This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

The effects of different storage temperatures (2, 4 and 8 ℃) and their corresponding optimal heat treatment conditions on the quality, physiological and biochemical indexes of Cucumber Fruits during storage were studied by using the quadratic regression orthogonal rotation combination design. The effects of different storage temperatures (2, 4 and 8 ℃) and their corresponding optimal heat treatment conditions on the chilling injury, hardness, weightlessness rate, polyphenol oxidase (PPO), catalase (CAT), peroxidase (POD), H₂O₂, super oxygen anion free radical (O^2-), ASA and GSH were determined. The results showed that heat treatment could inhibit chilling injury, while heat treatment combined with 4 ℃ low temperature storage could effectively inhibit the decline of fruit hardness and weight loss rate, delay the increase of peroxidase (POD) and polyphenol oxidase (PPO) activities, inhibit the increase of H₂O₂ and superoxide anion free radical O^2- and significantly inhibit the browning of cucumber, delay the decline of ascorbic acid and maintain the content of GSH, it was beneficial to adjust the balance of active oxygen system. The results showed that under the storage condition of 4 ℃, the hot water treatment condition of cucumber was 39.4 ℃ and 24.3 min, which could delay the senescence of cucumber fruit and better maintain the quality of cucumber fruit.

This paper examines the transformative potential of e-government in public administration, focusing on its capacity to enhance service delivery, transparency, accessibility, cost efficiency, and civic engagement. The study identifies key challenges, including inadequate technological infrastructure, cybersecurity vulnerabilities, resistance to change within public institutions, and a lack of public awareness about e-government services. These barriers hinder the seamless operation and adoption of digital government initiatives. Conversely, the study highlights significant opportunities such as streamlined service delivery, enhanced transparency through real-time access to government data, increased accessibility for marginalized and remote communities, substantial cost savings, and greater civic engagement via digital platforms. Addressing these challenges through targeted strategies—enhancing technological infrastructure, bolstering cybersecurity, managing organizational change, and raising public awareness—can help policymakers and public administrators implement more effective and inclusive e-government initiatives. Additionally, the integration of these digital solutions can drive sustainable development and digital inclusion, fostering social equity and economic growth. By leveraging these opportunities, governments can achieve more efficient, transparent, and accountable governance. Ultimately, the successful implementation of e-government can transform the relationship between citizens and the state, building trust and fostering a more participatory democratic process.

The present work shows an application of the Chan-Vese algorithm for the semi-automatic segmentation of anatomical structures of interest (lungs and lung tumor) in 4DCT images of the thorax, as well as their three-dimensional reconstruction. The segmentation and reconstruction were performed on 10 CT images, which make up an inspiration-expiration cycle. The maximum displacement was calculated for the case of the lung tumor using the reconstructions of the onset of inspiration, the onset of expiration, and the voxel information. The proposed method achieves appropriate segmentation of the studied structures regardless of their size and shape. The three-dimensional reconstruction allows us to visualize the dynamics of the structures of interest throughout the respiratory cycle. In the future, it is expected to have more evidence of the good performance of the proposed method and to have the feedback of the clinical expert, since the knowledge of the characteristics of anatomical structures, such as their dimension and spatial position, helps in the planning of Radiotherapy (RT) treatments, optimizing the radiation dose to cancer cells and minimizing it in healthy organs. Therefore, the information found in this work may be of interest for the planning of RT treatments.

The optimized methodology and results of the new characterization in terms of dose and image quality of the X-ray system used in the main pediatric hemodynamics service in Chile are presented. In addition, scattered dose rate values at the operator’s eye level are reported for all acquisition modes available in different thicknesses of absorbent media and angiography. The characterization was performed according to the European DIMOND and SENTINEL protocols adapted to pediatric procedures. The air kerma at the entrance surface (ESAK) was measured and the image quality parameters signal-to-noise ratio (SNR) and a figure of merit (FOM) were calculated. The scattered dose rate was measured in personal dose equivalent units. The ESAK for fluoroscopic modes ranged from 0.2 to 35.6 μGy/image when passing from 4 to 20 cm of polymethyl methacrylate (PMMA). For the cine mode, these values ranged from 2.8 to 160.1 μGy/image. The values of the image quality parameters showed a correct system configuration, although abnormal values were observed in the medium fluoroscopic mode. As for the scattered dose rate at the level of the cardiologist’s eyes, the highest value is PMMA with a thickness of 20 cm, where the cine mode reached 9.41 mSv·h-1. The differences found from previous evaluations can be explained by the deterioration of the system and the change of one of the X-ray tubes.