gravel dam settlement using Kalman filter-based kernel extreme learning machine

Accurately predicting settlement of concrete face sandy gravel dams is a crucial yet challenging task. The conventional approach of point forecasting can hardly describe the uncertainties inherent in the complex dam system. Hence, a hybrid prediction interval (PI) method using Kalman filter-based kernel extreme learning machine (KELM) is proposed to quantify the uncertain information associated with dam settlement prediction. The Kalman Filter (KF) is integrated into the original KELM by incorporating real-time actual measurement. The wavelet multiresolution analysis is employed to eliminate irrelevant information from historical settlement time series for more accurate prediction. Additionally, a Bayesian method is used to detect change points in the KF modified-KELM model. The proposed method is demonstrated in the settlement monitoring of the Nazixia dam and is compared with three popular machine learning methods. Results indicate that the PI constructed by the proposed method can exhibit better interval coverage and a comprehensive index.

Settlement Prediction for Concrete Face Rockfill Dams Considering Major Factor Mining Based on the HHO-VMD-LSTM-SVR Model

Some important discoveries have been revealed in some studies, including that the settlement of concrete face rockfill dams (CFRDs) may cause cracks in the concrete face slabs, which may lead to dam collapse. Therefore, deformation behavior prediction of CFRDs is a longstanding and emerging aspect of dam safety monitoring. This paper aims to propose a settlement prediction model for CFRDs combining the variational mode decomposition (VMD) algorithm, long short-term memory (LSTM) network, and support vector regression algorithm (SVR). Firstly, VMD is applied in the decomposition of dam settlement monitoring data to reduce its complexity. Furthermore, feature information on settlement time series is extracted. Secondly, the LSTM and SVR are optimized by the Harris hawks optimization (HHO) algorithm and modified least square (PLS) method to mine the major influencing factors and establish the prediction model with higher precision. Finally, the proposed model and other models are applied to predict the deformation behavior of the Yixing CFRD. Prediction results indicate that the proposed method possesses particular advantages over other models. The proposed VMD-LSTM-SVR model might help to evaluate the settlement trends and safety states of CFRDs.

Antibiotics alter development and gene expression in the model cnidarian Nematostella vectensis.

Antibiotics are commonly used for controlling microbial growth in diseased organisms. However, antibiotic treatments during early developmental stages can have negative impacts on development and physiology that could offset the positive effects of reducing or eliminating pathogens. Similarly, antibiotics can shift the microbial community due to differential effectiveness on resistant and susceptible bacteria. Though antibiotic application does not typically result in mortality of marine invertebrates, little is known about the developmental and transcriptional effects. These sublethal effects could reduce the fitness of the host organism and lead to negative changes after removal of the antibiotics. Here, we quantify the impact of antibiotic treatment on development, gene expression, and the culturable bacterial community of a model cnidarian, Nematostella vectensis. Ampicillin, streptomycin, rifampicin, and neomycin were compared individually at two concentrations, 50 and 200 µg mL-1, and in combination at 50 µg mL-1 each, to assess their impact on N. vectensis. First, we determined the impact antibiotics have on larval development. Next Amplicon 16S rDNA gene sequencing was used to compare the culturable bacteria that persist after antibiotic treatment to determine how these treatments may differentially select against the native microbiome. Lastly, we determined how acute (3-day) and chronic (8-day) antibiotic treatments impact gene expression of adult anemones. Under most exposures, the time of larval settlement extended as the concentration of antibiotics increased and had the longest delay of 3 days in the combination treatment. Culturable bacteria persisted through a majority of exposures where we identified 359 amplicon sequence variants (ASVs). The largest proportion of bacteria belonged to Gammaproteobacteria, and the most common ASVs were identified as Microbacterium and Vibrio. The acute antibiotic exposure resulted in differential expression of genes related to epigenetic mechanisms and neural processes, while constant application resulted in upregulation of chaperones and downregulation of mitochondrial genes when compared to controls. Gene Ontology analyses identified overall depletion of terms related to development and metabolism in both antibiotic treatments. Antibiotics resulted in a significant increase to settlement time of N. vectensis larvae. Culturable bacterial species after antibiotic treatments were taxonomically diverse. Additionally, the transcriptional effects of antibiotics, and after their removal result in significant differences in gene expression that may impact the physiology of the anemone, which may include removal of bacterial signaling on anemone gene expression. Our research suggests that impacts of antibiotics beyond the reduction of bacteria may be important to consider when they are applied to aquatic invertebrates including reef building corals.

