Search Results (143)

Traumatic injury remains a major cause of death worldwide, with bleeding being one of its most critical and life-threatening consequences. Whole-body computed tomography (WBCT) has become a standard diagnostic method in trauma settings; however, timely interpretation remains challenging for acute care physicians. In this study, we propose a new automated method for detecting traumatic bleeding in CT images using a three-dimensional object detection model enhanced with an atrous spatial pyramid pooling (ASPP) module. Furthermore, we incorporate a false positive (FP) reduction approach based on multi-organ segmentation, as developed in our previous study. The proposed method was evaluated on a multi-institutional dataset of delayed-phase contrast-enhanced CT images using a six-fold cross-validation approach. It achieved a maximum sensitivity of 90.0% with 587.3 FPs per case and a sensitivity of 70.0% with 46.9 FPs per case, outperforming previous segmentation-based methods. In addition, the average processing time was reduced to 4.2 ± 1.1 min. These results suggest that the proposed method enables rapid and accurate bleeding detection, demonstrating its potential for clinical application in emergency trauma care. Full article

The use of gait analysis to differentiate among paediatric populations with neurological and developmental conditions such as idiopathic toe walking (ITW), cerebral palsy (CP), and hereditary spastic paraplegia (HSP) remains challenging due to the insufficient precision of current diagnostic approaches, leading in some cases to misdiagnosis. Existing methods often isolate the analysis of gait variables, overlooking the whole complexity of biomechanical patterns and variations in motor control strategies. While previous studies have explored the use of statistical physics principles for the analysis of impaired gait patterns, gaps remain in integrating both kinematic and kinetic information or benchmarking these approaches against Deep Learning models. This study evaluates the robustness of statistical physics metrics in differentiating between normal and abnormal gait patterns and quantifies how the data source affects model performance. The analysis was conducted using gait data sets from two research institutions in Madrid and Dublin, with a total of 81 children with ITW, 300 with CP, 20 with HSP, and 127 typically developing children as controls. From each kinematic and kinetic time series, Shannon’s entropy, permutation entropy, weighted permutation entropy, and time irreversibility metrics were derived and used with Random Forest models. The classification accuracy of these features was compared to a ResNet Deep Learning model. Further analyses explored the effects of inter-laboratory comparisons and the spatiotemporal resolution of time series on classification performance and evaluated the impact of age and walking speed with linear mixed models. The results revealed that statistical physics metrics were able to differentiate among impaired gait patterns, achieving classification scores comparable to ResNet. The effects of walking speed and age on gait predictability and temporal organisation were observed as disease-specific patterns. However, performance differences across laboratories limit the generalisation of the trained models. These findings highlight the value of statistical physics metrics in the classification of children with different toe walking conditions and point towards the need of multimetric integration to improve diagnostic accuracy and gain a more comprehensive understanding of gait disorders. Full article

Traditionally, Helicobacter pylori (HP) gastritis has been diagnosed by pathologists through the examination of gastric biopsies using optical microscopy with standard hematoxylin and eosin (H&E) staining. However, with the adoption of digital pathology, the identification of HP faces certain limitations, particularly due to insufficient resolution in some scanned images. Moreover, interobserver variability has been well documented in the traditional diagnostic approach, which may further complicate consistent interpretation. In this context, deep convolutional neural network (DCNN) models are showing promising results in the automated detection of this infection in whole-slide images (WSIs). The aim of the present article is to detect the presence of HP infection from our own institutional dataset of histopathological gastric biopsy samples using different pretrained and recognized DCNN and AutoML approaches. The dataset comprises 100 H&E-stained WSIs of gastric biopsies. HP infection was confirmed previously using immunohistochemical confirmation. A total of 45,795 patches were selected for model development. InceptionV3, Resnet50, and VGG16 achieved AUC (area under the curve) values of 1. However, InceptionV3 showed superior metrics such as accuracy (97%), recall (100%), F1 score (97%), and MCC (93%). BoostedNet and AutoKeras achieved accuracy, precision, recall, specificity, and F1 scores less than 85%. The InceptionV3 model was used for external validation, and the predictions across all patches yielded a global accuracy of 78%. In conclusion, DCNN models showed stronger potential for diagnosing HP in gastric biopsies compared with the auto ML approach. However, due to variability across pathology applications, no single model is universally optimal. A problem-specific approach is essential. With growing WSI adoption, DL can improve diagnostic accuracy, reduce variability, and streamline pathology workflows using automation. Full article

