Search Results (4,629)

Many organic fungicides are chiral and are used in diverse application areas, including pharmaceuticals, personal care products, agrochemicals, and industry. Fungicides have valuable effects such as preventing fungal infestations and the treatment of diseases, but their generalized use resulted in their occurrence in diverse environmental compartments which is an increasing environmental concern with negative impact on non-target organisms and human health risks. Besides, enantiomers of chiral fungicides may exhibit distinct bioactivity including toxicity and degradation profiles. Therefore, monitoring their enantioselective occurrence in the environment is essential to accurately assess enantioselective (eco)toxicity and establish environmental quality standard levels. This review provides the first comprehensive and critically interpretative assessment of enantioselective chromatographic methods for the determination of fungicides, with a primary focus on azole compounds, in complex environmental matrices (e.g., soil, sediment, plants, earthworms, sewage sludge, water, wastewater) due to their regulatory relevance in the EU Watch Lists, frequent occurrence in environmental matrices, and specific analytical challenges associated with their chiral nature. Other fungicide classes are also included, since other fungicides (either chiral or achiral) reported in the articles retrieved by the literature search, were also evaluated, integrating methodological, analytical and regulatory dimensions. Liquid chromatography was identified as the predominant analytical technique, with polysaccharide-based chiral stationary phases being the most frequently used, while sample preparation was mainly based on solid-phase extraction and QuEChERS-based approaches for complex environmental matrices. Analytical performance parameters were compared to highlight strengths and limitations of reported methods, while environmental monitoring data were reviewed, identifying soil and water as matrices with the highest reported chiral fungicide levels. The urgent need to develop robust enantioselective analytical methods to recognize the distinctive biological and toxicological properties of individual enantiomers are critically discussed. By revealing persistent gaps in enantioselective workflows and regulatory differentiation between enantiomers, it highlights the need for robust analytical approaches and reliable monitoring strategies to contribute for future enantiomer-specific environmental risk assessment frameworks. Full article

Cohesion among individuals reflects the quality of relationships and interpersonal interaction within a community. Elements such as social connections, trust, and a sense of belonging serve as key indicators of societal cohesion and are often rooted in acts of good neighborliness. Despite this, limited knowledge exists regarding perceptions and behaviors related to good neighborliness within South African society. The present study examines how perceptions and practices of good neighborliness contribute to the development of cohesive communities. Research was conducted in four South African communities: Philippolis, Lambert’s Bay, Caledon, and Grabouw. Utilizing an interpretivist approach, the study adopted a qualitative methodology involving interviews with 25 participants, including family members and community stakeholders. Data were collected through in-depth interviews, and thematic analysis facilitated the identification of recurring patterns and key themes. The principal themes identified were everyday mutual support and practical assistance, moral norms and values of care, social familiarity and community connectedness, trust and good neighborliness, and intergroup relations and cohesion across diversity. The findings demonstrate the crucial role of good neighborliness in advancing social cohesion. For communities and families to thrive, it is vital that members experience safety and cultivate trusting relationships, which often requires openness about their vulnerabilities and needs. Full article

This study focuses on identifying wine-growing subzones within the PDO Amyndeon and PGI Drama wine-growing zones in Northern Greece, with the aim of assessing their suitability for producing high-quality red wines from the Xinomavro (Vitis vinifera L.) and Cabernet Sauvignon (Vitis vinifera L.) grape varieties, respectively. The initial delineation of suitability zones was carried out using readily available satellite data on soil, topography, and climate, in four different suitability categories. To validate how effectively these categories distinguished actual wine-growing regions, we compared them against two years of field data collected from experimental vineyards. The results showed that this methodology was able to discern the most suitable areas for both varieties and regions with an acceptable relation to real grape and wine attributes as confirmed by the collection of data from the pilot vineyards. The overall performance of this method will ultimately depend on the validity of the expert knowledge used to define the most critical parameters and their range. According to the results of this study, and given the relevance of the proposed suitability criteria, this method has the potential to provide an alternative solution for subzone delineation in cases where wine analytical and sensory data are not available. Full article

