Shape Variables Research Articles

Individual Differences in the Structure of the Pterygopalatine Fossa of the Adult Skull

The use of endoscopic microsurgical techniques in a number of surgical interventions on deep anatomical structures of the face requires detailed knowledge on the shape and individual variability of the size of the pterygopalatine fossa, containing vascular and nerve structures that provide blood supply and innervation of the upper face, including the pterygopalatine ganglion. The aim was to study individual differences in the shape and size of the pterygopalatine fossa of the adult human skull. Material and methods. The study included 62 archival series of anonymous CT scans (37 men and 25 women), performed with slice thickness of 0.5 mm. On axial and frontal scans, the X and Y coordinates were determined relative to the upper left corner of the scan of the opening of the greater palatine canal, which later serves as the zero point. On subsequent sections, a point with the coordinates of the opening of the greater palatine canal and the distance from this point to another point of interest along the X and Y axes were determined. The difference between the slice numbers multiplied by the thickness of the slice is the distance between two points along the Z axis. Based on the obtained coordinates, a 3- D image of the pterygopalatine fossa was constructed in the isometry system. On axial, frontal and sagittal scans, the width of the medial, anterior and posterior walls of the pterygopalatine fossa, its depth, height and other dimensions characterizing the relative location of the openings passing nerves were measured. The right and left sides of the scans, which had no pathology in this area, were examined. Results. It was stated that in the cavity of the pterygopalatine fossa, one should distinguish between the most bulk main (central) region, adjacent on the lateral side to the sphenopalatine foramen, and narrower regions which are directed downwards (vestibule of the greater palatine canal); backward (vestibule of the pterygoid canal); and laterally (vestibule of the pterygomaxillary fissure). New information has also been obtained characterizing the variability of the size of the pterygopalatine fossa. Conclusion. This study has been shown that the pterygopalatine fossa has a more complex shape than a narrow slit or pyramid, and the presence of the vestibule of the pterygoid canal in its cavity suggests a different position of the pterygoid ganglion in the pterygopalatine fossa and its external structure.

Assessing the influence of urbanization on the historic city of Paithan, India: a case study focusing on the urban core

ABSTRACT Historic cities around the world have been experiencing continuous threats to their cultural heritage due to the multifaceted pressures of urbanization, with historic cities being increasingly threatened by factors beyond population migration, such as changes in land use, degradation of historic character, urban decay, lack of socio-economic development and challenges to sustainable urbanization, Historic City reestablishment becomes vital, as this would promote sustainable growth. Analysing the impacts and extent of urbanization in historic cities is essential to determine how one might help mitigate it. This study investigates the impact of urbanization on the cultural heritage of the historic city of Paithan, Aiming to answer two key questions: how does urbanization alter the physical and sociocultural fabric of Paithan’s urban historic core, and what factors drive these changes, with the primary objective focussing on assessing the extent of urbanization-led changes and identifying key socio-economic and physical variables influencing this transformation. Four ML models – K-Nearest Neighbour (kNN), Support Vector Machines (SVM), Logistic Regression, and the Random Forest Method were applied to analyse urbanization data. A set of 11 predictor variables was identified, and the findings reveal the rising land values and changing building use as primary drivers of transformation, leading to a decline in traditional architectural elements. The RFM model emerged as the most accurate model, with an accuracy of 89.3%, providing the most accurate insights into the non-linear relationships between the variables. The study concludes with a call for inclusive growth, balancing sustainable development and modern needs. The ML models chosen for this study use open-source data as well as field surveys. Highlights Research investigates urbanization's impact on cultural heritage in a historic city. Novel study compares machine learning models to assess historic core transformations. Identifies critical factors shaping changes in historic urban fabric and their impact. Analyzes socio-economic and physical variables shaping urbanization patterns. Calls for policies balancing sustainable urban growth and heritage conservation.

