Search Results (621)

Background/Objectives: Targeting individuals with certain characteristics provides improved precision in many healthcare applications. An alert mechanism for COPD exacerbations has recently been validated. It has been argued that its efficacy improves considerably with stratification. This paper provides an in-depth analysis of the cough data of the stratified cohort to identify options for and the feasibility of improved precision in the alert mechanism for the intended patient group. Methods: The alert system was extended using a system complementary to the existing one to accommodate observed rapid changes in cough trends. The designed system was tested in a post hoc analysis of the data. The trend data were inspected to consider their meaningfulness for patients and caregivers. Results: While stratification was effective in reducing misses, the augmented alert system improved the sensitivity and number of early alerts for the acute exacerbation of COPD (AE-COPD). The combination of stratification and the augmented mechanism led to sensitivity of 86%, with a false alert rate in the order of 1.5 per year in the target group. The alert system is rule-based, operating on interpretable signals that may provide patients or their caregivers with better insights into the respiratory condition. Conclusions: The augmented alert system operating based on cough trends has the promise of increased precision in detecting AE-COPD in the target group. Since the design and testing of the augmented system were based on the same data, the system needs to be validated. Signals within the alert system are potentially useful for improved self-management in the target group. Full article

The Santurbán paramo is a sensitive high-mountain ecosystem exposed to pressures from extractive and agricultural activities, as well as increasing tourism. In response, this study presents a context-aware recommendation system designed to support sustainable tourism through the integration of deep neural networks and ontology-based semantic modeling. The proposed system delivers personalized recommendations—such as activities, accommodations, and ecological routes—by processing user preferences, geolocation data, and contextual features, including cost and popularity. The architecture combines a trained TensorFlow Lite model with a domain ontology enriched with GeoSPARQL for geospatial reasoning. All inference operations are conducted locally on Android devices, supported by SQLite for offline data storage, which ensures functionality in connectivity-restricted environments and preserves user privacy. Additionally, the system employs geofencing to trigger real-time environmental notifications when users approach ecologically sensitive zones, promoting responsible behavior and biodiversity awareness. By incorporating structured semantic knowledge with adaptive machine learning, the system enables low-latency, personalized, and conservation-oriented recommendations. This approach contributes to the sustainable management of natural reserves by aligning individual tourism experiences with ecological protection objectives, particularly in remote areas like the Santurbán paramo. Full article

Objectives: To compare the objective refraction of young hyperopes obtained by two wavefront autorefractors with identical measurement principles but different optical designs: a monocular closed-field (VX 120) and a binocular open-field (Eye Refract), both developed by the same manufacturer (Visionix; Pont-de-l’Arche, France). Methods: A randomized, cross-sectional study was carried out with 37 hyperopic participants (18.2 ± 7.8 years; range 8 to 31 years). Each participant underwent two measurement sessions (one with and one without cycloplegia), during which three measurements were taken per autorefractor (monocular and binocular). Refractive variables (M, J0, and J45) were analyzed in one randomly selected eye. Results: The spherical equivalent (M) showed significant differences between autorefractors under noncycloplegic and cycloplegic conditions (p < 0.001). Without cycloplegia, the binocular autorefractor measured +0.45 (+1.49, −0.58) D more hyperopia than the monocular device. Under cycloplegia, this difference decreased to +0.26 D (+0.99, −0.48) D. Both autorefractors provided higher hyperopia with cycloplegia, with differences inversely correlated with age (r = −0.4; p < 0.05). Conclusions: Whenever possible, refraction in young hyperopes should be measured under cycloplegic conditions using a binocular open-field autorefractor to promote greater accommodative relaxation and ensure more reliable hyperopia measurements in both clinical practice and research. Full article

The Panama Canal, inaugurated in 1914, continues to play a pivotal role in global maritime connectivity. In 2016, the Canal underwent a significant expansion, reshaping maritime transit by accommodating larger vessels and reinforcing its strategic importance in international trade. The objective of this study is to identify a suitable time series statistical model to forecast the number of vessels transiting the Panama Canal. The three approaches employed were the following: the Autoregressive Integrated Moving Average (ARIMA) model, the Holt–Winters (HW) exponential smoothing method, and the Neural Network Autoregressive (NNAR) model. The models were compared based on forecasting errors to evaluate their predictive accuracy. Overall, the NNAR model exhibited slightly better predictive performance than the SARIMA (1,0,1) (0,1,1) model in terms of error, with both outperforming the Holt–Winters model by a significant margin. Full article

