Search Results (1,329)

Background/Objectives: Early experiences can significantly influence brain development, particularly when they occur during specific time windows known as sensitive or critical periods. Therefore, the early promotion of neurodevelopmental functions is crucial in children at risk for neurodevelopmental disabilities, such as those with cerebral palsy. This article introduces AMIRA (A Multidimensional and Integrated Rehabilitation Approach), a rehabilitative framework designed for infants at risk of neurodevelopmental disabilities. Methods: AMIRA is intended to guide clinical–rehabilitation reasoning rather than prescribe a rigid sequence of predetermined activities for the child. The theoretical foundation and structure of AMIRA are presented by formalizing its criteria, objectives, tools, and intervention procedures. The framework comprises four distinct sections, each supported by adaptive strategies to facilitate access to materials and to promote play-based interactions among the child, their environment, and communication partners. Particular attention is given to optimizing both micro- and macro-environments for children with, or at risk of, co-occurring visual impairment. Each rehabilitative section includes three progressive phases: an initial observation phase, a facilitation phase to support the child’s engagement, and an active experimentation phase that gradually introduces more challenging tasks. Results: The intervention pathways in AMIRA are organized according to six core developmental domains: behavioral–emotional self-regulation, visual function, postural–motor skills, praxis, interaction and communication, and cognitive function. These are outlined in structured charts that serve as flexible guidelines rather than prescriptive protocols. Each chart presents activities of increasing complexity aligned with typical developmental milestones up to 24 months of age. For each specific ability, the corresponding habilitation goals, contextual recommendations (including environmental setup, objects, and tools), and suggested activities are provided. Conclusions: This study presents a detailed intervention approach, offering both a practical framework and a structured set of activities for use in rehabilitative settings. Further studies will explore the efficacy of the proposed standardized approach. Full article

Background: Musculoskeletal disorders significantly affect healthcare professionals, particularly physiotherapists, due to the physical demands of their work. The link between physical ailments and psychological distress is especially prominent in clinical settings. Objectives: To assess the prevalence of work-related low back pain (LBP), stress, anxiety, and depression among physiotherapists in Saudi Arabia, and to identify associated local risk factors. Methods: A cross-sectional study using convenience sampling included 710 licensed physiotherapists across Saudi Arabia. Participants completed an online survey containing demographic data and the validated measures, including the Visual Analog Scale (VAS) for pain, the Oswestry Disability Index (ODI), and the Depression, Anxiety, and Stress Scale-21 (DASS-21) for psychological distress. Data were analysed using descriptive statistics, chi-square tests, correlation, and regression analyses. Results: Of 710 responses, 697 were valid; 378 physiotherapists reported work-related LBP. The mean pain intensity was 4.6 (SD = 1.6), with 54.2% experiencing moderate to severe disability. Mental health results showed 49.7% had depressive symptoms and 33.9% experienced some level of anxiety. Significant correlations were observed between disability and psychological distress (anxiety: r = 0.382; depression: r = 0.375; stress: r = 0.406; all p < 0.001). Regression analyses indicated psychological distress significantly predicted disability, with R² values ranging from 0.125 to 0.248, being higher among inpatient physiotherapists. Conclusions: This study reveals a high prevalence of LBP and psychological distress among Saudi physiotherapists, with stress being the strongest predictor of LBP severity. Integrated ergonomic and mental health interventions, including workplace wellness programs and psychological support, are recommended to reduce risks and promote a healthier, more sustainable physiotherapy workforce. Full article

Background/Objectives: Art therapy is a psychotherapeutic technique that involves the creation of tangible visual arts and represents a coping strategy to support children with cancer. Evaluating the effects of such activities on children with cancer is essential for providing evidence of the value that creativity holds within healthcare systems. A dedicated tool for assessing the creative process is the Arts Observational Scale (ArtsObS), focusing on mood and emotional states as key indicators of psychosocial well-being. This study aims to validate a translated version of the ArtsObS in the Italian language. Methods: The translation process followed recommendations for translation and cultural adaptation. The distribution properties of the scores, internal consistency, sensitivity to change, reliability, and convergent validity were assessed through observations conducted by two different evaluators. Results: The ArtsObS in its Italian adaptation is proven to be an adequate tool for capturing changes following an intervention, with good internal consistency and low sensitivity to differences between operators. The analysis supports the reliability of the ArtsObS across different observers. Conclusions: The Italian ArtsObS is a valid and reliable instrument for evaluating the impact of art therapy on pediatric patients’ mood and emotional states. It provides a standardized tool for clinical and research settings to assess creative interventions in pediatric oncology. Full article

