Search Results (2,526)

Anthocyanins, a subclass of flavonoid pigments, impart vivid red, purple, and blue coloration to horticultural plants, playing essential roles in ornamental enhancement, stress resistance, and pollinator attraction. Recent studies have identified B-box (BBX) proteins as a critical class of transcription factors (TFs) involved in anthocyanin biosynthesis. Despite these advances, comprehensive reviews systematically addressing BBX proteins are urgently needed, especially given the complexity and diversity of their roles in regulating anthocyanin production. In this paper, we provide an in-depth overview of the fundamental structures, biological functions, and classification of BBX TFs, along with a detailed description of anthocyanin biosynthetic pathways and bioactivities. Furthermore, we emphasize the diverse molecular mechanisms through which BBX TFs regulate anthocyanin accumulation, including direct activation or repression of target genes, indirect modulation via interacting protein complexes, and co-regulation with other transcriptional regulators. Additionally, we summarize the known upstream regulatory signals and downstream target genes of BBX TFs, highlighting their significance in shaping anthocyanin biosynthesis pathways. Understanding these regulatory networks mediated by BBX proteins will not only advance fundamental horticultural science but also provide valuable insights for enhancing the aesthetic quality, nutritional benefits, and stress adaptability of horticultural crops. Full article

The parameter identification of Autonomous Underwater Vehicles (AUVs) serves as a fundamental basis for achieving high-precision motion control, state monitoring, and system development. Currently, AUV parameter identification typically relies on the complete motion information obtained from onboard sensors. However, in practical applications, it is often challenging to accurately measure key state variables such as velocity and angular velocity, resulting in incomplete measurement data that compromises identification accuracy and model reliability. This issue is particularly pronounced in vertical motion tasks involving low-speed, large pitch angles, and highly maneuverable conditions, where the strong coupling and nonlinear characteristics of underwater vehicles become more significant. Traditional hydrodynamic models based on full-state measurements often suffer from limited descriptive capability and difficulties in parameter estimation under such conditions. To address these challenges, this study investigates a parameter identification method for AUVs operating under vertical, large-amplitude maneuvers with constrained measurement information. A control autoregressive (CAR) model-based identification approach is derived, which requires only pitch angle, vertical velocity, and vertical position data, thereby reducing the dependence on complete state observations. To overcome the limitations of the conventional Recursive Least Squares (RLS) algorithm—namely, its slow convergence and low accuracy under rapidly changing conditions—a Multi-Innovation Least Squares (MILS) algorithm is proposed to enable the efficient estimation of nonlinear hydrodynamic characteristics in complex dynamic environments. The simulation and experimental results validate the effectiveness of the proposed method, demonstrating high identification accuracy and robustness in scenarios involving large pitch angles and rapid maneuvering. The results confirm that the combined use of the CAR model and MILS algorithm significantly enhances model adaptability and accuracy, providing a solid data foundation and theoretical support for the design of AUV control systems in complex operational environments. Full article

Introduction: Despite clinical evidence for efficacy, there has been minimal uptake of transcranial direct current stimulation (tDCS) for musculoskeletal conditions. Thus, our objective was to explore the perceptions and experiences of people living with lower-limb musculoskeletal injury as well as healthy physically active populations and relate this to the usage of tDCS and key aspects of tDCS design that would improve the capacity for implementation. Methods: We conducted a qualitative descriptive study of 16 participants (44% women) using semi-structured focus groups to identify the descriptions and experiences of people living with lower-limb musculoskeletal injury and healthy physically active populations. A thematic template was used to create a coding structure. Codes were then grouped, and key themes were derived from the data. Results: Four primary themes were identified from focus groups. These were (i) the impact of musculoskeletal injuries on health and quality of life, (ii) performance and injury recovery as facilitators to using tDCS, (iii) barriers and facilitators to tCDS application and (iv) design and aesthetic factors for a tDCS device. Discussion: Our qualitative descriptive study identified four themes relevant to the successful implementation of tDCS into rehabilitative and performance practice. To increase the likelihood of successful tDCS implementation, these barriers should be addressed and facilitators promoted. This should include innovative approaches to device application and structure that allow for a stylish, user-friendly design. Full article