A Study on Innovative Design Approaches for Implementing an Intelligent ICT-Based Smart Highway

This research, conducted over a three-year period starting from 2020, was a collaborative project between practitioners in the field of VE design and the Korea Expressway Corporation, aimed at innovating the design VE project to construct an intelligent ICT-based smart highway and enhancing highway driving performance and customer satisfaction.
 The research included R&D support for payment and management systems integrated with IOT technology, the application of the developed prototype at highway sites, and analysis of user performance evaluation. Based on the Innovation Work Roadmap of the Korea Expressway Corporation, the research process involved collaboration between a public participation group and an expert group, considering the technical feasibility of data-based ICT technology through the National Idea VE Contest.
 The final VE design results were implemented at the Seongnam tollgate site with budget support from relevant departments, followed by a satisfaction survey. It is expected that the continuous contributions to achieving an ESG society, such as the increase in the number of customers using the tolling zone equipped with smart upgrades, along with their satisfaction rate, and the reduction in carbon emissions and total settlement time of highway users, will be sustained.

Prediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach

The prediction of surface settlement occupies a crucial role in achieving effective catastrophe prevention and mitigation, as well as facilitating the maintenance of airport runways. Given the challenges associated with the manual collection of settlement data and the suboptimal timeliness of the Back Propagation (BP) technique in neural networks, this study proposes an integrated prediction method that combines the Ensemble Kalman Filter (EnKF) with BP. This study focuses on the processing of Synthetic Aperture Radar (SAR) pictures obtained from the ascending orbit of the Sentinel-1A satellite. The Small Baseline Subset Interferometric synthetic aperture radar (SBAS-InSAR) technology is employed to derive the settlement time series on the runway of Kangding Airport. Moreover, three sites with high coherence within the primary settlement region are employed to assess the dependability of the model after the expansion of the data by cubic spline interpolation. The findings of the study indicate that both the BP-EnKF and BP models exhibit favorable outcomes in predicting airport runway settlement. However, following the alteration of data caused by external environmental influences, the BP-EnKF model has superior adaptability to variations in data. It has been shown that the BP-EnKF model exhibits a prediction accuracy that surpasses the BP model by 9.25%.

Fractal Evolution Characteristics of Isolation Layers in a Submarine Gold Mine: A Case Study

The establishment of an isolation layer in submarine mining has been a persistent challenge. In the context of this research, we conducted a similarity simulation test to preliminarily assess the interaction between the thickness and extent of the isolation layer. Subsequently, we introduce an innovative approach that integrates fractal theory and the Bonded Block Model (BBM) to simulate undersea isolation layer mining. The validation of this method relies on on-site borehole scanning and displacement monitoring, which depict the intricate fractal evolution of fractures and predict the optimal thickness of the isolation layer. Our findings affirm the robustness and validity of this method. Evaluation of the fractal dimensions of fractures reveals that a critical threshold of 1.7 is essential to prevent structural failure of the isolation layer, while a limit of 1.5 is necessary to avoid significant water ingress. Remarkably, the correlation dimension of the settlement time series closely aligns with the fractal dimension of the fractures, underscoring the feasibility of ensuring the safety of isolation layer mining through real-time settlement monitoring.

Machine-Learning-Based Deformation Prediction Method for Deep Foundation-Pit Enclosure Structure

During the construction of deep foundation pits in subways, it is crucial to closely monitor the horizontal displacement of the pit enclosure to ensure stability and safety, and to reduce the risk of structural damage caused by pit deformations. With advancements in machine-learning (ML) techniques and correlation analysis in engineering, data-driven methods that combine ML with engineering monitoring data have become increasingly popular. These methods offer benefits such as high prediction accuracy, efficiency, and cost effectiveness. The main goal of this study was to develop a machine-learning method for predicting the enclosure deformation of deep foundation pits. This was achieved by analyzing the factors influencing deep foundation-pit enclosure deformation and incorporating historical cases and monitoring reports. The performance of each machine-learning prediction model was systematically analyzed and evaluated using K-Fold cross validation. The results revealed that the random forest model outperformed the other models. The result of the test data showed that the random forest model achieved an R2 of 0.9905, an MAE of 0.8572 mm, and an RMSE of 1.9119 mm. Feature importance analysis identified the depth of enclosure structure, water level, surface settlement, axial force, and exposure time as the most critical factors for accurate prediction. The depth of the enclosure structure had an especially significant impact on the prediction of enclosure deformation.