This study focuses on surface wind analysis at the small regional airport in Svidnik, used primarily for pilot training under daytime VFR conditions. Due to the complex local terrain and lack of prior meteorological data, an automatic weather station was installed, collecting over 208,000 wind measurements over a two-year period at ten-minute intervals. The dataset was processed using hierarchical filtering and statistical selection, and visualized via wind rose diagrams. The results confirmed a dominant southeastern wind component, supporting the current runway orientation (01/19). However, a less frequent easterly wind direction was identified as a safety concern, causing turbulence near the runway due to terrain and vegetation. This is particularly critical for trainee pilots during final approach and landing. Statistical analysis showed that easterly winds, though less common, appear year-round with a peak in summer. Pearson correlation and linear regression confirmed a significant relationship between the number of easterly wind days and their measurement frequency. Daytime winds were stronger than nighttime, justifying the focus on daylight data. The study provides practical recommendations for training flight safety and highlights the value of localized wind monitoring at small airports. The presented methodology offers a framework for improving operational awareness and reducing risk in complex environments. Full article

Nomadic heritage villages constitute significant material cultural heritage. Under China’s cultural revitalization and rural development strategies, these villages face spatial degradation driven by tourism and urbanization. Current research predominantly employs isolated analytical approaches—space syntax often overlooks social dynamics while social network analysis (SNA) overlooks physical interfaces—hindering the development of holistic solutions for socio-spatial resilience. This study proposes a multi-scale integrated assessment framework combining social network analysis (SNA) and space syntax to systematically evaluate public space structures in traditional nomadic villages of Xinjiang. The framework provides scientific evidence for optimizing public space design in these villages, facilitating harmonious coexistence between spatial functionality and cultural values. Focusing on three heritage villages—representing compact, linear, and dispersed morphologies—the research employs a hierarchical “village-street-node” analytical model to dissect spatial configurations and their socio-functional dynamics. Key findings include the following: Compact villages exhibit high central clustering but excessive concentration, necessitating strategies to enhance network resilience and peripheral connectivity. Linear villages demonstrate weak systemic linkages, requiring “segment-connection point supplementation” interventions to mitigate structural elongation. Dispersed villages maintain moderate network density but face challenges in visual integration and centrality, demanding targeted activation of key intersections to improve regional cohesion. By merging SNA’s social attributes with space syntax’s geometric precision, this framework bridges a methodological gap, offering comprehensive spatial optimization solutions. Practical recommendations include culturally embedded placemaking, adaptive reuse of transitional spaces, and thematic zoning to balance heritage conservation with tourism needs. Analyzing Xinjiang’s unique spatial–social interactions provides innovative insights for sustainable heritage village planning and replicable solutions for comparable global cases. Full article

We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed method combines multi-source data fusion, including hyperspectral and multispectral UAV imagery with ground sensor data, to achieve high-resolution spatial and spectral analysis of soil nutrients. Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). The experimental validation compared the proposed system against two conventional approaches: (1) laboratory soil testing with standardized fertilization recommendations and (2) satellite NDVI-based fertilization. Field trials across three distinct agroecological zones demonstrated that the proposed system reduced fertilizer inputs by 18–27% while increasing crop yields by 4–11%, outperforming both conventional methods. Furthermore, an intelligent fertilization decision model generates tailored fertilization plans by analyzing real-time soil conditions, crop demands, and climate factors, with continuous learning enhancing its precision over time. The system also incorporates GIS-based visualization tools, providing intuitive spatial representations of nutrient distributions and interactive functionalities for detailed insights. Our approach significantly advances precision agriculture by automating the entire workflow from data collection to decision-making, reducing resource waste and optimizing crop yields. The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices. Full article

