Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.

Scientists have harnessed the diverse capabilities of nanofluids to solve a variety of engineering and scientific problems due to high-temperature predictions. The contribution of nanoparticles is often discussed in thermal devices, chemical reactions, automobile engines, fusion processes, energy results, and many industrial systems based on unique heat transfer results. Examining bioconvection in non-Newtonian nanofluids reveals diverse applications in advanced fields such as biotechnology, biomechanics, microbiology, computational biology, and medicine. This study investigates the enhancement of heat transfer with the impact of magnetic forces on a linearly stretched surface, examining the two-dimensional Darcy-Forchheimer flow of nanofluids based on blood. The research explores the influence of velocity, temperature, concentration, and microorganism profile on fluid flow assumptions. This investigation utilizes blood as the primary fluid for nanofluids, introducing nanoparticles like zinc oxide  and titanium dioxide (. The study aims to explore their interactions and potential applications in the field of biomedicine. In order to streamline the complex scheme of partial differential equations (PDEs), boundary layer assumptions are employed. Through appropriate transformations, the governing partial differential equations (PDEs) and their associated boundary conditions are transformed into a dimensionless representation. By employing a local non-similarity technique with a second-degree truncation and utilizing MATLAB’s built-in finite difference code (bvp4c), the modified model’s outcomes are obtained. Once the calculated results and published results are satisfactorily aligned, graphical representations are used to illustrate and analyze how changing variables affect the fluid flow characteristics problems under consideration. In order to visualize the numerical variations of the drag coefficient and the Nusselt number, tables have been specially designed. Velocity profile of -blood and -blood decreases for increasing values of  and , while temperature profile increases for increasing values of  and . Concentration profile decreases for increasing values of , and microorganism profile increases for increasing values of . For rising values of  and  the drag coefficient increases and the Nusselt number decreases for rising values of  and  The model introduces a novel approach by conducting a non-similar analysis of the Darchy-Forchheimer bioconvection flow of a two-dimensional blood-based nanofluid in the presence of a magnetic field.

The recent development of characteristic towns has encountered a multitude of challenges and chaos. Nevertheless, there have been many instances of information asymmetry due to the absence of an effective management model and an intuitive digital management system. Consequently, this has caused the erosion of public interests and inadequate supervision by public agencies. As society is progressing at a rapid pace, there is a growing apprehension regarding poor management synergy, outdated management practices, and limited use of technology in traditional construction projects. In today's technologically sophisticated society characterized by the “Internet+” and intelligent management, there is an urgent requirement to identify a more efficient collaborative management model, thereby reducing errors caused by information asymmetry. This paper focuses on the integration of building information modeling (BIM) and integrated project delivery (IPD) for collaborative management within characteristic towns in the PPP mode. By analyzing the available literature on the application status, this study investigates the implementation methods and framework construction of collaborative management while exploring the advantages and disadvantages. On this basis, this study highlights the problems that arise and provides recommendations for improvement. Considering this, the application of the BIM-based IPD model to characteristic towns in PPP mode will enhance the effectiveness of collaborative management among all parties involved, thereby fostering an environment that facilitates decision-making and operational management in the promotion of characteristic industries.

In today’s manufacturing sector, high-quality materials that satisfy customers’ needs at a reduced cost are drawing attention in the global market. Also, as new applications are emerging, high-performance biocomposite products that complement them are required. The production of such high-performance materials requires suitable optimization techniques in the formulation/process design, not simply mixing natural fibre/filler, additives, and plastics, and characterization of the resulting biocomposites. However, a comprehensive review of the optimization strategies in biocomposite production intended for infrastructural applications is lacking. This study, therefore, presents a detailed discussion of the various optimization approaches, their strengths, and weaknesses in the formulation/process parameters of biocomposite manufacturing. The report explores the recent progress in optimization techniques in biocomposite material production to provide baseline information to researchers and industrialists in this field. Therefore, this review consolidates prior studies to explore new areas.