Search Results (1,758)

Background/Objectives: Food waste in school canteens constitutes a significant environmental, organizational, and public health challenge. Despite numerous initiatives aimed at reducing plate waste, limited evidence exists on participatory interventions grounded in coherent theoretical frameworks and implemented in real school settings. This study aimed to evaluate the effects of the Schools Don’t Waste (SDW) program, a participatory, educational, and behavioral intervention based on the Needs-Based, Learner-Centered, Behaviorally Focused (NLB) model, in reducing visually assessed plate waste in primary school canteens. Methods: A quasi-experimental pre-post design without randomization was conducted in 37 public primary schools in Warsaw during the 2024/2025 school year. The intervention consisted of four stages: baseline plate waste assessment (T1), participatory roundtable meetings (T2), implementation of educational and organizational actions (T3), and post-intervention evaluation (T4). Plate waste was assessed using a standardized five-point visual scale. Differences between T1 and T4 were analyzed at the school level using the Wilcoxon signed-rank test. Implementation fidelity and its association with food waste reduction were explored using Spearman correlations. Results: A total of 4988 meals were assessed at baseline and 4080 at follow-up. Significant reductions were observed in the proportion of completely uneaten meals (Δ = −6.10 pp; p < 0.001; r = −0.67), meals with three-quarters uneaten (Δ = −5.76; p < 0.001), and meals with half uneaten (Δ = −7.97; p = 0.002). Overall uneaten meals decreased significantly (p = 0.004). Sixty-two percent of schools demonstrated measurable improvement, although fidelity indicators were not significantly correlated with outcomes. Conclusions: Participatory, low-cost interventions integrating educational and organizational components may effectively reduce plate waste in school settings, while structural and contextual factors appear to moderate intervention effectiveness. Full article

Differentiating life-threatening arrhythmias, such as ventricular tachycardia and supraventricular tachycardia, from non-threatening ones is crucial for clinical applications. This study aimed to develop a deep learning model to classify five key Electrocardiogram (ECG) patterns: normal sinus rhythm, sinus tachycardia, sinus bradycardia, supraventricular tachycardia, and ventricular tachycardia. We collected 1500 single-lead 10 s ECG signals from public datasets, including PhysioNet/Computing in Cardiology (CiC) Challenge 2020 and the Malignant Ventricular Ectopy Database, for training and 2297 ECGs for testing. Each 10 s signal was decomposed into 1 s sliding windows with a 5-point stride, which served as the input for the proposed deep learning architecture utilizing temporal attention and Time2Vec embedding. The model performance achieved an overall accuracy of 95.2%. For the five classes—supraventricular tachycardia, sinus tachycardia, normal sinus rhythm, ventricular tachycardia, and sinus bradycardia—the model achieved sensitivities of 90.3%, 92.9%, 97.4%, 100.0%, and 99.0% and accuracies of 96.3%, 95.8%, 98.9%, 99.9%, and 99.5%, respectively. Specificities for all rhythm categories exceeded 97.4%. This simple and effective single-lead model can significantly support the growing trend of home healthcare and professional clinical decision-making. Full article

In this study, by using four different silicon sources obtained from Konya, Turkey, and its surroundings and employing the sol–gel method, we aim to synthesize silica-based aerogel, characterize it, and improve the use of the innovative building material as a thermal insulator in architectural applications. In this direction, silica aerogel production was carried out using four different starting materials (commercial casting sand, waste casting sand, radiolarite, and quartz) and five different pH values (2–4–6–8–9) by the sol–gel method. The produced silica aerogels were subjected to a surface modification process with Trimethylchlorosilane (TMCS), a modification chemical, and then superhydrophobic silica aerogel powder was obtained. In terms of characterization of the obtained final silica aerogels, XRF, XRD, ICP-OES, density study, FT-IR, BET, FESEM, and contact angle studies were performed. In terms of application of the architectural building material, plasterboard experimental samples were produced using low reinforcement rates (0 wt%, 0.5 wt%, 1 wt%, 2 wt%, and 5 wt%) of silica aerogel. To determine the mechanical and physical properties of the produced silica-aerogel-reinforced plasterboard samples, three-point bend (flexural) strength, compressive strength, thermal conductivity, and water absorption tests were applied. After surface modification, the lowest density value was 0.340 g/cm³, the highest surface area was 311.161 m²/g, and the lowest thermal conductivity coefficient was 0.29 W/mK in silica aerogel material containing radiolarite. In addition to high reinforcement contents in the literature, when it comes to silica aerogel low-reinforcement material and mechanical properties, it can be stated that increasing reinforcement contents negatively affects the mechanical behavior of the material after a certain value. Full article