KENYA: ESTABLISHING THE NATURE AND RATE OF RESILIENCE (RECOVERY) AMONG THE DISPLACED POPULATION IN NAKURU COUNTY

Although internal displacement of persons has been witnessed in Kenya over the years, the 2007/08 episode was the most severe. This study was conducted to examine the socio-eco nomic characteristics of the internally displaced population (IDPs) and to assess the nature of the initial resettlement among the displaced population at the Nakuru Pipeline Complex, Nakuru County, Kenya. The study used a survey design and sampled 260 households from the resettle ment register. Questionnaires which included the household displacement deprivation scale and key informant guide were used. Indicators that were rated worst (i.e., severely or rarely available or accessible) at the time of the initial settlement in 2008 included loss of self-esteem (82%), loss of income (82%), loss of employment (78%), lack of shelter (81%) and loss of property (71%). By 2018, there were considerable improvements (recovery) that included housing (72.0%), food access (63.0%), water (57.0%), and clothing (54.0%) compared to the initial crisis periods. Given the occurrence of processes that induce disasters and displacement, social development efforts should be directed to the reduction of vulnerabilities, including socio-ecological vulnerabilities. Such measures will ensure that when disasters and displacements occur, it will be possible for the people, and citizens, to recover, adapt to new environments, and continue with their liveli hoods. Reduction of severity in magnitude and duration will need to be an integral part of the social development planning. Keywords: Resilience, internally displaced pop ulation, displacement, Nakuru Pipeline, deprivation.

Land subsidence analysis along high-speed railway based on EEMD-Prophet method

Environmental changes and ground subsidence along railway lines are serious concerns during high-speed railway operations. It is worth noting that AutoRegressive Integrated Moving Average (ARMA), Long Short-Term Memory (LSTM), and other prediction methods may present limitations when applied to predict InSAR time series results. To address this issue, this study proposes a prediction method that decomposes the nonlinear settlement time series of feature points obtained through InSAR technology using Ensemble Empirical Mode Decomposition (EEMD). Subsequently, multiple Intrinsic Mode Functions (IMFs) are generated, and each IMF is individually predicted using the Prophet forecasting model. Finally, we employ an equal-weight superimposition method to combine the results, resulting in the prediction of the InSAR settlement time series. The predicted values of each component are subsequently weighted equally and combined to derive the final prediction outcome. This paper selects InSAR monitoring data along a high-speed railway in inland China and uses the proposed method and ARMA and Prophet models to carry out comparative experiments. The experimental results show that compared with the ARMA and Prophet models, the method in this paper improves the root mean square error by 58.01% and 32.3%, and increases the mean absolute error by 62.69% and 33.78%, respectively. The predicted settlement values generated by our method exhibit better agreement with the actual InSAR monitoring values.

Growth of Alternative Dispute Resolution Method in The Legal System

Alternative Dispute Mechanism is viewed as the most significant and critical perspective in present day time of dispute settlement. It is an old peculiarity and technique to determine the questions through amicable settlement. It will assist with settling the debate without meddling by unbending court method and conventions. ADR component demonstrate exceptionally helpful, essential and more successful in commercial and civil dispute. The complicity of business and common questions can undoubtedly oversee through the ADR without meddling by details and complex methodology of regulation. The non-intercession by supporters and court will make it more powerful instrument for question settlement. It might consider as elective technique for equity conveyance framework in India. In this exploration paper the specialist will attempt to examination the ADR framework is elective strategy for dispute settlement and way for the Alternative mechanism of existing complex legal framework. The examination will be contended with a goal to investigate the concentrate between the ordinary strategy versus ADR technique for debate settlement and will close by giving a few viable arrangements that ADR is considered as an essential choice in settlement of questions.