Rough sets and fuzzy sets are two complementary approaches for modeling uncertainty and imprecision. Their integration enables a more comprehensive representation of complex, uncertain systems. However, existing rough fuzzy sets models lack the expressive power to fully capture the interactions among structural uncertainty, cognitive hesitation, and multi-level granular information. To address these limitations, we achieve the following: (1) We propose intuitionistic fuzzy covering rough membership and non-membership degrees based on maximal description and construct a new single-granulation model that more effectively captures both the structural relationships among elements and the semantics of fuzzy information. (2) We further extend the model to a multi-granulation framework by defining optimistic and pessimistic approximation operators and analyzing their properties. Additionally, we propose a neutral multi-granulation covering rough intuitionistic fuzzy sets based on aggregated membership and non-membership degrees. Compared with single-granulation models, the multi-granulation models integrate multiple levels of information, allowing for more fine-grained and robust representations of uncertainty. Finally, a case study on real estate investment was conducted to validate the effectiveness of the proposed models. The results show that our models can more precisely represent uncertainty and granularity in complex data, providing a flexible tool for knowledge representation in decision-making scenarios. Full article

The present study aimed to provide Congolese refugee women with an opportunity to narrate firsthand experiences coping with resettlement challenges in the United States. Translator-assisted, face-to-face semi-structured individual interviews were conducted with newly resettled Congolese refugee women (n = 20) aged 18 and older who arrived in the United States between 2011 and 2018. All participants were receiving assistance from a resettlement agency, located in the Midwestern US, at the time of the study. Data were analyzed using descriptive coding and thematic analysis. Three overarching themes were developed, indicating that Congolese refugee women adopt three main coping mechanisms to deal with challenges they face after resettling in the United States: (1) use of social support, (2) acceptance of the situation, and (3) spirituality. Resettlement support services, such as those provided by resettlement agencies, mental health providers, and community-based organizations, should integrate both economic and cultural dimensions into their services to address the complex physiological, mental, and emotional impacts of resettlement. These services should prioritize culturally and spiritually sensitive techniques that are linguistically accessible. Full article

Background: Lung cancer ranks as the leading cause of cancer-related mortality worldwide. The complexity of tumor delineation, crucial for radiation therapy, requires expertise often unavailable in resource-limited settings. Artificial Intelligence (AI), particularly with advancements in deep learning (DL) and natural language processing (NLP), offers potential solutions yet is challenged by high false positive rates. Purpose: The Oncology Contouring Copilot (OCC) system is developed to leverage oncologist expertise for precise tumor contouring using textual descriptions, aiming to increase the efficiency of oncological workflows by combining the strengths of AI with human oversight. Methods: Our OCC system initially identifies nodule candidates from CT scans. Employing Language Vision Models (LVMs) like GPT-4V, OCC then effectively reduces false positives with clinical descriptive texts, merging textual and visual data to automate tumor delineation, designed to elevate the quality of oncology care by incorporating knowledge from experienced domain experts. Results: The deployment of the OCC system resulted in a 35.0% reduction in the false discovery rate, a 72.4% decrease in false positives per scan, and an F1-score of 0.652 across our dataset for unbiased evaluation. Conclusions: OCC represents a significant advance in oncology care, particularly through the use of the latest LVMs, improving contouring results by (1) streamlining oncology treatment workflows by optimizing tumor delineation and reducing manual processes; (2) offering a scalable and intuitive framework to reduce false positives in radiotherapy planning using LVMs; (3) introducing novel medical language vision prompt techniques to minimize LVM hallucinations with ablation study; and (4) conducting a comparative analysis of LVMs, highlighting their potential in addressing medical language vision challenges. Full article