Against the backdrop of China’s urban transformation from incremental expansion to stock regeneration, community regeneration has emerged as a critical mechanism for enhancing urban governance efficacy. As fundamental units of urban systems, the regeneration of communities requires comprehensive approaches to address complex socio-spatial challenges, with public participation serving as the core driver for achieving sustainable renewal goals. However, significant regional disparities persist in the effectiveness of public participation across China, necessitating the systematic institutionalization of participatory practices. Guangzhou, as a pioneering city in institutional innovation and the practical exploration of urban regeneration, provides a representative case for examining the evolutionary trajectory of participatory planning. This research employs Arnstein’s Ladder of Participation theory, utilizing literature analysis and comparative case studies to investigate the evolution of participatory mechanisms in Guangzhou’s community regeneration over four decades. The study systematically examined the transformation of public engagement models across multiple dimensions, including organizational frameworks of participation, participatory effectiveness, diversified financing models, and the innovation of policy instruments. Three paradigm shifts were identified: the (1) transition of participants from “passive responders” to “active constructors”, (2) advancement of engagement phases from “fragmented intervention” to “whole-cycle empowerment”, and (3) evolution of participation methods from “unidirectional communication” to “collaborative co-governance”. It identifies four drivers of participatory effectiveness: policy frameworks, financing mechanisms, mediator cultivation, and engagement platforms. To enhance public engagement efficacy, the research proposes the following: (1) a resilient policy adaptation mechanism enabling dynamic responses to multi-stakeholder demands, (2) a diversified financing framework establishing a “government guidance + market operation + resident contribution” cost-sharing model, (3) a professional support system integrating “localization + specialization” capacities, and (4) enhanced digital empowerment and institutional innovation in participatory platform development. These mechanisms collectively form an evolutionary pathway from “symbolic participation” to “substantive co-creation” in urban regeneration governance. Full article

Building Information Modeling (BIM) concepts are permeating the approach to the design of buildings and landscapes for the architectural, engineering, and construction sectors. Recent regulations require that even medium–small-size public works are managed through BIM-driven design. These circumstances have led to an increase in research on the topic. The expansion of the demand of BIM-skilled professionals urges higher education institutions to re-engineer their design programs. The aim of this paper is to evaluate this academic education transition in the Department of Agricultural Sciences at the University of Sassari, Italy. The method consists of a BIM academic education assessment framework based on ten criteria clustered into three macro-issues. The application of this framework to the assessment of three diploma final theses signals that some actions have been undertaken (i.e., introducing BIM basic concepts in rural building and landscape design, stimulating interest in students, clarifying the dimensions of BIM, and promoting the concept of 3D object design and management), but still, much work must be carried out. The work confirms typical barriers to the implementation of BIM concepts in the core curriculum and the need to mobilize the whole educational ecosystem to achieve satisfactory progress toward effective innovation in contemporary BIM-led design teaching. This work represents the first attempt to evaluate the progress of the Department of Agricultural Sciences, University of Sassari, toward the integration of BIM concepts in its courses and to position this transition in an international panorama. Full article