Is the skull of the black-headed gull dimorphic? Analysis of shape variation

The black-headed gull (Chroicocephalus ridibundus) is a small bird belonging to the Laridae family. Their distribution and breeding broad area primarily cover the northern part of the Eurasian continent. Gulls are considered monomorphic birds, and distinguishing the sexes based on external morphological features is extremely difficult. In this study, a 3D shape analysis of the skull of black-headed gulls from central-northern Poland was performed to reveal the variation in shape between individuals and whether male skulls differ from females. For these purposes, 82 skulls were used (32 females and 50 males). 3D surface models of the skull were extracted using computed tomography. Twenty-one landmarks were designed on each skull. The principal components method was used to assess the variability of skull shapes. The first two principal components accounted for 48.28% of the cumulative shape variation. The most significant shape variation relative to PC1 was observed in the braincase. Positive PC2 values reflected the neurocranium expanding more rapidly dorso-ventrally with a wider orbit, and the nasofrontal hinge moved dorsally. According to the Procrustes ANOVA, the centroid size was statistically different between the sexes (p < 0.0001). Male skulls were longer than females. Neurocranium was wider in male gulls. The nasofrontal hinge was more caudal in females. The results of this study are consistent with the observations of other authors applying linear morphometry.

Does greater richness of life bring greater happiness in older adults?

Aims: The happiness during old age years is closely linked to psychosocial factors such as richness of experience. Richness of experience refers to the level of meaning and fulfillment in individuals' lives through various activities and experiences. This research focused on exploring how the richness of experience is related to the happiness in older adults. In addition, the role of various demographic and psychosocial variables in shaping this relationship were examined. Methods: The study sample consisted of 179 older adults. 64.2% of the participants were female and 35.8% were male. The participants were administered the psychologically rich life questionnaire, and the psychological well-being in the elderly scale as well as a sociodemographic form. Simple Linear Regression was used to analyze the predictive power of richness of experiences, and pearson correlation analysis was conducted to assess the strength of the relationships between richness of experiences and psychological well-being. Independent Groups t-test and ANOVA were applied to explore if there is a difference on the score based on the sociodemographic differences. Results: The results of this study indicated a significant positive correlation between a psychologically rich life and psychological well-being in older adults. According to regression analysis, psychologically rich life was found to be a strong predictor of psychological well-being and explained 57% of the variance. Education level and income level were found to significantly affect psychologically rich life and psychological well-being levels such that university graduates and high-income group received the highest scores. Participants without a chronic disease were found to have significantly higher scores on psychological well-being and psychological rich life. No significant differences were found in terms of other sociodemographic variables such as gender, marital status and having children. Conclusion: These findings suggest that richness of experiences can be an important factor that improves the quality of life of older adults and the value of diversity of experiences for psychological well-being.

How Do Vegetation Biomass, Area, and Shape Attributes Influence the Cooling Effect of Urban Green Spaces?

Despite the increasing volume of research exploring the impact of various characteristics of urban green spaces (UGS) on land surface temperature (LST), findings remain inconsistent, particularly in arid climatic zones. In this research, we examined UGS change and their temperature and analyzed the relationship between pertinent variables of vegetation biomass, area, and shape of green patches and LST in Karaj city, an Iranian semi-arid urban area in 2000 and 2020. Linear regressions were used to model the relationship between green patches’ variables and LST. The results showed that vegetation biomass of green patches was more effective in reducing temperature in comparison with area and shape complexity. Moreover, larger patches with more vegetation biomass and higher shape complexity showed lower temperatures. These results can guide urban landscape optimization by providing a clear understanding of which factors contribute most significantly to temperature mitigation in arid and semi-arid urban areas. For instance, areas identified as green but thermally not significantly cold need to be prioritized for improvements such as planting denser vegetation or introducing more heat resilient species.

The structure-dynamics feedback mechanism governs the glassy dynamics in epithelial monolayers.

The glass-like slow dynamics in confluent epithelial monolayers is crucial for wound healing, embryogenesis, cancer progression, etc. Experiments have indicated several unusual properties in these systems. Unlike ordinary glasses, the glassiness in cellular systems strongly correlates with their static properties and is sub-Arrhenius. These results imply that the slow dynamics in epithelial monolayers is either not glassy or the underlying mechanism is different from ordinary glasses. Combining the analytical mode-coupling theory (MCT), vertex model simulations, and cellular experiments, we show that the slow dynamics is glassy, though the mechanism differs from ordinary glasses. The structure-dynamics feedback mechanism of MCT, and not the barrier-crossing mechanism, dominates the glassy dynamics, where the relaxation time diverges as a power law with a universal exponent 3/2 and naturally explains the sub-Arrhenius relaxation. Our results suggest the possibility of describing various complex biological processes like cell division and apoptosis via the static properties of the systems, such as average cell shape or shape variability.