Background/Objectives: Agricultural workers in Spain with a migratory background face challenging working and living conditions that significantly affect their health. This study aimed to explore how professionals in healthcare, social services, civil society organisations, and labour institutions perceive that the working conditions affect the physical health of this population. Methods: A qualitative descriptive study was conducted through 92 semi-structured interviews with professionals from six provinces in Spain. Data were analysed using thematic analysis following Braun and Clarke’s six-phase framework. Rigour was ensured through triangulation, independent coding, and interdisciplinary consensus. Results: Two overarching themes were identified: (1) the health consequences of workplace demands and environmental hazards, and (2) navigating health services such as sick leave and disability permits. These findings highlight how the impact of precarious working conditions and limited access to healthcare affect the physical health of migrant agricultural workers. Conclusions: The professionals interviewed described and relate precarious working conditions with adverse health outcomes among migrant agricultural workers. Their insights reveal the need for systemic reforms to enforce labour rights, ensure access to health services, and address the structural factors that contribute to exclusion and vulnerability. Full article

Background/Objectives: Understanding the impact of dietary habits in terms of obesity, health outcomes, and functional decline is critical in Europe’s growing elderly population. This study analyzed trends in Mediterranean diet (MD) adherence, obesity prevalence, and grip strength among middle-aged and elderly Europeans using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). Methods: Data from four SHARE waves (2015–2022) across 28 countries were analyzed. Dietary patterns were assessed through food frequency questionnaires classifying participants as MD-adherent or non-adherent where adherent implies daily consumption of fruits and vegetables and occasional (3–6 times/week) intake of eggs, beans, legumes, meat, fish, or poultry (an unvalidated definition of the MD pattern). Handgrip strength, a biomarker of functional capacity, was categorized into low, medium, and high groups. Body mass index (BMI), self-perceived health (SPHUS), chronic disease prevalence, and CASP-12 scores (control, autonomy, self-realization, and pleasure evaluated on the 12-item version) were also evaluated. Statistical analyses included descriptive methods, logistic regressions, and multiple imputations to address missing data. Results: A significant majority (74–77%) consumed fruits and vegetables daily, which is consistent with MD principles; however, the high daily intake of dairy products (>50%) indicates limited adherence to the MD, which advocates for moderate consumption of dairy products. Logistic regression indicated that individuals with two or more chronic diseases were more likely to follow the MD (odds ratio [OR] = 1.21, confidence interval [CI] = 1.11–1.32), as were those individuals who rated their SPHUS as very good/excellent ([OR] = 1.42, [CI] = 1.20–1.69). Medium and high maximal handgrip were also strongly and consistently associated with higher odds of MD adherence (Medium: [OR] = 1.44, [CI] = 1.18–1.74; High: [OR] = 1.27, [CI] = 1.10–1.48). Conclusions: The findings suggest that middle-aged and older adults are more likely to adhere to the MD dietary pattern if they have more than two chronic diseases, are physically active, and have a medium or high handgrip. Although an unvalidated definition of the MD dietary pattern was used, the results highlight the importance of implementing targeted dietary strategies for middle-aged and elderly adults. Full article