Semantically enriched trajectories have attracted growing interest in recent research, driven by the need for more expressive and context-aware movement data analysis. Two primary approaches have emerged for the storage and management of such data: moving object databases, which operate at the transactional or operational level, and trajectory data warehouses (TDWs), which support analytical processing within decision support systems. Conventional TDW methodologies typically model semantic aspects of trajectories by introducing new dimensions into the data warehouse schema. However, this approach often requires structural modifications to the schema in order to accommodate additional semantic attributes, potentially resulting in significant disruptions to the architecture and maintenance of the underlying decision support systems. To overcome this limitation, we propose a novel TDW model that supports dynamic and extensible integration of semantic aspects, without necessitating changes to the schema. This design enhances flexibility and promotes seamless adaptability to domain-specific requirements. To enable such extensibility, we propose an innovative approach to representing semantic trajectories by leveraging natural language processing (NLP) techniques. without relying on traditional spatiotemporal features. This enables the analysis of semantic movement patterns purely through textual context. Finally, we present a comprehensive framework that implements the proposed model in real-world application scenarios, demonstrating its practical extensibility. Full article

This study presents a data-driven, multi-objective optimization framework for user-centric product form design, integrating affective response modeling with coupled constraint satisfaction. Initially, morphological analysis and aesthetic evaluation are employed to extract critical design elements, while cluster analysis segments users based on preference data. Dominance-based rough set theory is then applied to derive group-specific affective patterns, which are subsequently modeled using Genetic Algorithm-optimized Backpropagation Neural Networks (GA-BPNN). The framework leverages Non-dominated Sorting Genetic Algorithm II (NSGA-II) to generate Pareto-optimal solutions, balancing aesthetic preferences and engineering constraints across user groups. A case study on SUV form design validates the proposed methodology, demonstrating its efficacy in delivering optimal, user-group-targeted design solutions while accommodating individual variability and constraint interdependencies. The results highlight the framework’s potential as a generalizable approach for emotion-aware, constraint-compliant product design. Full article

Background/Objectives: SARS-CoV-2 vaccine candidates comprising the receptor binding domain (RBD) of the spike protein have been shown to confer protection against infection. Previous research evaluating vaccine candidates with SARS-CoV-2 RBD fused to ferritin (RBD-ferritin) and other scaffolds suggested that multimeric assemblies of RBD can enhance antigen presentation to improve the potency and breadth of immune responses. Though RBDs directly fused to a self-assembling scaffold can be delivered as messenger RNA (mRNA) formulated with lipid nanoparticles (LNPs), reports of SARS-CoV-2 vaccine candidates that combine these approaches remain scarce. Methods: Here, we designed RBD fused to AP205 or TIP60 self-assembling nanoparticles following a search of available structures focused on several scaffold properties. RBD-AP205 and RBD-TIP60 were tested for antigenicity following transfection and for immunogenicity and neutralization potency when delivered as mRNA in mice, with RBD-ferritin as a direct comparator. Results: All scaffolded RBD constructs were readily secreted to transfection supernatant and showed antigenicity in ELISA, though clear heterogeneity in assembly was observed. RBD-AP205 and RBD-TIP60 also exhibited robust antibody binding and neutralization titers in mice that were comparable to those elicited by RBD-ferritin or a full-length membrane-bound spike. Conclusions: These data suggest that AP205 and TIP60 can present RBD as effectively as ferritin and induce similar immune responses. By describing additional scaffolds for multimeric display that accommodate mRNA delivery platforms, this work can provide new tools for future vaccine design efforts. Full article

Traditional approaches in tunnel lighting have been directed toward the installation of appropriate luminaires in the intermediate and transitional sections with the simple objective of diminishing the effect of delayed visual accommodation during daylight hours. Such efforts run in parallel with the target of keeping the huge electrical use at the lowest level. Nevertheless, inadequate attention has been conceded to the interior areas, whose noticeable longitude in several instances, and subsequently the duration of occupancy of the users, can produce discomfort in the majority of the tunnel or underground passageway. It is in this region where the flicker effect presents a more remarkable impact. Although such effect is in fact uncomfortable, the strategies to eliminate it efficiently have not been developed in depth and the result is still deserving, especially in terms of sustainability. The reasons for this neglect, as well as some particularities and solutions, are exposed and discussed in the present article. Specifically, it is proved that the use of sunlight can be an adequate initiative and a positive energy input into design and retrofit tunnels capable of hampering or totally avoiding such unwanted effect. The innovative tunnel geometry explained in this manuscript is not cylindrical, and it is not based in revolution forms. Thus, it prevents the appearance of such unnerving visual effects, which compromise sustainability and endanger security. We are in the position to explain how the vector field generated by the normal to the points of the novel surface displayed remains non-parallel, ensuring appropriate diffusivity and, consequently, an even distribution of radiated energy. In the same manner, the notion of the tunnel is extended from a linear system to a veritable network of galleries, which can traverse in space bi- or even three-dimensionally. Accordingly, we will offer diverse instances of junctions and splices that further enhance the permeability into the terrain, augmenting the resilience capabilities of this disruptive technology. With all the former, a net reduction of costs reaching 25% can be easily expected with revenues. Full article