To meet the strict non-contact measurement requirements for the assembly of aircraft engine pipelines and to overcome the limitations of the traditional three-dimensional laser scanning workflow, this study proposes an automated pipeline point cloud processing and deviation analysis framework. Through a standardized three-dimensional laser scanning procedure, high-resolution pipeline point clouds are obtained and preprocessed. Based on the geometric characteristics of the pipeline, automated algorithms for point cloud feature segmentation, axis extraction, and model registration are developed. Particularly, the three-dimensional extended Douglas–Peucker (DP) algorithm is introduced to achieve efficient point cloud downsampling while retaining necessary geometric and structural features. These algorithms are fully integrated into a unified software platform, supporting one-click operation, and can automatically analyze and obtain five key types of pipeline deviations: angular deviation, radial deviation, axial deviation, roundness error, and diameter error. The platform also provides intuitive visualization effects and comprehensive report generation functions to facilitate quantitative inspection and analysis. Test results show that the proposed method significantly improves the processing efficiency and measurement reliability of complex pipeline systems. The developed framework provides a powerful practical solution for the automated geometric inspection of aircraft engine pipelines and lays a solid foundation for subsequent quality assessment tasks. Full article

Background: Spirometry-based methacholine challenge testing using the provocative dose causing a 20% decline in forced expiratory volume in 1 s (FEV₁, PD₂₀) is a reference method for assessing airway hyperresponsiveness. Impulse oscillometry (IOS), performed during tidal breathing, may capture airway mechanical changes not fully reflected by spirometry. We compared FEV₁- and IOS-based methacholine responsiveness in a large, real-world adult cohort and examined associations with clinical markers and symptoms. Methods: We analyzed 794 consecutively referred adults undergoing standardized methacholine challenge testing with concurrent spirometry and IOS. IOS positivity was defined as a ≥40% increase in resistance at 5 Hz (ΔR₅ ≥ 40%). Agreement between FEV₁–PD₂₀ positivity (PD₂₀ ≤ 1440 µg) and IOS positivity was evaluated using cross-classification and Cohen’s κ. Associations between continuous responses were assessed using Pearson and Spearman correlations. The relationship between ΔR₅ and the probability of a ≥20% decline in FEV₁ was examined using logistic regression. Predictors of ΔR₅ were assessed using multivariable linear regression. Symptom severity was recorded immediately post-challenge using a five-point Likert scale and related to physiological responses. Results: FEV₁–PD₂₀ classified 37.5% of participants as hyperresponsive, whereas IOS positivity (ΔR₅ ≥ 40%) classified 70.6%. Agreement between methods was limited (κ = 0.09; p < 0.01). ΔFEV₁ and ΔR₅ were weakly correlated (r = −0.287; ρ = −0.306; both p < 0.001; R² = 0.08). A 20% decline in FEV₁ corresponded on average to a 74% increase in R₅, whereas ΔR₅ ≥ 40% corresponded to an average FEV₁ decline of 7.6%. In multivariable models, referral diagnosis group and age independently predicted ΔR₅, whereas FeNO and baseline FEV₁% predicted did not. Baseline FEV₁% predicted modified the ΔFEV₁–ΔR₅ slope (interaction β = −0.0317; p = 0.0028). Post-challenge symptom (5-point Likert) related to MCT was associated with both ΔFEV₁ and IOS responses; ΔFEV₁ showed a stronger linear association with symptoms, whereas IOS measures showed larger stepwise differences across symptom categories. Conclusions: IOS identifies a larger, partly distinct subset of methacholine-responsive individuals compared with conventional FEV₁–PD₂₀ criteria and detects mechanical changes at lower levels of spirometric impairment. Despite limited concordance, IOS provides complementary physiological and symptom-relevant information when used alongside spirometry. Standardized IOS response definitions and prospective validation are needed to establish clinical utility. Full article