Introduction: Congestive heart failure (CHF), a complex clinical syndrome characterized by the heart’s inability to pump blood effectively due to structural or functional impairments, is a growing public health concern, with profound implications for patients’ physical and emotional well-being. In India, the burden of CHF is rising due to aging demographics and increasing prevalence of lifestyle-related risk factors. Among the subtypes of CHF, heart failure with preserved ejection fraction (HFpEF), i.e., heart failure with left ventricular ejection fraction of ≥50% with evidence of spontaneous or provokable increased left ventricular filling pressure, and heart failure with reduced ejection fraction (HFrEF), i.e., heart failure with left ventricular ejection fraction of 40% or less and is accompanied by progressive left ventricular dilatation and adverse cardiac remodeling, may present differing impacts on health-related quality of life (HRQoL), i.e., an individual’s or a group’s perceived physical and mental health over time, yet comparative data remains limited. This study assesses HRQoL among CHF patients using the Minnesota Living with Heart Failure Questionnaire (MLHFQ), one of the most widely used health-related quality of life questionnaires for patients with heart failure based on physical and emotional dimensions and identifies sociodemographic and clinical variables influencing these outcomes. Methods: A cross-sectional analytical study was conducted among 233 CHF patients receiving inpatient and outpatient care at the Department of Cardiology at a quaternary care teaching hospital in coastal Karnataka in India. Participants were enrolled using convenience sampling. HRQoL was evaluated through the MLHFQ, while sociodemographic and clinical characteristics were recorded via a structured proforma. Statistical analyses included descriptive measures, independent t-test, Spearman’s correlation and stepwise multivariable linear regression to identify associations and predictors. Results: The mean HRQoL score was 56.5 ± 6.05, reflecting a moderate to high symptom burden. Patients with HFpEF reported significantly worse HRQoL (mean score: 61.4 ± 3.94) than those with HFrEF (52.9 ± 4.64; p < 0.001, Cohen’s d = 1.95). A significant positive correlation was observed between HRQoL scores and age (r = 0.428; p < 0.001), indicating that older individuals experienced a higher burden of symptoms. HRQoL also varied significantly across NYHA functional classes (χ² = 69.9, p < 0.001, ε² = 0.301) and employment groups (χ² = 17.0, p < 0.001), with further differences noted by education level, gender and marital status (p < 0.05). Multivariable linear regression identified age (B = 0.311, p < 0.001) and gender (B = –4.591, p < 0.001) as significant predictors of poorer HRQoL. Discussion: The findings indicate that patients with HFpEF experience significantly poorer HRQoL than those with HFrEF. Older adults and female patients reported greater symptom burden, underscoring the importance of demographic-sensitive care approaches. These results highlight the need for routine integration of HRQoL assessment into clinical practice and the development of comprehensive, personalized interventions addressing both physical and emotional health dimensions, especially for vulnerable subgroups. Conclusions: CHF patients, especially those with HFpEF, face reduced HRQoL. Key factors include age, gender, education, employment, marital status, and NYHA class, underscoring the need for patient-centered care. Full article

Background: This study aims to compare the logistical challenges of Home Health Care (HHC) services in Portugal and Brazil, highlighting the structural and operational differences between both systems. Methods: Guided by an abductive research approach, data were collected using a semi-structured survey with open-ended questions, applied to 13 HHC teams in Portugal and 18 in Brazil, selected based on national coordination recommendations. The data collection process was conducted in person, and responses were analyzed using descriptive statistics and qualitative content analysis. Results: The results reveal that Portugal demonstrates higher productivity, stronger territorial coverage, and a more integrated inventory management system, while Brazil presents greater multidisciplinary team integration, more flexible fleet logistics, and more advanced digital health records. Despite these strengths, both countries continue to address key logistical aspects, such as scheduling, supply distribution, and data management, largely through empirical strategies. Conclusions: This research contributes to the theoretical understanding of international HHC logistics by emphasizing strategic and systemic aspects often overlooked in operational studies. In practical terms, it offers insights for public health managers to improve resource allocation, fleet coordination, and digital integration in aging societies. Full article

Background: Upper-limb impairment is a major cause of post-stroke disability, limiting participation in meaningful activities. Robotic rehabilitation may address this by delivering high-dosage, task-oriented training while reducing clinician workload. However, limited clinical translation of robotic interventions may be partly due to poor reporting in the literature. This systematic review evaluated the intervention-reporting quality (completeness and consistency) of randomized controlled trials (RCTs) comparing robotic and conventional upper-limb stroke rehabilitation. Methods: Four databases were searched for RCTs investigating robotic upper-limb interventions compared with dose-matched conventional interventions for people with stroke. Intervention reporting was assessed using the TIDieR-Rehab checklist. Trained reviewers independently extracted and evaluated data, resolving discrepancies through consensus. Completeness and consistency were analyzed descriptively. Results: Among 25 RCTs, the overall reporting completeness was low (43%). Robotic interventions were better described (50%) than conventional interventions (36%). While timing and total dose were commonly reported, critical details on provider expertise, active dose, progressive challenge, personalization, and harms were often omitted. Reporting consistency was moderate (68%), with key information dispersed across article sections. Conclusions: Inadequate reporting limits the transparency, replication, and implementation of robotic upper-limb interventions. Adopting structured reporting frameworks like TIDieR-Rehab is essential for advancing the field. Full article