This paper discusses the development of an Integrated Building Energy Model (IBEM) in MATLAB (R2024b) for a university campus building. In the general context of the development of integrated energy district models to guide the evolution and planning of smart energy grids for increased efficiency, resilience, and sustainability, this work describes in detail the development and use of an IBEM for a university campus building featuring a heat pump-based heating/cooling system and PV generation. The IBEM seamlessly integrates thermal and electrical aspects into a complete physical description of the energy performance of a smart building, thus distinguishing itself from co-simulation approaches in which different specialized tools are applied to the two aspects and connected at the level of data exchange. Also, the model, thanks to its physical, white-box nature, can be instanced repeatedly within the comprehensive electrical micro-grid model in which it belongs, with a straightforward change of case-specific parameter settings. The model incorporates a heat pump-based heating/cooling system and photovoltaic generation. The model’s components, including load modeling, heating/cooling system simulation, and heat pump implementation are described in detail. Simulation results illustrate the building’s detailed power consumption and thermal behavior throughout a sample year. Since the building model (along with the whole campus micro-grid model) is implemented in the MATLAB Simulink environment, it is fully portable and exploitable within a large, world-wide user community, including researchers, utility companies, and educational institutions. This aspect is particularly relevant considering that most studies in the literature employ co-simulation environments involving multiple simulation software, which increases the framework’s complexity and presents challenges in models’ synchronization and validation. Full article

Background/Objectives: Long COVID-19 is characterized by persistent symptoms lasting three months or more following SARS-CoV-2 infection. Nutrition has emerged as a modifiable factor influencing recovery trajectories and symptom burden; however, existing evidence remains fragmented across diverse study designs and populations. This scoping review synthesized global evidence on the role of diet and nutrition in managing long COVID-19 symptoms and supporting recovery. Methods: Following PRISMA-ScR and Joanna Briggs Institute guidelines for scoping reviews, we searched major biomedical databases for studies published between 2020 and 2025. Eligible studies examined dietary intake, nutritional status, or nutrition-related interventions in adults with long COVID-19. Results: After duplicates were removed, 1808 records were screened, resulting in 50 studies that met the inclusion criteria—27 intervention studies and 23 observational studies. Nutritional exposures included micronutrients (e.g., vitamins D, K₂), amino acids (e.g., L-arginine), multinutrient formulations, microbiota-targeted therapies (e.g., probiotics, synbiotics), nutritional status, diet quality, and whole-diet patterns (e.g., the Mediterranean diet). Approximately 76% of studies reported improvements in long COVID-19-related symptoms such as fatigue, mood disturbances, physical function, and markers of inflammation. Conclusions: Diet and nutrition may support long COVID-19 recovery by targeting inflammation and the gut microbiome to alleviate symptoms and improve functional outcomes. Well-powered trials of whole-diet approaches, combined with targeted supplementation, are needed to confirm their potential as scalable, accessible tools for post-COVID-19 recovery and management. Full article

Societies need to develop more sustainable ways of living, working, and doing business. Education for sustainable development (ESD) plays a pivotal role in this endeavor. The aim is to provide people with the necessary knowledge, values, and skills for the needed transformation. Therefore, organizations of adult and continuing education must address issues of climate protection and sustainability in their programs and act accordingly in the way the organization is managed. This article reports on a qualitative study that involves leaders of adult education institutions in China, Germany, and the USA. This study seeks to investigate what these leaders do and how they act to implement ESD in their organizations. It specifically looks at current challenges, management strategies, beliefs, and values of the leaders. The results of this study show that leaders of adult and continuing education organizations recognize the need to address sustainability in adult education. However, they face many challenges in implementing ESD, including a lack of resources (e.g., finances and staff), structural barriers, and difficulties in reaching new target groups. Despite these challenges, many participants strive to develop their organizations in a more sustainable way, such as through curriculum design and campus management. Some leaders take a comprehensive approach, guided by the Whole Institution Approach, by integrating ESD into their institution’s vision and mission, establishing dedicated working groups, and forming new partnerships with external stakeholders. Overall, this study highlights the crucial role of leadership in advancing sustainability efforts. Full article