This research investigates the shear performance of sustainable self-compacting reinforced geopolymer concrete (GPC) beams incorporating granite waste powder (GWP) and ground granulated blast-furnace slag (GGBFS) as eco-friendly binding agents through experimental and numerical analyses. Five geopolymer reinforced concrete beam specimens (100 mm × 150 mm × 1500 mm) were tested under two-point loading conditions to evaluate the influence of longitudinal reinforcement ratio (0.85% to 2.0%) and shear span-to-effective depth ratio on the structural shear performance. The experimental investigation revealed that geopolymer reinforced concrete beams exhibit shear behavior characteristics similar to conventional Portland cement concrete beams, with the 2.0% reinforcement ratio achieving 18.3% higher shear strength compared to the 0.85% reinforcement ratio, while shear capacity increased proportionally with increasing shear span-to-depth ratio. Experimental data, including load–displacement response, shear strength measurements, strain distributions, failure modes, and crack patterns, were studied. Finite element nonlinear analysis was conducted by modifying the concrete modulus and stress–strain relationships to reflect the properties of geopolymer concrete using ABAQUS software integrated with the concrete damaged plasticity model. The results demonstrated that for the tested geopolymer reinforced concrete beams, first cracking load, steel yielding load, and ultimate load capacity increased systematically with increasing tension steel reinforcement ratio and proportionally with higher shear span-to-depth ratios. Full article

This article presents a simple and understandable approach to the automatic assessment of the severity of late blight on tomato leaves. We collect our own dataset of 5245 RGB images of healthy and diseased tomato leaves and determine five ordinal classes: healthy (0%) and four infection levels (0.1–10%, 11–25%, 26–50%, and ≥51% of the affected area). Each image is segmented using the global definition of the Otsu threshold, followed by morphological purification, after which seven textural and geometric characteristics are extracted from the contours of the lesion: contrast, number of contours, average and standard deviation of the contour area, average and standard deviation of the contour perimeter, and average area-to-perimeter ratio. All characteristics are normalized and used as input data for the XGBoost classifier. The dataset is randomly split into 80% training and 20% test images, resulting in an independent test set of 1049 images. In this test set, the proposed model provides an overall accuracy of 0.93 and an F1 macro score of 0.93 points, while for each F1 class, it varies from 0.90 to 0.97. The confusion matrix shows a stable difference between neighboring severity levels, while the analysis of the importance of the features confirms the relevance of contour descriptors for characterizing the size and shape of the lesion. This method only runs on a central processor, requires a small amount of memory, and outputs interpretable output data, making it suitable for use in greenhouses and farms with limited computing resources. We also discuss the limitations associated with the boundaries between neighboring classes and the potential shift in the subject area, and we outline directions for expanding the approach to multi-sheet scenes and explicit ordinal loss functions. Full article

Background/Objectives: Digitalization of medical knowledge has improved access to information but also increased the spread of imprecise content. Repeated exposure to incorrect descriptions may lead to their normalization over time. This is particularly evident for the Hornblower sign, which is frequently conflated with the Patte test in the literature, online sources, and large language model outputs. This study systematically evaluates these descriptions and quantifies related inaccuracies. Methods: A three-step approach was applied to answer the question “What is the Hornblower sign?”. First, primary publications referring to the original description by Arthuis were analyzed. Second, the first 35 Google search results were systematically reviewed. Third, responses from five widely used LLMs (ChatGPT 5.1, Grok 4.1, Gemini 3 Pro, Perplexity, and DeepSeek-R1) were evaluated. All descriptions were assessed using a standardized 4-point scoring system (0–3 points) capturing content accuracy and correct differentiation between the Hornblower sign and the Patte test. Results: Fourteen original publications were included, yielding a mean score of 2.07. Correct descriptions were found in 50%, while 43% described only the Patte test. Among 34 evaluable Google search results, the mean score was 1.17, with 77% scoring ≤ 1 point. The five LLMs achieved a mean score of 1.8, demonstrating substantial variability and overall incomplete conceptual accuracy. Conclusions: Descriptions of the Hornblower sign show substantial heterogeneity and frequent inaccuracies across the scientific literature, online sources, and LLM outputs. Conflation with the Patte test undermines diagnostic reliability and limits study comparability. Critical source appraisal and adherence to original test descriptions are essential to maintain clinical and scientific rigor. Full article