At the Politecnica Salesiana University (UPS) in Guayaquil, Ecuador, urban mobility challenges were addressed with the aim of improving students’ quality of life and promoting sustainability. This study evaluated the technical, economic, and social feasibility of implementing a shared transportation (carpooling) system using a quantitative-descriptive approach. Surveys were applied to a stratified sample of 256 students to analyze transportation habits. Route planning was performed using ArcGIS software, and costs were calculated with Microsoft Excel. Social impact assessment involved focus groups and analysis of variables such as changes in mobility patterns, system acceptance, and perceived safety, comfort, and accessibility. Key indicators included the percentage of students willing to participate in the pilot (82.7%), satisfaction with travel time savings (85.7% fully satisfied), and positive perceptions of safety and comfort. The results suggest that the proposed system is not only economically viable but also widely accepted by students, contributing to reduced stress, travel time, and single-occupancy vehicle use. This study demonstrates the feasibility of shared transport in urban universities and provides a replicable model to guide sustainable mobility policies that improve safety, comfort, and efficiency in student commuting. Full article

Despite the importance of financial literacy, particularly in sustaining and improving rural agriculture, it is documented in the literature that little is known about financial literacy, particularly in rural communities in developing countries. Responding to the calls for research to address this gap, the current study investigates how financial literacy relates to access to funding, innovative service adoption, and sustainable food production among agricultural food producers in Nigeria’s rural communities. A probability sampling technique was used to draw 460 samples from registered rural farmers in the Central Bank of Nigeria’s Anchored Borrower’s Programme for food production in Edo State, Nigeria. Quantitative data were collected using a structured questionnaire. The hypotheses were tested using regression analysis, while descriptive statistics were deployed to analyse the demographic data of the respondents. The outcomes suggest that financial literacy has significant links with access to funding, innovative service adoption and sustainable food production among agricultural food producers in Nigerian rural communities. Based on the outcomes, it is concluded that financial literacy significantly influences sustainable food production in Nigerian rural communities. As such, there is a need for the Nigerian government and financial authorities to embark on a financial literacy drive to increase financial literacy, particularly in light of ever-evolving disruptive financial technologies. Full article

Forming interdisciplinary research teams is challenging, especially when the pool of candidates is large and/or the addressed research projects require multi-disciplinary expertise. Based on their previous research outputs, like published work, a data-driven team formation procedure selects the researchers that are likely to work well together while covering all areas and offering all skills required by the multi-disciplinary topic. The description of the research team formation problem proposed in this paper uses novel quantitative metrics about the team candidates computed from bibliographic metadata records. The proposed methodology first analyzes the metadata fields that provide useful information and then computes four synthetic indicators regarding candidates’ skills and their interpersonal traits. Interdisciplinary teams are formed by solving a complex combinatorial multi-objective weighted set cover optimization problem, defined as equations involving the synthetic indicators. Problem solving uses the NSGA-II genetic algorithm. The proposed methodology is validated and compared with other similar approaches using a dataset on researchers from Politehnica University of Timisoara extracted from the IEEE Xplore database. Experimental results show that the method can identify potential research teams in situations for which other related algorithms fail. Full article

This paper addresses the problem of loss of control during flight caused by failures of flight control surfaces. It presents a study of an emergency thrust control system based on linear-quadratic control with integral action. The research encompasses an analysis of thrust modulation control characteristics, a review of existing control systems, and a detailed description of the development process, including the research platform configuration, identification of the aircraft state-space model, control law design, integration of system components within the MATLAB and Simulink environment, and software-in-the-loop testing conducted in the X-Plane 11 flight simulator using a Boeing 757-200 model. The study also investigates the issue of control channel cross-coupling and its impact on simultaneous control of the aircraft’s longitudinal and lateral dynamics. The simulation results demonstrate that the proposed emergency system provides adequate controllability, with settling times of approximately 12 s for achieving a flight path angle setpoint of +5°, and 13 s for attaining a maximum (limited) roll angle of 20°, achieved in separate manoeuvres. Furthermore, simulated landing attempts suggest that the system could potentially enable successful landings at approach speeds significantly higher than standard recommendations. However, further investigation is required to address decoupling of control channels, ensure system stability, and evaluate control performance across a broader range of aircraft configurations. Full article