Interspecific otolith shape and genetic variability as tools for identifying tropical sympatric and congeneric mullet species

Interspecific otolith shape and genetic variability as tools for identifying tropical sympatric and congeneric mullet species

NeuroSight: A Deep‐Learning Integrated Efficient Approach to Brain Tumor Detection

ABSTRACTBrain tumors pose a significant health risk and require immediate attention. Despite progress, accurately classifying these tumors remains challenging due to their location, shape, and size variability. This has led to exploring deep learning and machine learning in biomedical imaging, particularly in processing and analyzing Magnetic Resonance Imaging (MRI) data. This study compared a newly developed Convolutional Neural Network model to pre‐trained models using transfer learning, focusing on a comprehensive comparison involving VGG‐16, ResNet‐50, AlexNet, and Inception‐v3. VGG‐16 model outperformed all other models with 95.52% test accuracy, 99.87% training accuracy, and 0.2348 validation loss. ResNet‐50 model got 93.31% test accuracy, 98.78% training accuracy, and 0.6327 validation loss. The CNN model has a 0.2960 validation loss, 92.59% test accuracy, and 98.11% training accuracy. The worst model seemed to be Inception‐v3, with 89.40% test accuracy, 97.89% training accuracy, and 0.4418 validation loss. This approach facilitates deep‐learning researchers in identifying and categorizing brain cancers by comparing recent papers and assessing deep‐learning methodologies.

Prediction of change in suitable habitats of Senna obtusifolia and Senna tora under climate change

Senna obtusifolia (L.) Irwin & Barneby and Senna tora (L.) Roxb represent important medicinal resources in traditional Chinese medicine for more than two millennia. Sustainable resource utilization and preservation strategies for Senna species necessitate a thorough understanding of the climatic factors governing their distribution patterns. Therefore, this study aimed to identify the key climate variables shaping the current and potential future global distribution of both Senna species. To achieve this, the MaxEnt ecological niche model was employed, integrating species occurrence data with relevant environmental variables. The results indicated that Bio13 and Bio14 were the most critical variables affecting distribution of S. tora, while Bio6 and Bio14 were crucial for S. obtusifolia. The moderate and high suitability habitats of S. obtusifolia and S. tora consist of ca. 189.69 × 104 km2 and 129.07 × 104 km2, respectively, under current situation. Moreover, the global distribution of both species under various climate scenarios revealed that the suitable habitats of both Senna species will reach the maximum during the 2081–2100 period under the SSP585 scenario. Projections across all four climate scenarios indicate a general northward migration in the core distribution of both Senna species. Intriguingly, the observed high degree of ecological niche overlap between the two species aligns with their close phylogenetic relationship. These findings provide valuable insights into the potential future distribution and ecological niche of Senna species, informing sustainable utilization and preservation strategies for Senna resources.

Macroecological patterns of rodent population dynamics shaped by bioclimatic gradients

Long‐term studies of cyclic rodent populations have contributed fundamentally to the development of population ecology. Pioneering rodent studies have shown macroecological patterns of population dynamics in relation to latitude and have inspired similar studies in several other taxa. Nevertheless, such studies have not been able to disentangle the role of different environmental variables in shaping the macroecological patterns. We collected rodent time‐series from 26 locations spanning 10 latitudinal degrees in the tundra biome of Fennoscandia and assessed how population dynamics characteristics of the most prevalent species varied with latitude and environmental variables. While we found no relationship between latitude and population cycle peak interval, other characteristics of population dynamics showed latitudinal patterns. The environmental predictor variables provided insight into causes of these patterns, as 1) increased proportion of optimal habitat in the landscape led to higher density amplitudes in all species and 2) mid‐winter climate variability lowered the amplitude in Norwegian lemmings and grey‐sided voles. These results indicate that biome‐scale climate and landscape change can be expected to have profound impacts on rodent population cycles and that the macro‐ecology of such functionally important tundra ecosystem characteristics is likely to be subjected to transient dynamics.