Background: In Pakistan, the number of Human immunodeficiency virus (HIV) cases is increasing significantly, attributed to risk factors such as injection drug use, sexual transmission, etc. However, transmission through hemodialysis units is not well documented. In 2024, an outbreak of HIV cases in Multan, Pakistan, drew alarm from local health authorities due to reports linking it to a large public hospital in South Punjab. Here, we report the molecular epidemiological investigation of the outbreak. Methods: Twenty-five hemodialysis patients identified during the outbreak were enrolled. Blood samples were subjected to DNA extraction and polymerase chain reaction (PCR) amplification. Phylogenetic analysis was conducted using the maximum-likelihood approach in IQ-TREE. For dating phylogenetics, a maximum clade credibility tree (MCC) was constructed using the BEAST tool. The MCC tree was constructed using the Bayesian Skyline model with an uncorrelated lognormal relaxed clock. The VESPA program was used to identify amino acid signatures unique to outbreak sequences compared with Pakistani reference sequences. Results: A total of 25 patients (identified as part of the HIV outbreak) were enrolled. 96% (24 out of 25) also tested positive for Hepatitis C, while none tested positive for Hepatitis B. The age range of patients in the study was 23 to 72 years (median age: 44.88 years). In terms of gender distribution, 13 out of 25 were male. All the sequences were identified as HIV subtype CRF02_AG. Phylogenetic analysis revealed that Multan sequences formed a well-supported monophyletic cluster, indicating shared recent origin. Signature pattern analysis identified a unique molecular fingerprint at 26 nucleotide positions, whereas molecular dating placed the emergence of the cluster between 2023 and 2024, consistent with the outbreak timing. Conclusions: Findings provide biologically plausible evidence of a point-source HIV outbreak linked to lapses in infection prevention and control practices at the hemodialysis unit. Full article

Background: This study aimed to investigate the biomechanical behavior of conservative inlay restorations fabricated from different CAD/CAM materials by combining experimental flexural strength testing with finite element analysis. Methods: Five CAD/CAM materials were evaluated: feldspathic ceramic (Cerec Blocs), leucite-reinforced ceramic (IPS Empress CAD), resin nano-ceramic (Lava Ultimate), polymer-infiltrated ceramic network (VITA Enamic), and lithium disilicate ceramic (IPS e.max CAD). Young’s modulus and Poisson’s ratio were experimentally determined using three-point bending and nanoindentation tests and used as inputs for 3D FEA. Von Mises (VM) stress distributions within the inlays were analyzed under simulated occlusal loading. Results: Maximum VM stresses showed an inverse relationship with material elasticity. IPS e.max CAD exhibited the highest maximum VM stress (45.571 MPa), whereas the resin nano-ceramic showed the lowest (25.419 MPa). Despite higher stress concentrations in high-modulus ceramics, VM values for all materials remained well below their FS limits. Conclusions: All materials demonstrated adequate mechanical stability under physiological loading. Lithium disilicate showed a comparatively larger margin between stress levels and flexural strength, while lower-modulus materials tended to promote greater stress transfer to supporting structures. Full article

Background: Aflibercept is one of the anti-VEGF drugs used, among others, for the treatment of retinopathy of prematurity, alongside the widely used bevacizuab and ranibizumab. It is a recombinant fusion protein composed of the human VEGFR-1 and VEGFR-2 domains combined with the Fc part of human IgG, called VEGF-TRAP. The paper describes a group of premature infants treated with aflibercept due to retinopathy of prematurity at the Regional Specialized Children’s Hospital in Olsztyn, Poland, in the years 2017–2019. Methods: Eleven children (22 eyes) with extremely low birth weight and type 1 ROP and A-ROP qualified for treatment. The birth weight of the children was 460–940 g (average 677 g). Children were treated between 32 and 38 weeks of postconceptional age (on average in 33.3 week). We administered 1 mg (0.025 mL) of aflibercept intravitreal to each eye under local anesthesia. Results: In all cases, the retinopathy regressed. Between 2 and 7 weeks after treatment, the disease reactivated in five children (45%) in the form of ROP type 2, and these children underwent retinal laser photocoagulation. One child had a complication in the form of a cataract in one eye, while the remaining children had no complications after the injection and laser therapy. In all children, there was complete regression of ROP, and retinal vascularization was observed up to the end of zone III or up to the border of laser therapy. A child with cataract underwent lensectomy. All children are under the care of our center, and were examined ophthalmologically and strabologically; the results of these tests will be presented in a separate study. Conclusions: Aflibercept differs from other anti-VEGF drugs in its point of action and pharmacodynamics of action. In the literature, its effectiveness is estimated at over 80%, but there are also studies in which the reactivation of ROP after treatment reaches over 40%. In this study, the treated children were characterized by extremely low birth weight and, as a result, numerous complications related to prematurity occurred, such as bronchopulmonary dysplasia, sepsis, anemia, heart defects, and others. Many of them were in the intensive care unit. These factors may influence ROP reactivation and complications. The description compares studies in which aflibercept was administered at the same dose—1 mg. Currently, large studies (e.g., Firefleye and Butterfleye) describe the effects of a new aflibercept therapy at a dose of 0.4 mg. Studies on aflibercept obviously require further observations, so all reports, even from small groups, are important. Full article