Research has shown that a whole-school approach (WSA) is needed to increase student physical activity. There is a lack of empirical data on teachers’ opinions and needs regarding the implementation of a WSA approach to encourage physical activity. Our study aims to address this gap by identifying teachers’ and academics’ beliefs about the usefulness, content, and delivery mode of a WSA in fostering physical activity. To address the research aim, an exploratory mixed methods design was employed. Initially, a qualitative study with academics and stakeholders was conducted, followed by a quantitative investigation with teachers and school employees. In the first study, seven participants working in education took part in one-to-one interviews concerning their views on the usefulness, content, and delivery of whole-school education. The participants stressed the importance of the WSA and urged that educational authorities should consider the needs of children and the school community, promote teacher collaboration, pursue longevity, and engage with stakeholders and institutions throughout the process. In the second study, 160 school teachers and staff answered a survey about the content and delivery mode of an educational material for the promotion of WSA to fostering physical activity. The analyses indicated that participants preferred a three to six hours course, a hybrid mode of delivery, inclusion of best practices, and knowledge on how to implement a WSA. The study’s findings reveal several implications and recommendations for educators creating comprehensive school-based physical activity programs. Full article

Within the scope of “Eco Map of Zagreb” project, eight sensor sets (type AQMeshPod) were set up at an automatic measuring station at the Institute for Medical Research and Occupational Health (IMROH) for comparison with reference methods for air quality measurement during 2018. This station is a city background station within the Zagreb network for air quality monitoring, where measurements of SO₂, CO, NO₂, O₃, PM₁₀ and PM_2.5, are performed using standardized methods accredited according to EN ISO/IEC 17025. This paper presents a comparison of pollutant mass concentrations determined by sensors with reference methods. The data were compared and filtered to remove outliers and handle deviations between the results obtained by sensors and reference methods, considering the different approaches to gas and PM data. A comparison of sensor results with the reference methods showed a large scattering of all gaseous pollutants while the comparison for PM₁₀ and PM_2.5 indicated a satisfactory low dispersion. The results of a regression analysis showed a significant seasonal dependence for all pollutants. Significant statistical differences between the reference methods and sensors for the whole year and in all seasons for all gas pollutants, as well as for PM₁₀, were observed, while for PM_2.5 statistical significance showed varying results. Full article

The construction of complex systems is of great significance in enhancing national competitiveness and promoting social development. However, the academic community currently lacks a systematic understanding of its sustainable innovation mechanism. This study selected the China Manned Space Engineering Application System (CMSEAS) as a representative case of a complex system. Research data were collected by a multi-method approach including document literature, internal data, field research, and interviews. Through the lens of grounded theory, the study delves into how the complex system achieves local innovation and how to maintain the sustainability of innovation. Findings indicate that, firstly, late-mover advantage and spiritual strength jointly contribute to the knowledge accumulation of national major task-oriented complex systems, and this knowledge accumulation significantly improves the innovation ability of complex systems. Secondly, while emphasizing the enhancement of innovation capabilities, it is imperative for complex systems to implement holistic risk management, which is an important guarantee for successfully achieving the goal. Thirdly, in the context of market failure, the whole nation system provides strong support for the national major task-oriented complex system. The overall institution and overall capacity constitute the backbone for ensuring sustainable innovation. Full article

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the “creative potential” of “classical” transformation is the requirement for adequate “fitting” of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms. Full article

