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Entrepreneurship is vital for driving innovation, economic development, and sustainability in the agricultural sector, empowering farmers, and ensuring food security. Successful promotion of agri-entrepreneurship demands a nuanced approach that considers both the personal traits of entrepreneurs and the institutional factors. This study employed linear regression analysis and principal component analysis to examine the determinants of entrepreneurial success and identify factors contributing to effective interventions across three distinct entrepreneurial categories i.e., farm-based, off-farm based, and service/tech entrepreneurs. Data was gathered through structured interviews involving two hundred agri-entrepreneurs in Rajasthan and Telangana states. The regression analysis revealed that diverse psycho-personal and socioeconomic variables like marital status, income levels, and achievement motivation were of significant influence. The principal component analysis provided valuable insights into the institutional factors underpinning effective entrepreneurship promotion interventions. Technical factors like tailored project support, financial enablers including government funding and tax incentives, and robust implementation mechanisms involving stakeholder collaboration were highlighted. Operational elements such as; training institute-industry-market-entrepreneur linkages, administrative commitments, and policy consistency, collectively shaped intervention effectiveness across the entrepreneurial ecosystems. This comprehensive examination of individual and institutional determinants offered a holistic perspective on fostering successful agri-enterprises, emphasizing the need for contextualized approaches that align personal attributes with tailored institutional interventions.

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Given the complexity of spoken interaction, acquiring conversation skills has been difficult for most EFL learners, and as EFL classrooms largely depend on hypothetical scripted material, learners lack explicit exposure to naturally occurring language essential for real-life interaction. This paper reports on a quasi-experimental study aiming at assessing the impact of conversation analysis- (CA) informed language-in-(natural)-talk log assignments on the development of Thai EFL learners’ conversation skills. Eighty-eight second-year undergraduates at a university in southern Thailand took part in the study. As part of a monitored self-study task, the participants completed ten language-in-talk log assignments with self-selective use of audiovisuals available online. The quantitative data was collected using pre-and post-test role-plays. The qualitative data was assessed through completed log assignments, close analysis of the role-plays, and written interview for data triangulation. The findings suggested that the log assignment intervention significantly enhance participants’ conversation abilities, including turn construction, turn delivery, and the sequential organization of turn-taking. The qualitative results also show that via CA-informed requirements of the log assignment, students became more aware of conversation mechanisms and language use in real-life interaction. This paper recommends that language-in-talk log assignments be incorporated into existing EFL conversation lessons.

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Extended finite element method (X-FEM) has been recently emerged as an approach to implicitly create a discontinuity based on discontinuous partition of unity enrichment (PUM) of the standard finite element approximation spaces. Despite numerous progresses in mesh generating updating of finite element mesh during crack propagation remain extremely heavy and difficult. This problem becomes more complicate, when there are many discontinuities in the finite element domain. However, the extended finite element method (X-FEM) in the combination with level set method (LSM) could overcome this cumbersome issue. In this contribution, predefined cracks and internal boundaries are created using level set functions and also the effects of soft/hard inclusions (interfaces) and voids are considered on crack propagation schemes. In fact, the interaction of crack and heterogeneities are considered. The level set functions are utilized to represent the locations and the evolutions of internal interfaces. In addition, the stress intensity factors for mixed mode crack problems are numerically calculated by using the interaction integral method. Different crack growth paths are simulated automatically for different oriented edge and center cracks and the interactions of internal boundaries on crack propagations are shown. All numerical examples are demonstrated the flexibility and capabilities of X-FEM in the applied fracture mechanics.

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Full feedback data is mostly essential in control design. The measurement of the variation of flexible joint robot (FJR) actuators is not easy as the measurement of the changes of FJR links’ angles. The measurement of the states is also affected by noise, and the disturbance in the workspace of the robot is not ignorable. Hence a state observer or a nonlinear estimator is necessary to improve the performance of the dynamic system. The state-dependent Riccati equation (SDRE) is one of the most promising nonlinear optimal control methods for estimating variables of systems. Systematic procedure, simple structure, and incorporating wide range of systems (under observability condition) are some advantages of SDRE method. The majority of nonlinear techniques linearize the model, but the SDRE directly uses the nonlinear state space; it is one of the reasons for its precision and flexibility in design with respect to other methods. The goal of this work is to merge the SDRE controller and estimator simultaneously to reduce the state error of the system in presence of external disturbance and measurement noise. So, first, the controller and the observer formulation has been stated. Then, the procedure has been applied to design and to simulate a 3 DOF robot arm with flexible joints. Next, the process has been tested experimentally using Scout robot and the simulation results have been verified. Finally, the proposed method of this paper has been compared with the optimal sliding mode.

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Nowday, slab track is widely used in the world as railway supresturture because its advantages in comprison with conventioanl ballasted railway superstureure. So, design and analysis process of railway slab track is one the main issues in recent researches.  One of the main factor in the design and analysis of slab track is distrubtion of vertical load on longitudinal direction of the track (load distribution factor). In this paper, a 2D numerical model is developed in FORTRAN to investigate the effect of slab track properties on the load distribution factor. In this model, the slab track is comprised of rail, fastening system, concrete slab, elastic layer, concrete base and subgrade. Rail, concrete slab and concrete base are modeled as two nodeded beam element and fastening system, elastic layer and subgrade are simulated as spring element. According to the elements stiffness matrices, slab track stiffness matrix is developed. A wheel load is applied on the rail (in the middle of the model). Based on the two noded beam element shape functions, load vector of the model is developed. The equlibrium equation of the model is solved and load distribution factor is derived. To investigate the validity of the results obtained from the model, a comparsion is made between results obtained from the model and those of ABAQUS as a commercial finite element software. Rail displacement, concrete slab displacement, concrete base displacement and load disribution factor obtained from the ABAQUS are compared with those of the model developed in this paper and a very good agreement was illustrated between results. A parametric study was performed to investigate the effects of rail flexural rigidity, fastening system stiffness, concrete slab flexural rigidity, elastic layer stiffness, concrete base flexural rigidity and subgrade stiffness on the load distribtion factor. The results obtaine from the parametric study indicate that as the slab track element stiffness or flexural rigidity is decreased, the load distribution factor is decreased and vertical load is distributed widely in the longitudinal direction of the track. Rail pad stiffness has the maximum effect on the load distribution factor reletive to the other parameters. As the rail pad stiffness is changed from lowest to highest magnitude, the load distribution factor is varied from 0.3 to 0.7. The results obtained in this research indicate that propeties of lower slab track elements have lower effects on the load distribution factor compared to the upper slab track elements. So when the flexural rigidity of the concrete slab is changed from low to high, load distribution factor is changed from 0.52 to 0.54. Moreover, when the elastic layer stiffness, concrete base flexural rigidity and subgrade stiffness are changed from low to high, the load distibution factor are almost unchanged and is roughly 0.54. This shows that elastic layer stiffness, concrete base flexural rigidity and subgrade stiffness do not have any significant effects on the load distribution factor. So when a model is developed to calculate the load distribution factor and dcrease of analysis computation cost, elastic layer stiffness, concrete base flexural rigidity and subgrade stiffness could be ignored in the model. 
 

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