Innovative Gravity-Fed Filtration System to Improve Coastal Community Water Quality

Efforts to meet clean water needs, especially for drinking water, depend on the condition of groundwater that is healthy and sufficiently available. Filtration is the process of separating particles from a liquid by passing the liquid through a permeable material. This study examines the Gravity-Fed Filtering System with innovative Imhoff technology, combined with a Primary Treatment stage, to produce clearer and higher-quality water. The objective of this research is to assess the effectiveness of this system in reducing contamination levels in groundwater, including iron (Fe), manganese (Mn), total hardness (Ca and Mg), and organic compounds. The study employed an experimental method with a quantitative approach and used a One Group Pretest-Posttest design. The research was conducted in two locations: Barombong Village in Makassar and Pauwo Village in Gorontalo. Fifteen samples were randomly selected for analysis. The study began with preliminary observations and initial testing in March 2022, followed by the main research and prototype evaluation in 2023-2024. The results show that the system effectively reduced Fe, Mn, organic compounds, and total hardness levels. In Makassar, the highest reduction in Fe is 87.3% in sample 8, while in Gorontalo, the highest reduction is 93.3% in sample 8. The highest reduction in manganese (Mn) in Makassar is 63.3% in sample 1, and in Gorontalo, it is 62.1% in sample 1. The highest reduction in organic compounds in Makassar is 81.6% in sample 3, while the lowest reduction in total hardness in Makassar is 77.1% in samples 4, 5, 6, and 10. In Gorontalo, the highest reduction in total hardness is 90.3% in samples 1, 2, and 3. Recommendations for the community, The use of gravity-fed filtering system technology as one of the media used to reduce iron and manganese concentrations is considered quite good, but for similar research to be carried out, modifications should be made to the media specifically starting with the size, shape and other variables that support it so that it is more effective in reducing pollutant concentrations.

DANNET: deep attention neural network for efficient ear identification in biometrics

Biometric identification, particularly ear biometrics, has gained prominence amidst the global prevalence of mask-wearing, exacerbated by the COVID-19 outbreak. This shift has highlighted the need for reliable biometric systems that can function effectively even when facial features are partially obscured. Despite numerous proposed convolutional neural network (CNN) based deep learning techniques for ear detection, achieving the expected efficiency and accuracy remains a challenge. In this manuscript, we propose a sophisticated method for ear biometric identification, named the encoder-decoder deep learning ensemble technique incorporating attention blocks. This innovative approach leverages the strengths of encoder-decoder architectures and attention mechanisms to enhance the precision and reliability of ear detection and segmentation. Specifically, our method employs an ensemble of two YSegNets, which significantly improves the performance over a single YSegNet. The use of an ensemble method is crucial in ear biometrics due to the variability and complexity of ear shapes and the potential for partial occlusions. By combining the outputs of two YSegNets, our approach can capture a wider range of features and reduce the risk of false positives and negatives, leading to more robust and accurate segmentation results. Experimental validation of the proposed method was conducted using a combination of data from the EarVN1.0, AMI, and Human Face datasets. The results demonstrate the effectiveness of our approach, achieving a segmentation framework accuracy of 98.93%. This high level of accuracy underscores the potential of our method for practical applications in biometric identification. The proposed innovative method demonstrates significant potential for individual recognition, particularly in scenarios involving large gatherings. When complemented by an effective surveillance system, our method can contribute to improved security and identification processes in public spaces. This research not only advances the field of ear biometrics but also provides a viable solution for biometric identification in the context of mask-wearing and other facial obstructions.

Molecular-scale kinetic Monte Carlo simulation of pattern formation in photoresist materials for EUV nanolithography

A kinetic Monte Carlo (KMC) simulation tool for modeling the pattern formation process in photoresist materials for extreme ultraviolet (photon energy 92 eV) nanolithography is presented. The availability of such a tool should support the progress toward novel materials and experimental procedures that lead to an improved pattern resolution. The molecular-scale simulations describe the process in a stochastic and mechanistic manner and include the excitation of high-energy electrons upon light absorption, the creation of a charged-particle cloud, electron-induced chemical degradation of the photoresist molecules, the resulting bond formation between neighboring degraded molecules, and a chemical development step after which a pattern of the remaining non-dissolved molecules is obtained. The method is applied to the application-relevant class of Sn-oxocore photoresist materials and uses their known electronic structure and optical electron energy loss function. The validity of the approach is tested by comparing measured and simulated total electron yield spectra and photoelectron spectra. A demonstration of the method is given by calculating the dose and pitch dependent average shape and stochastic variability (line edge roughness) of line patterns that are obtained for rectangular and sine-wave illumination, assuming various scenarios that determine how molecular-scale degradation will lead to bond creation. We show how from these simulations the ultimate pattern resolution can be deduced. The findings are analyzed systematically using results of KMC simulations that reveal the size of the cloud of degraded molecules around a point of absorption (blur length) and that further reveal the sensitivity to uniform illumination (contrast curves), and using percolation theory. We find that KMC modeling captures the consequences of the strong gradients in the density of degraded molecules and of the stochasticity of the patterning process that simplified models do not include, leading to a significantly improved view of the final pattern quality.