The technological development of oil companies in Mexico is essential for ensuring their economic sustainability. A mechanism for the effective management of the technological development of oil companies, and the industry as a whole, is to determine its priority areas. This article provides a calculation for the choice of planning directions for the development of the oil sector in Mexico and related studies. Currently, the most promising technologies are offshore drilling and production. To achieve the study goals, we analyzed the patent activity of the oil sector. The results showed an unfavorable trend: the number of private and public patents in Mexico is decreasing. For example, from 2017 to 2023, the number of patents for offshore technologies decreased by more than 10 times. This dynamic significantly hinders the development of the oil industry. Despite the general measures taken within the framework of energy policy, the volume of oil production is constantly declining. Thus, in order to ensure the continued reproduction potential of the oil sector, it is necessary to take into account the importance of research and development. The innovation rating of the Mexican Petroleum Institute, a state-funded research center for the hydrocarbon sector, has been declining, having fallen by more than 50% from 102 international patents in 2014 to 40 in 2024. Today, the Mexican Institute of Petroleum is in the 48th percentile in terms of research performance among research institutes. The present authors’ approach considers that the intensification of technological development, which is costly, should not be an end in itself but rather an important means of increasing the efficiency of the integrated activities of oil companies. To integrate the patent-technological component of the strategic planning of oil companies, the concept of sub-potentials is proposed. The potential for the functioning and development of an oil enterprise from the point of view of the systems approach is decomposed into the sub-potentials of reproduction, defense, management, and reserve, which, under adverse conditions, can transition to the sub-potentials of threat and containment. An important task is to determine these transition points. The patent-technological component is taken into account in the sub-potential of reproduction. The remaining components of company development are taken into account within the framework of other sub-potentials, which are not discussed in detail in this article. At the same time, due to the unified conceptual approach, the integration of goals and objectives for technological development into a single economic and socio-ecological strategy for oil enterprises is ensured, which is the most effective approach to ensure their sustainable development. The dynamics of patent generation are an important factor in assessing the technological component and, in general, the effectiveness of projects in the energy sector. Full article

The role and responsibility of universities in supporting student mental health has been the subject of high-profile legal debate. Drawing on a thematic analysis of twelve semi-structured focus groups conducted during the Student Minds UK University Mental Health Charter consultations, this paper elucidates the experiences, perceptions, and practices of 75 staff working within student services to support student mental health, with the aim of clarifying the implications for role responsibilities within a whole university approach. Participants described being ‘stretched at both ends’ in response to a significant and ongoing increase both in overall demand and complexity of presentation, further compounded by capacity challenges in public mental health services. Despite the care and commitment of staff, these conditions compromise the effectiveness, safety, and accessibility of university services. As a result, students increasingly present with mental health challenges in academic settings, multiplying risk for themselves, their peers, academic staff, and their universities, whilst negatively impacting the learning process. Thus, precisely as sectoral debate around UK universities’ legal duty of care intensifies, the role and responsibility of university services and academic staff in relation to other institutional and external stakeholders is becoming increasingly indeterminate. Taken together, the findings demonstrate the imperative of clearer conceptualisation and investment in student services alongside closer working relationships with academic staff to ensure student success and safety, and to meet the principles of good practice in the University Mental Health Charter, as advocated by UK government. Full article

Background and Objectives: Brain tumors are complex diseases that require careful diagnosis and treatment. A minor error in the diagnosis may easily lead to significant consequences. Thus, one must place a premium on accurately identifying brain tumors. However, deep learning (DL) models often face challenges in obtaining sufficient medical imaging data due to legal, privacy, and technical barriers hindering data sharing between institutions. This study aims to implement a federated learning (FL) approach with privacy-preserving techniques (PPTs) directed toward segmenting brain tumor lesions in a distributed and privacy-aware manner.Methods: The suggested approach employs a model of 3D U-Net, which is trained using federated learning on the BraTS 2020 dataset. PPTs, such as differential privacy, are included to ensure data confidentiality while managing privacy and heterogeneity challenges with minimal communication overhead. The efficiency of the model is measured in terms of Dice similarity coefficients (DSCs) and 95% Hausdorff distances (HD95) concerning the target areas concerned by tumors, which include the whole tumor (WT), tumor core (TC), and enhancing tumor core (ET). Results: In the validation phase, the partial federated model achieved DSCs of 86.1%, 83.3%, and 79.8%, corresponding to 95% values of 25.3 mm, 8.61 mm, and 9.16 mm for WT, TC, and ET, respectively. On the final test set, the model demonstrated improved performance, achieving DSCs of 89.85%, 87.55%, and 86.6%, with HD95 values of 22.95 mm, 8.68 mm, and 8.32 mm for WT, TC, and ET, respectively, which indicates the effectiveness of the segmentation approach, and its privacy preservation.Conclusion: This study presents a highly competitive, collaborative federated learning model with PPTs that can successfully segment brain tumor lesions without compromising patient data confidentiality. Future work will improve model generalizability and extend the framework to other medical imaging tasks. Full article