Background/Objectives: Dental fear affects about one in four general dentistry patients in the U.S. and other high-income countries. However, the prevalence of fear in orthodontic practice has received scant attention, with no studies in the U.S. The aim of this study was to investigate the prevalence of orthodontic and general dentistry fear and the relationship between the two among patients at a large, U.S. urban university orthodontic clinic serving a culturally and ethnically diverse population. Methods: Patients (N = 186) rated their general dentistry and orthodontic fear using a validated single-item scale. Results: A substantial proportion of patients experienced clinically significant fear of dentists (22.1% [95% CI 16.31–28.69%]) and orthodontists (17.2% [95% CI 11.61–22.82%]). There was a strong effect size (r = 0.67) between ratings of fear of dentists and orthodontists. Our prevalences were nearly identical to the weighted prevalences in the literature for general dentistry and orthodontic fear (22.90% [95% CI: 20.73–25.22%] and 17.65% [95% CI: 15.09–20.53%], respectively) among orthodontic patients. Conclusions: Despite orthodontic procedures being generally less fear-inducing than general dentistry, orthodontists should assume that over one in six patients will be fearful. Further research is needed to create an assessment of the most feared orthodontic stimuli and to broaden the application of evidence-based dental fear treatments. We recommend screening all orthodontic patients using a single, validated question; if patients are fearful, providers should use empathic communication and accommodate patient needs in treatment sessions. Full article

Background/Objectives: The aging of workers with intellectual and developmental disabilities is an emerging reality attributed to the rise in life expectancy and improved labor market access. In this study, “workers” is used as an inclusive, neutral term covering all individuals engaged in paid labor—whether employees, self-employed, freelancers, or those performing manual or non-manual tasks. It encompasses every form of work. It is crucial to comprehend the reality of aging workers from the perspectives of the primary individuals involved: the workers, their families, and supporting professionals. Methods: A qualitative study was developed, involving 12 focus groups and 107 participants, using NVivo 12 Pro for analysis; we used a phenomenological methodology and grounded theory. Results: A set of concrete needs was highlighted: among them, 33 were related to declining work ability due to aging and disability (WADAD), and 30 to transition to retirement. These needs were grouped into categories: workplace accommodations, coordination and collaboration, personal and family support, counseling and training, and other types of needs. Conclusions: This study establishes an empirical basis tailored to the needs of this group, enabling the development of prevention and intervention protocols that address WADAD and the transition to retirement. Full article

As part of the post-conflict reconstruction and recovery, the development of Kabul New City aims to bring relief to the existing capital city, Kabul, which has experienced exponential population growth, putting heavy pressure on its existing resources. Kabul New City is divided into four subsectors, and each of them is being developed and is expected to reach a target population by 2025, as defined by the master plan. The study’s objective is to determine which of the four zones are in demand and need to be prioritized for development, as per the model results. The data collection involves an online questionnaire, and the responses are collected from residents of Kabul and Herat. Agent-based modeling (ABM) is an emerging method of simulating urban dynamics. Cities are evolving continuously and are forming unique spatial patterns that result from the movement of residents in search of new locations that accommodate their needs and preferences. An agent-based model is developed using the weighted random selection process based on household size and income levels. The agents are the residents of Kabul and Herat, and the environment is the land use classification image using the Sentinel 2 image of Kabul New City. The barren class is treated as the developable area and is divided into four sub-sectors. The model simulates three alternative growth rate scenarios, i.e., ambitious, moderate, and steady. The results of the simulation reveal that the sub-sector Dehsabz South, being closer to Kabul city, is in higher demand. Barikab is another sub-sector high in demand, which has connectivity through the highway and is an upcoming industrial hub. Full article