3DPatBody: 3D dataset of human bodies of a patagonian population and their anthropometric measurements

The study of human body shape using classical anthropometric techniques is often problematic due to several error sources. Instead, 3D models and representations provide more accurate registrations, which are stable across acquisitions, and enable more precise, systematic, and fast measuring capabilities. Thus, the same person can be scanned several times and precise differential measurements can be established in an accurate manner. Here we present 3DPatBody, a dataset including 3D body scans, with their corresponding 3D point clouds and anthropometric measurements, from a sample of a Patagonian population (female=211, male=87, other=1). The sample is of scientific interest since it is representative of a phenotype characterized by both its biomedical meaning as a descriptor of overweight and obesity, and its population-specific nature related to ancestry and/or local environmental factors. The acquired 3D models were used to compare shape variables against classical anthropometric data. The shape indicators proved to be accurate predictors of classical indices, also adding geometric characteristics that reflect more properly the shape of the body under study.

Multijet event shape variables for Mueller-Navelet jet topologies

This paper presents a new set of multijet event shape variables introduced to further understand the Mueller-Navelet jet topology. This topology consists of having at least one pair of jets with a very large rapidity separation between them, treating additional jet activity inclusively. This multijet topology is expected to shed light on the radiation pattern that is expected in the high-energy limit of the strong interaction. The paper relies on a Monte Carlo event generator analysis. One set of predictions uses the ex event generator, which is based on Balitsky-Fadin-Kuraev-Lipatov (BFKL) perturbative quantum chromodynamics (pQCD) evolution with a resummation of large logarithms of energy at leading-logarithmic accuracy. The ex predictions are compared with a fixed-order next-to-leading order pQCD calculation using matched to the parton shower of ythia8 (NLO+PS), which is the standard for NLO generator predictions at the LHC. We find that both approaches lead to compatible results at current LHC energies, assuming the current experimental constraints for the reconstruction of low transverse momentum jets in ATLAS and CMS. This shows the reliability of the BFKL approach at describing the behavior of the strong interaction in the preasymptotic limit of high center-of-mass energies. Differences between the NLO+PS and the BFKL-based approaches are found when the jet multiplicity is increased or when the minimum transverse momentum of the jets is decreased. Published by the American Physical Society 2024

Quantitative Endogenous Polyamine Analysis via Capillary Electrophoresis/Mass Spectrometry: Characterization and Practical Considerations.

Commonly used analytical techniques for polyamine analysis, including derivatization and mixed-mode liquid chromatography (LC), have inherent disadvantages. Capillary electrophoresis (CE) is uniquely suited to analyze small, highly charged molecules because analytes are separated on the basis of their electrophoretic mobility, not polarity or association with a stationary phase. Microfluidic CE-mass spectrometry (mCE-MS) is a relatively recent addition to commercially available CE offerings that streamlines traditional CE-MS interfacing and has the potential to improve upon classic CE challenges to robustness and reproducibility. MS instrument choice and scanning parameters are strongly influenced by a need for high acquisition rate to adequately sample CE peaks. Alternatively, isotachophoresis on loading can be intentionally avoided to produce sufficiently wide peaks. The mCE platform utilized here performed very well in many metrics; a limit of detection (LOD) as low as 0.25ng/mL was achieved for spermidine, and endogenous spermidine was easily detected in blood with this method. Both of these are challenging tasks for any separation technique and demonstrate a strong use case for the platform. During experimentation, various idiosyncrasies in the commercial CE-MS interface resulted in extensive chip-to-chip variability in both peak shape and LOD, complicating the application to robust absolute quantitation. Practical guidance for similar analyses is provided.