Introduction: The potential role of food hypersensitivity in the insurgence of inflammatory activity in arthritis such as Rheumatoid Arthritis (RA) has received intermittent attention, also supported by theoretical links involving mucosal immunity, mast-cell activation, and microbiome–immune interactions. Despite biological plausibility, the clinical significance of dietary antigens in RA remains uncertain. Methods: A systematic review was conducted following the PRISMA guidelines. Searches using PubMed, Scopus, and Web of Science identified studies exploring dietary interventions or food hypersensitivity in RA. Eligible articles included clinical trials, case reports, and observational studies, in English or Italian, up to the 10 December 2025. Data extraction and quality assessment were performed using the Newcastle–Ottawa Scale. Results: Eight studies met the inclusion criteria. Findings indicate that elimination or elemental diets occasionally yielded subjective improvements—such as a reduction in pain, morning stiffness, and functional improvements—yet objective inflammatory markers rarely changed. Small, highly selected, cohorts demonstrated immuno-histological alterations, including reduced mast-cell density, while long-term diets (e.g., gluten-free or vegan) have reduced specific IgG levels without altering radiographic progression. Conclusions: Evidence suggests that dietary interventions may offer symptomatic relief only in a minority of RA patients. Due to methodological constraints, inconsistent outcomes, and limited applicability to contemporary treatments, dietary approaches need further exploration and investigation. Rigorous trials in modern cohorts are warranted to clarify whether food hypersensitivity meaningfully influences RA pathophysiology. Full article

Landscape Character Assessment (LCA) is increasingly used to support landscape-sensitive planning; however, existing approaches often lack an operational integration of visual perception and map-based indicators, particularly in complex Mediterranean island contexts. This study demonstrates a methodology for integrated landscape character and quality assessment, combining landform and landcover mapping with map-based visibility indicators derived from the local road network. The approach was applied to the Platanos community in western Crete, a representative Mediterranean landscape of contrasting coastal resort zones, agricultural lowlands, and cultural heritage sites. The methodology followed three stages: desk-based mapping of Land Description Units (LDUs) using landform and landcover data, field surveys to define Landscape Character Types (LCTs) and assess socio-cultural and perceptual attributes, and GIS-based visibility analysis from 18 road observation points. Six visual indicators (connectivity, complexity, naturalness, disturbance, historicity, and visual scale) were calculated to quantify spatial and perceptual characteristics. Results revealed a spatial division between a core northern area of high visual scale, cultural importance, but also disturbance, and a southern area of greater naturalness but lower visual openness and cultural visibility. These results highlight that high landscape quality is not solely associated with naturalness, but emerges from the interaction between physical structure, cultural elements, and visual perception. The findings underscore the complementary value of combining physical, cultural, and perception-based metrics in LCA. The proposed framework offers a reproducible tool for evidence-based landscape planning and heritage-sensitive development in accordance with the principles of the European Landscape Convention (ELC). Full article

Hypersonic vehicles impose stringent requirements on lightweight structures to maintain mechanical integrity under extreme thermal environments. Bismaleimide (BMI)-based carbon fiber-reinforced polymer (CFRP) composites, featuring a high glass transition temperature and excellent thermal stability, are regarded as promising candidates for such applications. However, the high curing temperature and narrow processing window of BMI resins make it challenging to manufacture stiffened-shell structures with low defect levels and high fiber volume fractions. In this study, an integrated manufacturing route—hot-melt prepregging–filament winding–matched-metal mold forming—is proposed, and the key processing parameters are optimized via single-factor experiments and the Box–Behnken response surface methodology. The tensile strength of the laminate is selected as the response variable to evaluate the effects of the compression displacement (A), thermal consolidation/bonding temperature (B), heating rate (C), and cooling rate (D). The results reveal a unimodal dependence of the tensile strength on each parameter, with the significance ranking B > D > A > C; moreover, the A–B and A–D interactions are significant (p < 0.01). The established quadratic regression model exhibits good agreement with experimental data (R² = 0.974; R²_adj = 0.949). The predicted optimum conditions are A = 0.07 mm, B = 114.93 °C, C = 1.35 °C·min⁻¹, and D = 4.58 °C·min⁻¹, corresponding to a predicted tensile strength of approximately 2287 MPa. Validation experiments yielded 2291 MPa, in excellent agreement with the prediction. Microstructural observations indicate tight interlaminar bonding and a pronounced reduction in voids under the optimized conditions. Applying the optimized process to fabricate stiffened-shell demonstrators achieves a fiber volume fraction of >60% and a void content of <1%. This work provides a quantitatively defined processing window and parameter optimization basis for the high-quality manufacturing of BMI-CFRP stiffened-shell structures, with significant engineering relevance. Full article