Background/Objectives: A dietary pattern that simply reduces animal-based foods may be more acceptable to consumers than strict vegetarian or vegan diets. The objective of this investigation was to identify the most consistently used definitions of “flexitarian” dietary patterns, or dietary patterns with a reduced amount of animal foods. Then, sets of food-based dietary guidance (FBDG) from different countries and regions were evaluated to determine whether their guidance could accommodate flexitarian diets. Methods: Literature searches yielded 86 total results on flexitarian eating after screening by title/abstract, full text availability, and English language. Definitions of “flexitarian” were extracted from each article then reviewed and summarized. FBDGs available in English were downloaded from the Food and Agriculture Organization of the United Nations website. Guidance related to reduced animal product diets was extracted from FBDGs for eating patterns closest to 2000 kcal. Results: The summary definition of flexitarian included eating at least one animal product (dairy, eggs, meat, or fish) at least once per month but less than once per week. FBDGs from n = 42 countries or regions were downloaded and data extracted. Only FBDG from Sri Lanka explicitly describe a “semi-vegetarian” eating pattern, though n = 12 FBDGs describe a vegetarian pattern and n = 14 recommend reducing meat or animal food and/or choosing meat/dairy alternatives. Conclusions: Following a flexitarian dietary pattern in terms of reducing or limiting red meat is feasible and even implicitly recommended by the official dietary guidance of several countries. Most FBDGs examined did not include recommendations to decrease dairy or fish intake. Full article

Against the backdrop of the increasing penetration rate of new energy year by year, power systems face a continuously growing demand for flexibility. Under the structure of such a new power system, it is essential not only to introduce diverse flexible power sources but also to explore the flexible regulation capabilities of existing conventional power sources. To fully utilize the flexibility of thermal power units (TPUs), this study proposes a real-time optimal scheduling strategy for a wind–thermal energy-storage integrated system with an adaptive time division and variable objectives. Based on the evaluation results of the real-time flexible supply–demand relationship within a regional power grid, the operation modes of TPUs are categorized into three types: economic mode, peak shaving mode, and coordination mode. For each operation mode, corresponding optimization objectives are defined, and an energy storage control strategy is developed to assist in the peak shaving of TPUs. While effectively harnessing the flexibility of TPUs, the proposed method reduces both the frequency and capacity of TPUs entering deep peak shaving. Using data from a province in Northwest China as a case study, simulation calculations and analyses demonstrate that the proposed method increases renewable energy consumption by 314.37 MWh while decreasing system economic benefits by CNY 129,000. Compared with traditional scheduling methods for TPUs to accommodate renewable energy, the system benefit increases by CNY 297,000, and an additional 13.53 MWh of peak wind power is accommodated. These results confirm that the proposed scheduling strategy can significantly enhance the system’s ability to integrate new energy while maintaining its economic efficiency. Full article

Background/Objective: This study aims to evaluate the predictive performance of three supervised machine learning algorithms—decision tree (DT), support vector machine (SVM), and k-nearest neighbors (KNN) in forecasting key visual skills relevant to rhythmic gymnastics. Methods: A total of 383 rhythmic gymnasts aged 4 to 27 years were evaluated in various sports centers across Madrid, Spain. Visual assessments included clinical tests (near convergence point accommodative facility, reaction time, and hand–eye coordination) and eye-tracking tasks (fixation stability, saccades, smooth pursuits, and visual acuity) using the DIVE (Devices for an Integral Visual Examination) system. The dataset was split into training (70%) and testing (30%) subsets. Each algorithm was trained to classify visual performance, and predictive performance was assessed using accuracy and macro F1-score metrics. Results: The decision tree model demonstrated the highest performance, achieving an average accuracy of 92.79% and a macro F1-score of 0.9276. In comparison, the SVM and KNN models showed lower accuracies (71.17% and 78.38%, respectively) and greater difficulty in correctly classifying positive cases. Notably, the DT model outperformed the others in predicting fixation stability and accommodative facility, particularly in short-duration fixation tasks. Conclusion: The decision tree algorithm achieved the highest performance in predicting short-term fixation stability, but its effectiveness was limited in tasks involving accommodative facility, where other models such as SVM and KNN outperformed it in specific metrics. These findings support the integration of machine learning in sports vision screening and suggest that predictive modeling can inform individualized training and performance optimization in visually demanding sports such as rhythmic gymnastics. Full article

Background/Objectives: Advances in nanopore sequencing have opened new avenues for studying DNA methylation at single-base resolution, yet their application in epigenetic ageing research remains underdeveloped. Methods: We present a novel framework that leverages the unique capabilities of nanopore sequencing to profile and interpret age-associated methylation patterns in native DNA. Results: Unlike conventional array-based approaches, long reads sequencing captures full CpG context, accommodates diverse and repetitive genomic regions, removes bisulfite conversion steps, and is compatible to the latest reference genome. Conclusions: This work establishes nanopore sequencing as a powerful tool for next-generation epigenetic ageing studies, offering a scalable and biologically rich platform for anti-ageing interventions monitoring and longitudinal ageing studies. Full article