Small islands in developing countries often face infrastructural limitations, environmental fragility, and heavy economic dependence on tourism, making smart and sustainable innovation crucial. This study investigates what international tourists value in a destination to perceive it as a “smart island,” applying the smart city paradigm to the context of small island developing countries. A structured survey was conducted with 420 international tourists from diverse nationalities, using a five-point Likert scale to assess the importance of smart tourism attributes. Descriptive statistics, Pearson correlations, t-tests, and regression analyses were performed to identify significant predictors of overall satisfaction with smart tourism experiences. This study provides empirical evidence that international tourists primarily perceive destination smartness through core digital and infrastructural features rather than advanced technological sophistication. Real-time information systems emerged as the strongest predictor of perceived smartness, followed by free Wi-Fi access, sustainability-related technologies, and smart transport systems. The findings further reveal that demographic and cultural factors influence technology preferences, while immersive tools such as augmented reality play a secondary role. Overall, the results indicate that, in Small Island Developing Countries, smart tourism should be understood as a strategic approach to improving accessibility, connectivity, sustainability, and destination resilience rather than merely adopting high-end technologies. Full article

In agriculture, soil amendments like compost, manure, superabsorbent polymers (SAP) and biochar (BC) are already in use to mitigate the effects of water shortage and to obtain a higher yield and survivability. The present study focuses on the impact of BC and SAP under moderate and reduced soil water content (SWC) on the physiological and biochemical response of Chenopodium quinoa Willd. (cv. UDEC-5), a naturally drought-resistant and strategic crop in arid regions, with the aim of further improving its resilience and biomass production. Plants were grown in the presence or absence (control) of SAP (1% or 0.1% g/100 g SAP) or BC (3% g/100 g BC) by taking into account the smallest possible amount of irrigation necessary for optimal growth of the control. Sixty-five days after sowing, the reduced watering approaches started. The irrigation amount was reduced slowly until plants without any amendment showed a significant reduction in CO₂/H₂O gas exchange and further significant changes in 23 morphological, physiological and biochemical symptoms of water shortage. Each amendment already caused individual plant response in wet conditions: The soil amendments of SAP (1% and 0.1%) and BC had no significant effect on biomass production but caused changes in PS I (portion of oxidized and open centers in PS I), the C/N ratio and N content. The addition of SAP (0.1% and 1%) led to a decrease in gH⁺, ECStmAu ^× gH⁺, R_D, R_L, the C_i/C_atm ratio and ETR/A_gross ratio and to an increase in water use efficiency (WUE), especially in the 0.1% SAP treatment. In moderate conditions, 0.1% SAP and 3% BC caused a significant increase in both the LOP and C/N ratio. In the moderate treatments, the application of 0.1% SAP promoted an increased A_net, while 3% BC promoted a significant reduction in malondialdehyde (MDA). The results of the present quinoa experiment indicate the drought avoidance mechanism of the control under low SWC. The reduced transpiration led to increased WUE due to the efficient use of the substomatal CO₂ reservoir under low C_s and low E. It could also be confirmed that quinoa plants balanced low soil water potential by the accumulation of compatible solutes to lower the LWP and LOP. Drought led, especially in leaves in the 1% SAP treatment, to significant reductions in CO₂/H₂O gas exchange (A_net, R_D), decreases in Y (II) and ETR in PS II, and an increase in the ETR/A ratio and over-reduced centers in PS I, pointing to an increased appearance of reactive oxygen species (ROS) in the chloroplasts. The latter change was indicated by higher levels of lipid peroxidation (MDA). It could be shown that the response of the test species Chenopodium quinoa to the addition of BC and SAP proved to be highly adaptable. The plant reacted in a very coordinated and specific way to both the danger of oversupply of SAP soil amendments under water shortage conditions and an effective adaptation to a limited water supply with 3% BC and 0.1% SAP by increasing WUE and proline content. However, BC also had a mitigating effect on the level of reactive oxygen species (ROS). It can be assumed that this effect is based on a more plant-compatible, less one-sided ion composition of BC. The results presented indicate that SAP and BC can have an impact on the water and nutrient accessibility for plants. Therefore, optimal biomass production and plant response can only be reached if plant soil interactions and competition between SAP, BC and the plant roots are taken into account when planning for climate-resilient, water-saving agriculture. Full article