Background: Airway management in patients with obstructive sleep apnea (OSA) presents unique challenges for anesthesiologists and other airway practitioners. This comprehensive review examines current evidence and clinical practices for managing difficult airways in this high-risk population. OSA is characterized by specific anatomical and physiological alterations that increase both the likelihood of encountering difficult intubation and the risk of rapid desaturation during airway manipulation. Methods: Preoperative assessment of OSA patients requires integration of traditional difficult airway evaluation with OSA-specific considerations, including severity indices, oxygen desaturation patterns, and continuous positive airway pressure dependency. Conventional direct laryngoscopy often proves inadequate in these patients, prompting the development and refinement of alternative approaches. Videolaryngoscopy has emerged as a particularly valuable technique in OSA patients, offering improved glottic visualization while maintaining physiologic positioning. Flexible endoscopic techniques, particularly awake flexible bronchoscopic intubation, remain essential for high-risk scenarios, though they require considerable expertise. Results: Recent technological innovations have produced hybrid devices combining multiple modalities to address the specific challenges presented by OSA patients. Adjunctive tools and techniques, including specialized introducers, exchange catheters, and high-flow nasal oxygen, play critical roles in extending safe apnea time and facilitating successful intubation. Professional society guidelines now incorporate OSA-specific recommendations, emphasizing thorough preparation, appropriate device selection, and comprehensive monitoring. Conclusions: Effective management ultimately requires not only appropriate technology but also systematic preparation, strategic device selection, and meticulous execution. As OSA prevalence continues to rise globally, optimizing airway management approaches for this challenging population remains a critical priority for patient safety. Full article

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic upper airway disease that may involve different inflammatory endotypes, although in Western populations it is most commonly associated with type 2 inflammation. CRSwNP has a significant impact on the patient’s quality of life. The recommended appropriate medical therapy is effective in controlling CRSwNP symptoms in many patients; however, a subset continues to exhibit persistent type 2 inflammation, evidenced by recurrent nasal polyps, elevated eosinophil counts, or the need for systemic corticosteroids or surgery. Monoclonal antibodies have recently become a novel and personalized treatment that can help refractory patients restore disease control. Objective: The present study aims to evaluate the effectiveness of mepolizumab in real-world settings in a diverse patient population, focusing on assessing the impact of this therapy on patient-reported outcomes after six months of treatment. Methods: This is a multicenter, observational study of CRSwNP patients treated with mepolizumab carried out in five hospitals located in Spain. Adult patients with a diagnosis of uncontrolled CRSwNP were included in the study. The change in the nasal polyp score (NPS) was the main clinical endpoint. Changes in the Sinonasal Outcome Test (SNOT-22), nasal congestion and smell impairment visual analogue scale scores, and blood and nasal polyp tissue eosinophil counts were among other endpoints included. Results: In total, 47 patients were included, and 91% were asthmatic. The nasal polyp score (0–8) was reduced significantly in the cohort (mean change: −2.56, p < 0.0001). The mean SNOT-22 score improved 25.29 points. Nasal congestion (−3.57, p < 0.0001) and smell impairment (−4.0, p < 0.0001) visual analog scale scores (0–10) showed a significant improvement. Blood and tissue eosinophil median counts showed significant reductions versus baseline of 86% and 26%, respectively. Among those patients with asthma, the asthma control test score achieved a median value of 24 points. Conclusions: This study provides real-world evidence supporting the effectiveness of mepolizumab in managing CRSwNP in patients with features suggestive of type 2 inflammation. The observed improvements in patient-reported outcomes, nasal polyp burden, and asthma control suggest that mepolizumab may be a valuable therapeutic option for this patient population. Full article

Background/Objectives: This study examines the academic discourse surrounding Critical Incident Stress Debriefing (CISD) and Critical Incident Stress Management (CISM) for first responders using Latent Dirichlet Allocation (LDA) topic modeling. It aims to uncover latent topical structures in the literature and critically evaluate assumptions to identify gaps and limitations. Methods: A corpus of 214 research article abstracts related to CISD/M was gathered from the Web of Science Core Collection. After preprocessing, we used Orange Data Mining software’s LDA tool to analyze the corpus. We tested models ranging from 2 to 10 topics. To guide interpretation and labeling, we evaluated them using log perplexity, topic coherence, and LDAvis visualizations. A four-topic model offered the best balance of detail and interpretability. Results: Four topics emerged: (1) Critical Incident Stress Management in medical and emergency settings, (2) psychological and group-based interventions for PTSD and trauma, (3) peer support and experiences of emergency and military personnel, and (4) mental health interventions for first responders. Key gaps included limited focus on cumulative trauma, insufficient longitudinal research, and variability in procedural adherence affecting outcomes. Conclusions: The findings highlight the need for CISD/M protocols to move beyond event-specific interventions and address cumulative stressors. Recommendations include incorporating holistic, proactive mental health strategies and conducting longitudinal studies to evaluate long-term effectiveness. These insights can help refine CISD/M approaches and enhance their impact on first responders working in high-stress environments. Full article