Background: Despite the implementation of numerous evidence-based interventions, the 2024 Point-in-Time count in the United States (U.S.) reported that 259,473 people in families with children under 18 years old were experiencing homelessness, a record high since the count began in 2007. Recent findings suggest that co-developed interventions may increase engagement with vulnerable populations and, in turn, the effectiveness of health-based programs among them. Objective: In this review, we sought to systematically search and assess the current evidence on co-developed community-based interventions with and for children under age 18 and families experiencing homelessness (CFEH) in high-income countries and their impact on health and well-being outcomes. Methods: Seven databases (e.g., Medline, CINAHL, Embase) and four additional scholarly sources (e.g., Health CASCADE) were searched (publication dates between January 2000 and February 2025). In our analysis, methodological “quality” was assessed through two primary criteria: internal validity and the extent of CFEH involvement. Results: A total of 1617 studies were screened for eligibility, and nine studies were found to have co-developed interventions with CFEH in the U.S. (n = 6) and the United Kingdom (n = 3). These were categorized thematically by socio-structural, behavioral, and combined intervention types. Five studies reported positive engagement among families and staff, whereas three reported improved mental health outcomes. Conclusions: This review highlights the potential impact of co-developed interventions on CFEH’s mental and physical well-being as well as process-based outcomes. Limitations include different definitions of “co-” terminology and homelessness across studies, as well as a lack of transparency about the extent of CFEH’s involvement in these studies. The dearth of evidence indicates that future research should employ community-based participatory research while striking a balance of working with CFEH and other partners and ensuring the data are reliable and reproducible. Full article

Background/Objectives: The prediction of survival after resection of colorectal liver metastases is crucial for planning treatment strategies. Several prognostic scores have been proposed, but their reliability is debated. The present study aims to review available prognostic scores, focusing on their performance and the methodological approaches adopted for their evaluation. Methods: A systematic literature review was conducted using PubMed, Embase, and the Cochrane Database, including studies published between January 2015 and June 2024. Only English-language studies reporting the external validation of prognostic models were included. A random-effects meta-analysis was performed. Results: Overall, 48 prognostic scores were externally validated across 48 studies (n = 33,602 patients). A total of 286 performance measurements were reported, utilizing 17 different metrics and considering four outcomes: overall survival (OS), cancer-specific survival, recurrence-free survival (RFS), and recurrence rate. For OS, the pooled C-index values for the Fong, GAME, and RAS mutation Clinical Risk scores were 0.578 (0.570–0.587), 0.609 (0.592–0.625), and 0.579 (0.471–0.688), respectively. For RFS, the pooled C-index for the Fong score was 0.616 (0.578–0.653). Scores incorporating genetic, immunological and radiomic data performed better than purely clinical ones (C-index = 0.610, 0.657 and 0.635, respectively, vs. 0.585, p < 0.05). Analogously, the scores including perioperative data outperformed preoperative ones (C-index = 0.671 vs. 0.600, p = 0.007). Conclusions: The current survival prediction relies on scores with low reliability (C-index ≤ 0.65). Despite the abundance of available data, their heterogeneity and variable quality have limited their usability. Future research should prioritize the development of new prognostic tools and the standardization of prognostic modeling and reporting. Full article