The paper presents the development of a correlation model for initial tensile elastic modulus for flexible polymers as a function of Shore hardness in OO and A scale based on measurement. Measured polymers are in groups of silicone rubber, nitrile butadiene rubber (NBR), thermoplastic polyurethane (TPU) and silicone. The model is composed of piecewise exponential functions with fixed coefficients chosen to minimize the S₂ error norm and absolute value of relative error at the measured data points. Every chosen section of the hardness scale has one exponential function correlating the hardness to tensile elastic modulus with the argument in the form of a polynomial up to the fourth degree. The coefficients for the polynomial arguments were determined by enforcing interpolation conditions in a chosen set of points in the logarithmic scale for the elastic modulus. The correlation model possesses C0 continuity. For each material, five specimens were used for hardness measurements and five for the elastic modulus testing. The correlation model gives a positive value for elastic modulus of 0 for hardness, and a “finite”, “reasonable” value of 100 for hardness and is monotonic. Tensile properties were evaluated using true stress and logarithmic (Hencky) strain, with iterative correction of the changing cross-sectional area to account for large strain. The maximum relative error achieved in the correlation model for the OO scale is 13.4%, while for the A scale it is 7%. The developed model provides a practical and rapid method for estimating the initial tensile elastic modulus from non-destructive hardness measurements and is particularly useful in industrial applications and in the development of material models for dental surgery simulations. Full article

Against the backdrop of China’s dual carbon goals, understanding how terrain complexity affects the decoupling linkage between infrastructure investment and carbon emissions is crucial for developing differentiated low-carbon strategies. This study focuses on Sichuan Province, a region characterized by significant topographical heterogeneity, to investigate how terrain constraints influence carbon emission decoupling. We construct a Terrain Constraint Index (TCI) using three indicators (Digital Elevation Model (DEM), Coefficient of Variation of elevation (CV), and Terrain Position Index (TPI)) weighted by a game theory-based combination of entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) methods and employ the Tapio decoupling model combined with group comparison analysis to examine the correlation between terrain complexity and decoupling performance. The key findings are as follows. (1) The TCI exhibits a “high in the west, low in the east” spatial pattern, ranging from 0.151 (Zigong) to 0.591 (Ya’an), with five distinct terrain complexity levels identified. (2) During 2001–2021, good decoupling states (strong + weak decoupling) accounted for 76.8% of all observations, indicating overall improvement in carbon emission efficiency. (3) A monotonic negative association is observed between terrain complexity and decoupling performance: the good decoupling ratio decreases from 82.5% in Low TCI regions to 62.5% in Very High TCI regions, with Mann–Whitney tests showing suggestive differences (raw p < 0.05, though not significant after Bonferroni correction). (4) Average decoupling elasticity increases from 0.182 in Very Low TCI regions to 0.705 in Very High TCI regions, demonstrating that higher terrain complexity is associated with worse decoupling outcomes. (5) Geodetector analysis reveals that infrastructure investment has the highest explanatory power (q = 0.401, p < 0.01), and the interaction between terrain factors and investment shows significant nonlinear enhancement effects (q = 0.544–0.830). These findings suggest that terrain complexity is associated with worse carbon emission decoupling, plausibly through affecting infrastructure investment efficiency, and point to the need for differentiated low-carbon strategies for regions with varying topographical conditions. Full article