This paper examines how artificial intelligence (AI) can be strategically deployed to enhance urban planning and environmental livability in Riyadh by generating data-driven, people-centric design interventions. Unlike previous studies that concentrate primarily on visualization, this research proposes an integrative appraisal framework that combines AI-generated design with site-specific environmental data and native vegetation typologies. This study was conducted across key jurisdictional areas including the Northern Ring Road, King Abdullah Road, Al Rabwa, Al-Malaz, Al-Suwaidi, Al-Batha, and King Fahd Road. Using AI tools, urban scenarios were developed to incorporate expanded pedestrian pathways (up to 3.5 m), dedicated bicycle lanes (up to 3.0 m), and ecologically adaptive green buffer zones featuring native drought-resistant species such as Date Palm, Acacia, and Sidr. The quantitative analysis of post-intervention outcomes revealed surface temperature reductions of 3.2–4.5 °C and significant improvements in urban esthetics, walkability, and perceived safety—measured on a five-point Likert scale with 80–100% increases in user satisfaction. Species selection was validated for ecological adaptability, minimal maintenance needs, and compatibility with Riyadh’s sandy soils. This study directly supports the Kingdom of Saudi Arabia’s Vision 2030 by demonstrating how emerging technologies like AI can drive smart, sustainable urban transformation. It aligns with Vision 2030’s urban development goals under the Quality-of-Life Program and environmental sustainability pillar, promoting healthier, more connected cities with elevated livability standards. The research not only delivers practical design recommendations for planners seeking to embed sustainability and digital innovation in Saudi urbanism but also addresses real-world constraints such as budgetary limitations and infrastructure integration. Full article

Permeable pavement is an alternative to conventional impermeable pavement for various applications. However, a common issue with permeable pavement is clogging over time. Permeability is a parameter that reflects the capacity of the pavement to reduce surface runoff; a decline in permeability implies the occurrence of clogging. In this study, permeability data collected on pervious concrete (PC) and JW Eco-Technology (JW) revealed that JW maintained consistent permeability over time. However, PC displayed reduced values, and several locations along the edges had zero permeability, despite no regular vehicular and pedestrian use. Therefore, a portable pressure washer was used to clean the pavements. The cleaning procedure was able to recover the permeability of the areas that showed signs of clogging (0 to 2.69 cm/s) and restore the permeability of PC up to 4.60–5.58 cm/s for corner and center areas, respectively. Moreover, visual inspection using a borescope further revealed the full function of the JW pores (aqueducts), regardless of cleaning. Regardless, it is recommended that periodic cleaning maintenance be performed for both PC and JW using a pressure washer due to its convenience and efficacy, which will be discussed. Full article

Determining the effectiveness of fungicide programs based on cultivar resistance to pathogens, especially late leaf spot (caused by Nothopassalora personata (Berk. & M.A. Curtis) [U. Braun, C. Nakash., Videira & Crous]) is important in establishing recommendations to peanut (Arachis hypogaea L.) farmers. Research was conducted in North Carolina during 2021 and 2022 at three locations to compare the incidence of late leaf spot (e.g., visual estimates of percent of peanut leaflets with lesions), percentage of the peanut canopy defoliated caused by this disease, and yield of the peanut cultivars Bailey II, Emery, and Sullivan when exposed to five fungicide regimens including a non-treated control. Peanut yield was not affected by the interaction of cultivar × fungicide regimens. While differences in leaf spot incidence and canopy defoliation were noted for cultivars, these differences did not translate into differences in peanut yield. All fungicides regimens protected peanut yield from leaf spot disease regardless of the number of sprays during the cropping cycle (e.g., three, four, or five sprays). Peanut yield in the absence of fungicides was 4410 kg/ha compared with a range of 5000 to 5390 kg/ha when fungicides were applied. Peanut yield was greater when fungicides were applied four or five times compared with only three sprays or non-treated peanut. The regimen with five consecutive sprays of chlorothalonil alone for the first and final spray in the regimen and when this fungicide was applied with tebuconazole for the second, third, and fourth sprays was as effective as fungicide regimens including combinations of pydiflumetofen plus azoxystrobin plus benzovindiflupyr, mefentrifluconazole plus pyraclostrobin plus fluxapyroxad, bixafen plus flutriafol, and prothioconazole plus tebuconazole. Full article