Background: Dengue infection (DI) is a mosquito-borne arboviral disease primarily transmitted by infected female Aedes mosquitoes. In Bangladesh, DI poses a substantial public health challenge with recurrent outbreaks and rising incidence rates. This systematic review assesses the epidemiological characteristics of dengue infection in Bangladesh, focusing on demographic, clinical, and geographic trends. Objectives: To analyze dengue prevalence, demographic distribution, clinical symptoms, and serotype patterns in Bangladesh, with an emphasis on urban–rural disparities, gender differences, and serotype evolution. Methods: A systematic search was conducted across PubMed, Scopus, Web of Science, and Global Health (Ovid) databases, reviewing studies published from 2000 to 2024. Following PRISMA guidelines, 25 studies meeting eligibility criteria were selected. Data extraction and quality assessment were independently performed by three reviewers, ensuring methodological rigor. Results: Dengue incidence was higher in urban areas, mainly affecting males aged 20–34, with dengue virus serotype 3 (DENV-3) as the dominant serotype. Fever, headache, and joint pain were the most common symptoms, while severe cases often presented with respiratory and hemorrhagic complications. Acute symptoms like dyspnea and dehydration spread rapidly in densely populated areas. In rural areas, dengue showed a more endemic pattern, with persistent symptoms such as gastroenteritis and muscle pain. Conclusion: Dengue is now firmly endemic in Bangladesh, with clear geographic, demographic, and clinical differences. The dominance of DENV-3 and its association with more severe illness highlight the need for targeted and context specific interventions. Control efforts should prioritize vector management, public education, and continuous surveillance in urban areas, while strengthening community surveillance and primary healthcare in rural settings. Further research on rural transmission and the clinical impact of DENV-3 is essential to guide effective and tailored dengue control strategies. Full article

Background: Acute coronary syndrome (ACS) is a “can’t miss” diagnosis. The gold-standard workup for this requires serial troponin biomarker evaluation over a period of hours. Traditionally, many of these patients required telemetry while being evaluated in this fashion; however, the high-quality literature suggests that low-risk patients do not require ongoing continuous cardiac monitoring. Locally, it was found that over 70% of patients presenting with low-risk chest pain to our high-volume urgent care were transferred to the main hospital for an ACS rule-out work-up via emergency medical services (EMS). We felt this intersection of patient care and medical services could be streamlined to reduce critical resource utilization. Objective: The aim of this study is to reduce the usage of EMS utilization for transport of low-risk chest-pain patients from the urgent care to the main hospital by 25% over a 3-month period. Methods: This study was conducted as an uncontrolled before–after interrupted time series design. A comprehensive data drilldown was performed through a chart review and structured clinical-practice evaluation. This led to a multi-factorial quality improvement initiative centered around the creation of an evidence-based safe-for-self-transport tool and physician education. The primary outcome measure was the proportion of patients transported via EMS with the main balancing measures being the proportion of self-transported patients admitted to the hospital and the time to troponin blood-draw in self-transported patients. Results: The education and the newly developed transport tool resulted in a sustained shift below the previous baseline system mean control limit, indicating a significant reduction in EMS usage for patient transport. The overall reduction in usage was 30%. No change in balancing (safety) measures was identified post-implementation. Conclusions: EMS remains a finite resource within many Canadian health regions. The results of this study show that by focusing on a cardinal emergency-department presentation like chest pain, adapting evidence-based practice through quality-improvement methodologies can result in a significant sustained reduction in EMS utilization. Full article