Breast decorations from the burials of the Bolshiye Pamyaly burial ground of the XVIII – first half of the XIX century

The article for the first time publishes materials from the Bolshiye Pamyaly Mari burial ground, discovered in 2022. The paper studies the sul’gams, one of the numerous groups of decorations in the burial set of the burial ground without mounds of the XVIII – midXIX centuries. The relevance of the topic is due to the fact that the depicted patterns can trace the trends of cultural evolution and, at the same time, the continuity of forms with earlier ones. The typology of breast decorations, the basis of which are sul’gams, and their arrangement are considered. The classification of sul’gams uses the method of considering them as parts of breast decorations, considered by T.B. Nikitina according to their functional purpose. Statistical analysis by type indicates a significant predominance of the type II in the burial ground, for functional purpose - decorations. Sul’gams are most often found in burials in the number of one piece, but there are also two. They are not found with male bones. The burial ground is characterized as a monument of Mari culture. In some cases, the shapes and ornamentation of the sul’gams find analogies in the products of neighboring Chuvash and Mordvinian cultures. This decoration in the materials of the burial ground is distinguished by the variability of shapes and patterns.

Inter-call intervals, but not call durations, adhere to Menzerath's Law in the submissive vocal bouts of meerkats.

Diverse information encoding systems, including human language, the vocal and gestural systems of non-human animals and the structure of DNA and proteins, have been found to conform to 'Menzerath's Law'-a negative relationship between the number of units composing a sequence, and the size of those units. Here, we test for the presence of Menzerath's Law in the vocal bouts produced in a submissive context by meerkats (Suricata suricatta). Using a suite of Bayesian mixed effects models, we examined 1676 vocal bouts produced by 89 wild meerkats, ranging from 1 to 590 calls in length, to determine whether the number of calls composing each bout had a negative relationship with the duration of those calls or their inter-call intervals. In contradiction to Menzerath's Law, we found that the duration of vocalizations had a positive relationship with the number of calls in a bout. However, the duration of intervals between calls did have a negative relationship with bout size. Moreover, both calls and intervals had longer durations the closer they were positioned to the end of the bout. These findings highlight the multi-faceted ways in which efficiency trade-offs can occur in the vocal repertoires of non-human animals, shaping variability in the production of signal forms.

Model-based dimensional NDE from few X-ray radiographs: Application to the evaluation of wall thickness in metallic turbine blades

The extraction of 3D dimensional measurements based on a limited number of 2D X-ray radiographs of a part would offer a significant speed-up of quality control procedures in industry. However, there are challenges with respect to both measurements and uncertainties. This work addresses these challenges by creating an estimated numerical model of the imaged part on which dimensional measurements can be made. The numerical model is chosen as a parametric deformable model that encodes the expected shape variability of the parts resulting from the manufacturing process. The parameters and uncertainties of the numerical model of the imaged part are estimated by the registration of the computed projections of the model and the observed radiographs without the need of any segmentation. The registration requires the model, the initial parameters, and the observed radiographs. The proposed approach is applied to the inspection of turbine blades manufactured by investment casting, and in particular to the measurement of their wall thickness, which is a critical control. The deformable model consists in partitioning the inner ceramic core into multiple subparts, which may undergo a rigid body motion with respect to the master die. Wall thickness measurements are determined from the estimation of these rigid body motions. To assess the reliability of the proposed procedure, a repeatability study is performed. In addition, wall thickness measurements were compared to corresponding measurements from the surface of the metal boundary obtained by X-ray computed tomography. This surface was determined from a reconstructed tomogram using commercial software. Both analyses show that such measurements are reliable and efficient. Furthermore, residual differences between captured and computed projections reveal localized shape deviations from the CAD model, meaning that despite localized model errors, the approach is operable.

Factors Determining Promotional and Image-Building Activities of Vocational Schools

ABSTRACT This study investigates the factors influencing the promotion and image-building activities of vocational schools in Poland, with a focus on the Podlaskie Voivodeship (one of Poland’s fifteen regions). Using structural analysis and the MICMAC methodology, the research identifies key variables shaping vocational education promotion, including external factors like competition in the education market, generational attitudes of students, and regional economic development, as well as internal factors such as schools’ initiative-taking capacity, awareness of promotional needs, and relationships with employers. Expert stakeholder evaluations are analyzed using a structured methodology, ensuring that identified factors and relationships reflect insights from professionals and stakeholders in the vocational education sector. Significant interdependencies were found among factors, emphasizing the pivotal role of relationships with employers and the adaptive use of social media as a goal-oriented tool for communication. Findings underscore that effective promotion of vocational education requires a strategic approach integrating internal strengths with external collaborations to address stakeholder needs, improve societal perception, and enhance competitiveness. Key recommendations include fostering relational capital, involving employers in defining school missions, and aligning promotional strategies with dynamic labor market demands and technological advancements.