This study investigates the spatiotemporal evolution of oil released during the Agia Zoni II shipwreck in the Saronic Gulf in 2017, employing the OpenOil module of the OpenDrift framework. The simulation integrates oceanographic and meteorological data to model the transport, weathering, and fate of spilled oil over a six-day period. Oil behavior is examined across key transformation processes, including dispersion, emulsification, evaporation, and biodegradation, using particle-based modeling and a comprehensive set of environmental inputs. The modeled results are validated against in situ observations and visual inspection data, focusing on four critical dates. The study demonstrates OpenOil’s potential for accurately simulating oil dispersion dynamics in semi-enclosed marine environments and highlights the significance of environmental forcing, vertical mixing, and shoreline interactions in determining oil fate. It concludes with recommendations for improving real-time response strategies in similar spill scenarios. Full article

Objectives: This study aimed to implement a high-resolution Saudi voxel-based anthropomorphic phantom in the OpenMC Monte Carlo (MC) simulation framework. The objective was to evaluate its applicability in radiological simulations, including radiographic imaging and effective dose calculations, tailored to the Saudi population. Methods: A voxel phantom comprising 30 segmented organs/tissues and over 32 million voxels were constructed from full-body computed tomography data and integrated into OpenMC. The implementation involved detailed voxel mapping, material definition using ICRP/ICRU-116 recommendations, and lattice geometry construction. The simulations included X-ray radiography projections using mesh tallies and anterior–posterior effective dose calculations across 20 photon energies (10 keV–1 MeV). The absorbed dose was calculated using OpenMC’s heating tally and converted to an effective dose using tissue weighting factors. Results: The phantom was successfully modeled and visualized in OpenMC, demonstrating accurate anatomical representation. Radiographic projections showed optimal contrast at 70 keV. The effective dose values for 29 organs were calculated and compared with MCNPX, the ICRP-116 reference phantom, and XGBoost-based machine learning (ML) predictions. OpenMC results showed good agreement, with maximum deviations of −35.5% against ICRP-116 at 10 keV. Root mean square error (RMSE) comparisons confirmed reasonable alignment, with OpenMC displaying higher RMSEs relative to other methods due to expanded organ modeling and material definitions. Conclusions: The integration of the Saudi voxel phantom into OpenMC demonstrates its utility for high-resolution dosimetry and radiographic simulations. OpenMC’s Python (version 3.10.14) interface and open-source nature make it a promising tool for radiological research. Future work will focus on combining MC and ML approaches for enhanced predictive dosimetry. Full article

The present study implements novel innovative geostatistical imaging using precision agriculture (PA) under sugarbeet field conditions. Two driplines layout designs (d.l.d.) and soil water content (SWC)–irrigation treatments (A: d.l.d. = 1.00 m driplines spacing × 0.50 m emitters inline spacing; B: d.l.d. = 1.50 m driplines spacing × 0.50 m emitters inline spacing) were applied, with two subfactors of clay loam and clay soils (laboratory soil analysis) for modeling (evaluation of seven models) TDR multi-sensor network measurements. Different sensor calibration methods [method 1(M1) = according to factory; method 2 (M2) = according to Hook and Livingston] were applied for the geospatial two-dimensional (2D) imaging of accurate GIS maps of rootzone soil moisture profiles, soil apparent dielectric Ka profiles, and granular and hydraulic parameters profiles, in multiple soil layers (0–75 cm depth). The modeling results revealed that the best-fitted geostatistical model for soil apparent dielectric Ka was the Gaussian model, while spherical and exponential models were identified to be the most appropriate for kriging modelling, and spatial and temporal imaging was used for accurate profile SWC ${\theta v}_{TDR}$(m³·m⁻³) M1 and M2 maps using TDR sensors. The resulting PA profile map images depict the spatio-temporal soil water and apparent dielectric Ka variability at very high resolutions on a centimeter scale. The best geostatistical validation measures for the PA profile SWC ${\theta v}_{TDR}$ maps obtained were MPE = −0.00248 (m³·m⁻³), RMSE = 0.0395 (m³·m⁻³), MSPE = −0.0288, RMSSE = 2.5424, ASE = 0.0433, Nash–Sutcliffe model efficiency NSE = 0.6229, and MSDR = 0.9937. Based on the results, we recommend d.l.d. A and sensor calibration method 2 for the geospatial 2D imaging of PA GIS maps because these were found to be more accurate, with the lowest statistical and geostatistical errors, and the best validation measures for accurate profile SWC imaging were obtained for clay loam over clay soils. Visualizing sensors’ soil moisture results via geostatistical maps of rootzone profiles have practical implications that assist farmers and scientists in making informed, better and timely environmental irrigation engineering decisions, to save irrigation water, increase water use efficiency and crop production, optimize energy, reduce crop costs, and manage water resources sustainably. Full article