Penerapan Soil Preloading, PVD, dan PHD untuk Analisis Penurunan Konsolidasi Tanah

Soft clay has a low bearing capacity, high compressibility and low permeability. This condition causes soft clay soil to have a long settlement time. To overcome this soft soil condition, soil improvement methods are needed. One of the efforts is to use a combination of soil preloading methods, Prefabricated Vertical Drain (PVD), and Prefabricated Horizontal Drain (PHD) methods. Calculating soil settlement with soil improvement is carried out using the Asaoka method, which is a field observation method, and the theoretical method using the Terzaghi method. Based on the calculation results of field observations using the Asaoka method, the average degree of soil settlement is 93.5%. The calculation results of the Asaoka method are recalculated using a back calculation to produce a new parameter value, namely the horizontal consolidation (Ch) value, which is then compared with the Ch value in the previous plan. In the Terzaghi method, the average soil settlement value is 1.205 meters. The results of soil settlement value are used to analyze the height of the embankment based on the load ratio requirement in SNI 8460: 2017, where the load ratio on the ground is ≥ 1.3 times the planned load under service conditions. Based on the monitoring results, a load ratio value of 0.875 was obtained so that the SNI requirements carried out a re-planning of the landfill. Then, proceed with the design of PVD and PHD. The results obtained in planning use triangular PVD patterns with a distance between PVDs of 1 meter.

Analisis Penurunan Gabungan Prefabricated Vertical Drain dan Stone Column Untuk Perbaikan Tanah Lunak

Soft soil is inevitable in the construction, be it road construction or building construction. Soil improvement is needed to overcome the problem of soft soil, soil improvement methods are growing and diverse. This research is focused on studying the interaction behavior of combination two soil improvement methods, namely Prefabricated Vertical Drain (PVD) and Stone Column (SC). This research was conducted using PLAXIS 2D with Mohr-Coulomb (MC) and Soft Soil (SS) material models. The results showed that the combination of PVD and SC methods provides the advantage that PVD can accelerate the consolidation time and SC can reduce the settlement that occurs in the soil. The use of SS model is greater settlement compared to using Mohr-Coulomb material model with a settlement of 1,641 m for Soft Soil and 0.463 m for Mohr-Coulomb. SC depth variation affects the settlement and settlement time, the longer the SC the smaller settlement and the shorter time, while PVD only affects the time. Combining PVD and SC results in better settlement and settlement time compared to PVD or SC alone. Variations in construction methods result in slight differences for MC material models, whereas for SS material models, construction methods 2 are greater in settlement and shorter time.

Moving to Mars: The Feasibility and Desirability of Mars Settlements

The on-going space settlement debate has raised questions whether it is possible to settle other planets, and if it was, is it something humans should do. The problem with this space ethical discussion is that it can easily become too vague. To avoid this problem, we suggest a framework for identifying relevant variables that affect the feasibility constraints and desirability factors of establishing space settlements. The variables we focus on include the settlement stage, scale and time frame. Based on the relevant literature, we take mission cost, survival, habitation, water, in situ resources for food, oxygen and fuel energy and dependence on Earth as feasibility constraints that are relevant for the framework. None of them are hard constraints, but rather soft feasibility constraints that make it difficult to establish a permanent human settlement on Mars in the near- to medium-term future. However, in the past, humanity has achieved goals that first seemed infeasible. To justify the costs and effort, the goal must be highly morally desirable. We discuss five different desirability factors that could help justify the effort but as each framework has unique feasibility constraints, not all of these factors are sufficient or necessary to justify this effort. We argue that some of the desirability factors prominent in space ethical literature are not sufficient or necessary in our framework, and thus, we conclude that the normative grounds for establishing a permanent Mars settlement in the foreseeable future are weak.

Analisis Proses Konsolidasi Dengan PVD Pada Proyek Reklamasi di Samping Tangki CPO Antar Pulau Belawan Berdasarkan Bore Log BH-1

