Objective: To evaluate the imaging features of spondyloarthritis on magnetic resonance imaging (MRI) of the sacroiliac (SI) joints in terms of topography (in thirds) and affected margin, since this aspect is rarely addressed in the literature. Methods: Cross-sectional study with MRI (1.5 T) evaluation of the SI in 16 patients with diagnosis of axial spondyloarthritis regarding the presence of acute (subchondral bone edema, enthesitis, synovitis and capsulitis) and chronic changes (erosions, subchondral bone sclerosis, bone bridging and fatty replacement), performed by two radiologists, blinded to clinical data. MRI findings were correlated with clinical data including age, disease duration, medications, HLA-B27, BASDAI, ASDAS-VHS and ASDAS-PCR, BASMI, BASFI, and mSASSS. Results: Bone edema pattern and erosions showed predominance in the upper third of SI (p = 0.050, p = 0.0014, respectively). There was a correlation between the time of disease and structural changes by affected third (p = 0.028-0.037), as well as the presence of bone bridges with BASMI (p = 0.028) and mSASSS (p = 0.014). Patients with osteitis of the lower third had higher ASDAS values (ESRV: p = 0.011 and CRP: p = 0.017). Conclusion: Chronic inflammatory changes and the pattern of bone edema predominated in the upper third of the SI, but there was also concomitant involvement of the middle or lower thirds of the joint. The localization of involvement in the upper third of the SI was insufficient to differentiate between degeneration and inflammation.

The focus of this research is the task of assistance from the government in improving agriculture in the region and analyzing the obstacles that occur. However, there has been a decrease in the number of assistance tasks given by the central government to the local government of Rokan Hulu, Riau Province, Indonesia in 2022. This study aims to evaluate and find out the obstacles to the implementation of assistance tasks in Rokan Hulu Regency in 2022. This study uses a qualitative method with an exploratory type and is analyzed using Nvivo 12 Plus software. The results of this study show that the Rokan Hulu regional government only gets one implementation of assistance tasks, namely from the Ministry of Agriculture through the Director General of Infrastructure and the Director General of Food Crops whose performance achievements have been maximized. The findings in this study are that in its implementation there are obstacles, one of which is the relatively short period of implementation of assistance tasks, making it difficult to implement assistance tasks by regional apparatus organizations as recipients of assistance tasks. The conclusion in this study is that the implementation of assistance tasks there is one assistance task received from the Ministry of Finance whose implementation in the region is carried out by the Food Crops and Horticulture Service. This research contributes to the government of Rokan Hulu, Indonesia, namely as a basis for policymaking, especially in the use of the budget for assistance tasks.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.

Land suitability analysis using geographic information systems (GIS) is one of the most widely used method today. In this type of studies, GIS and geo-spatial statistical tools are used to evaluate land units and present the results in suitability maps. The present work aims to characterize the suitability of soils in the province of Catamarca for pecan nut production according to the variables: rockiness, salinity, risk of water-logging, depth, texture and drainage described in the Soil Map of Argentina at a scale of 1:500,000 published by the National Institute of Agricultural Technology. A classification of the suitability of the soil cartographic units was made according to crop requirements, applying the methodology proposed by FAO. The standardization of variables made by omega score and the calculation of the spatial classification score were carried out as a result of the synthesis of the spatial distribution of soil suitability. The applied methodology allowed obtaining the soil suitability map resulting in a total of 60,662 km² suitable for pecan nut production, which accounts for 59.8% of the total area of the province.

Through the combination of the geographic information systems (GIS) and the integrated information model, the stability of regional bank slope was comprehensively evaluated. First, a regional bank slope stability evaluation index system was established through studying seven selected factors (slope grade, slope direction, mountain shadow, elevation, stratigraphic lithology, geological structure and river action) that have an impact on the stability of the slope. Then, each factor was rasterized by GIS. According to the integrated information model, the evaluation index distribution map based on rasterized factors was obtained to evaluate the stability of the regional bank slope. Through the analysis of an actual project, it was concluded that the geological structure and stratigraphic lithology have a significant impact on the evaluation results. Most of the research areas were in the relatively low stable areas. The low and the relatively low stable areas accounted for 15.2% and 51.5% of the total study area respectively. The accuracy of slope evaluation results in the study area reached 95.41%.

Strategically managing production systems is crucial for creating value and enhancing the competitive capabilities of companies. However, research on organizational culture within these systems is scarce, particularly in the Colombian context. This research aims to evaluate cultural profiles and their impact on the performance of production systems in Colombian firms. The regional focus is vital as cultural and contextual factors can vary significantly between regions, influencing organizational behavior and performance outcomes. To achieve this, we make a study in a sample of Colombian companies, with participation from working students of the Universidad Nacional Abierta y a Distancia (UNAD). We used a data analytics approach to collected data. The results will be relevant to both the scientific community and business practitioners. This research seeks to determine whether the perception of the work environment within a company influences the perceived performance of the company. The findings will provide a deeper understanding of the relationship between organizational culture and production system performance, offering a foundation for business decision-making and enhancing competitiveness in Latin American context.