The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

An alternative for sustainable management in the cultivation of Capsicum annuum L. has focused on the use of plant growth promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AMF). This research selected PGPRPGPR and AMF based on their effect on Bell Pepper and Jalapeño bell pepper plants. Five bacterial strains isolated from different localities in the state of Mexico (P61 [Pseudomonas tolaasii], A46 [P. tolaasii], R44 [Bacillus pumilus], BSP1.1 [Paenibacillus sp.] and OLs-Sf5 [Pseudomonas sp.]) and 3 AMF treatments (H1 [consortium isolated from Chile rhizosphere in the state of Puebla], H2 [Rhizophagus intraradices] and H3 [consortium isolated from lemon rhizosphere from the state of Tabasco]). In addition, a fertilized treatment (Steiner solution 25%) and an absolute control were included. Jalapeño bell pepper “Caloro” and Bell Pepper “California Wonder” seedlings were inoculated with AMF at sowing and with CPB 15 days after emergence, and grown under controlled environment chamber conditions. In Jalapeño bell pepper, the best bacterial strain was P61 and the best AMF treatment was H1; in Bell Pepper the best strain was R44 and the best AMF were H3 and H1. These microorganisms increased the growth of jalapeño bell pepper and Bell Pepper seedlings compared to the unfertilized control. Likewise, P61 and R44 positively benefited the photosynthetic capacity of PSII.

The scarcity of the insulators that are required for refrigeration has made it necessary to use locally available materials that can achieve the desired refrigeration. This work presents the performance evaluation of a refrigerator utilizing a locally available material, which is wood particles that have been converted to particle board, as one of its insulators. A vapor compression refrigeration system was designed and fabricated to chill and preserve agricultural products, which are eggs, yogurt, and tomatoes. The various temperatures at which the agricultural products became chilled were compared with their theoretical preservation temperatures obtainable in literature, thereby evaluating the performance of the refrigerator. The temperature of 11 ℃, which was recorded for the egg in the present experiment, is lower than the theoretical preservation temperatures of 18 ℃ to 21 ℃ for an egg. The temperature of 7 ℃, which was recorded for the yogurt, is approximately equal to its theoretical preservation temperature of 5 ℃. The temperature of 8 ℃, which was recorded for the tomato, is lower than the theoretical preservation temperatures of 7 ℃ to 10 ℃ of tomato. This work has revealed that wood particles have the potential to achieve refrigeration, as well as chill and preserve agricultural products.

Modelling and simulation have now become standard methods that serve to cut the economic costs of R&D for novel advanced systems. This paper introduces the study of modelling and simulation of the infrared thermography process to detect defects in the hydroelectric penstock. A 3-D penstock model was built in ANSYS version 19.2.0. Flat bottom holes of different sizes and depths were created on the inner surface of the model as an optimal scenario to represent the subsurface defect in the penstock. The FEM was applied to mimic the heat transfer in the proposed model. The model’s outer surface was excited at multiple excitation frequencies by a sinusoidal heat flux, and the thermal response of the model was presented in the form of thermal images to show the temperature contrast due to the presence of defects. The harmonic approximation method was applied to calculate the phase angle, and its relationship with respect to defect depth and defect size was also studied. The results confirmed that the FEM model has led to a better understanding of lock-in infrared thermography and can be used to detect subsurface defects in the hydroelectric penstock.

This paper is devoted to the determination of the dispersive component of the surface energy of two boron materials such as h-BN and BPO₄ surfaces by using the inverse gas chromatography (IGC) at infinite dilution. The specific interactions and Lewis’s acid-base parameters of these materials were calculated on the light of the new thermal model concerning the dependency of the surface area of organic molecules on the temperature, and by using also the classical methods of the inverse gas chromatography as well as the different molecular models such as Van der Waals, Redlich-Kwong, Kiselev, geometric, Gray, spherical, cylindrical and Hamieh models. It was proved that h-BN surface exhibits higher dispersive surface energy than BPO₄ material.

The specific properties of interaction of the two boron materials were determined. The results obtained by using the new thermal model taking into account the effect of the temperature on the surface area of molecules, proved that the classical IGC methods, gave inaccurate values of the specific parameters and Lewis’s acid base constants of the solid surfaces. The use of the thermal model allowed to conclude that h-BN surface has a Lewis basicity twice stronger than its acidity, whereas, BPO₄ surface presents an amphoteric character.

This study examines the impact of state highway construction contracts on state spending efficiency controlling for production structure, service demands, and situational factors. The theoretical argument is that because highway construction projects are relatively large in scale, complex, and can be monitored through objective performance measurement, state highway construction programs may save government production costs through contracts. Contracting helps highway producers achieve efficiency by optimizing production size based on workload and task complexity. The unit of analysis is 48 state governments’ highway construction contracts from 1998 to 2008. Through a two-stage analysis method including a Total Function Productivity (TFP) index and system dynamic panel data analysis, the results suggest that highway construction contracts enhance state highway spending efficiency, especially for large-scale construction projects.