In the planning of civil building, construction problems are often encountered in soft soil types, including low soil carrying capacity and large settlements (settlements) when given a load. Soil improvement is needed to speed up the consolidation settlement time. One method that can be applied to speed up the consolidation settlement time is to use a pre-fabricated vertical drain (PVD) and this preloading method is able to increase the shear strength of soft soils and remove pore water in the soil. This research aims to determine the magnitude of settlement of soft soil consolidation using the 1-dimensional Terzaghi consolidation formula and analysis using the finite element method with PLAXIS 2D modeling, comparing the results of PLAXIS 2D modeling with actual data, the effect of the smear zone effect on the settlement of soil consolidation in the embankment area and to determine the difference in the decrease in preloading methods combined with PVD and preloading without PVD based on point bore log BH-1. From the results of the analysis, it is found that the consolidation settlement by analytical method using the 1-dimensional Terzaghi consolidation formula was 0.858 meters. The amount of settlement that occurs in the consolidation process using PLAXIS 2D modeling taking into account the smear zone effect is 0.786 meters and 0.852 meters without taking into account the smear zone effect. Meanwhile, the actual settlement that occurred in the field based on settlement plate (SP-01) was 0.867 meters and the magnitude of the preloading settlement without PVD was 0.512 meters. It can be concluded that the PVD combination preloading method is proven to accelerate consolidation time, while the improvement with the preloading method alone produces a relatively small decrease.

The directed acyclic graph helped identify confounders in the association between coronary heart disease and pesticide exposure among greenhouse vegetable farmers.

To explore the causal pathways associated with coronary heart disease (CHD) and pesticide exposure using a directed acyclic graph (DAG) analysis and to investigate the potential benefits of DAG by comparing it with logistic regression. This cross-sectional study enrolled 1368 participants from April 2015 to May 2017. Trained research investigators interviewed farmers using a self-administered questionnaire. Logistic regression and DAG models were used to identify the associations between CHD and chronic pesticide exposure. A total of 150 (11.0%) of the 1368 participants are characterized as having CHD. High pesticide exposure (odds ratio = 2.852, 95% confidence intervals: 1.951-4.171) is associated with CHD when compare with low pesticide exposure by both DAG and logistic analyses. After adjusting for the additional potential influence of factors identified by the DAG analysis, there is no significant association, such as the results in logistic regression: ethnicity, education level, settlement time, and mixed pesticide status. Specifically, age, meal frequency, and consumption of fresh fruit, according to the DAG analysis, are independent factors for CHD. High pesticide exposure is a risk factor for CHD as indicated by both DAG and logistic regression analyses. DAG can be a preferable improvement over traditional regression methods to identify sources of bias and causal inference in observational studies, especially for complex research questions.

The role of blockchain technology in advancing sustainable energy with security settlement: enhancing security and efficiency in China’s security market

Blockchain technology has the potential to revolutionize securities settlement systems, offering an efficient, reliable, and cost-effective alternative to traditional methods. Its features, including distributed data authenticity, programmability, and scalability, can enhance security and efficiency in China’s securities market, while promoting a sustainable energy future. However, to fully leverage the benefits of blockchain in securities registration and settlement, it is crucial to address algorithmic loopholes and operational risks associated with smart contracts. Establishing blockchain technical standards and rules is also necessary to ensure smooth system operation. Furthermore, given the uncertainty of the final settlement time point, adherence to decentralization principles and the incorporation of embedded technology for supervision are essential. Legislative measures are required to regulate smart contracts and mitigate systemic risk effectively. This will ensure a stable settlement time expectation and enable fair allocation of legal responsibility among the involved parties. Additionally, other regulatory approaches should be implemented to provide effective supervision and adapt to the rapid development of blockchain. By addressing challenges and risks, blockchain’s full potential can be realized, enabling a sustainable energy future, while enhancing security and efficiency in China’s securities market.

Mysore Palace Establishment Under Wodeyars and Its Financial Administration

The Mysore palace essentially refers to Ambavilas palace of Princely Mysore. Mysore was a modern state and model state under wodeyars . . The rulers of Mysore during the period 1881 to 1947 are Wodeyars of Mysore .The city of Mysore was capital for the Wodeyars . At the time of settlement of 1868, there were 25 departments (establishments) in the palace which was reduced to 12 later. These departments comprised an entire administration on a small scale. These worked to fulfill the roles of maintenance of the Maharaja’s house hold, performance of ritual in the palace, execution of certain traditional Kingly behavior of patronage, endowment and charity. It has departments like Avasarada Hobli, Maramath, Muzarai, Mothi Khana, Estates and Gardens, Games and Tigers Preserves Office, Dasara, etc. which has jointly and independently helped in palace general and financial administration of the palace.