Owing to the high pharmacological relevance and multidimensional quality attributes of Panax spp., accurate authentication and quality evaluation of Panax-derived herbal materials remain challenging within traditional Chinese medicine (TCM) quality control systems. Conventional approaches often face trade-offs among analysis speed and throughput, non-destructive measurement, and analytical accuracy, which can limit their suitability for modern, large-scale quality control. This review summarizes recent advances in vibrational and related analytical techniques—infrared (IR) and near-infrared (NIR) spectroscopy, Raman spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging (HSI), and nuclear magnetic resonance (NMR)—for authentication and quality evaluation of Panax materials. We compare the capabilities of each modality in supporting key tasks, including species authentication, geographical origin tracing, age/cultivation-stage discrimination, and quantitative assessment of major chemical markers, with emphasis on the underlying measurement principles. In general, NIR and HSI are well suited to rapid, high-throughput screening of bulk samples, whereas Raman and NMR provide higher chemical specificity for molecular and structural characterization. To mitigate limitations of single-modality analysis, this review discusses a methodological shift from conventional spectral fingerprinting and chemometric approaches toward model-driven, data-enabled sensing strategies for robust quality evaluation. Specifically, we highlight multimodal data fusion frameworks combined with interpretable machine-learning/deep-learning methods to build robust classification and regression models for quality assessment. This perspective aims to support standardized and scalable authentication and quality evaluation of Panax herbal materials and to facilitate the digitization of quality control workflows for Chinese herbal medicines. Full article

Origin–Destination matrices (ODms) are a fundamental input for public transport planning and optimization, as they characterize travel demand across a network. Traditionally estimated from user surveys, ODms are now increasingly inferred from large-scale automatically collected data, such as Automated Fare Collection (AFC), Automated Passenger Counting (APC), and Automated Vehicle Location data (AVL). This review focuses on the reconstruction of static ODms in public transport systems, while accounting for studies that exploit dynamic or short-term observations when these are used to infer static or quasi-static demand patterns. We provide a transversal synthesis of OD estimation approaches by jointly analyzing data sources, modeling assumptions, uncertainty handling, and validation strategies. A structured comparative table summarizes representative case studies across different data contexts, objectives, and methodological families. Beyond a descriptive overview, this review identifies key research gaps, including the lack of uncertainty-aware benchmarking frameworks, the limited propagation of uncertainty across modeling stages, and the strong dependence of reported performance on data quality and validation references. These findings highlight that OD estimation performance is context-dependent and that methodological choices should be aligned with data availability, modeling objectives, and acceptable assumptions rather than with reported accuracy alone. Full article

This study proposes a data quality-driven channel selection methodology to improve hand gesture recognition performance in multi-channel wearable Human–Machine Interface (HMI) systems. The methodology centers around calculating (i) five data quality indices for both surface electromyography (sEMG) and pressure-based force myography (pFMG) signals and (ii) establishing a relationship between these data quality indices and the accuracy of gesture recognition for applications typified by prosthetic hand control. Machine learning (ML)-based and correlation-based methods were used to select three optimal channel/pair configurations from an eight-channel/pair system. Evaluations on the UOW and Ninapro DB2 datasets showed that the proposed methods consistently outperformed random channel selection, with the ML-based approach achieving the best results (76.36% for sEMG, 71.59% for pFMG, and 88.2% for fused sEMG-pFMG on the UOW dataset and 70.28% on Ninapro DB2). Notably, using three pairs of strategically selected sEMG-pFMG channels generated 88.2%, which is comparable to the 88.38% accuracy obtained with a full eight-channel sEMG system on the UOW dataset, highlighting the efficacy of our channel selection methodologies. These results highlight the value of data quality indices for sensor selection and provide a foundation for developing more efficient wearable HMI systems. Full article

Honey is a complex natural product with nutritional and therapeutic properties that depend on the diversity of its chemical composition, which includes volatile organic compounds (VOCs). VOCs in honey are key indicators of its botanical and geographical origin, as well as its quality and authenticity. This review provides a comprehensive overview of the analytical instruments and methods used for the identification and quantification of VOCs in different types of honey. Techniques such as headspace solid-phase microextraction (HS-SPME) are used for VOC extraction, and gas chromatography coupled with mass spectrometry (GC-MS) and electronic nose (e-nose) systems for honey analyses, as well as their advantages, limitations, and applications and challenges related to VOC analysis, such as for different types of honeys, their aroma profile, compound variability, and data interpretation, are also discussed. By summarizing recent advancements in analytical methodologies, this review provides an overview of the analysis of VOCs for authentication and research purposes in honey production and processing. Full article

Arable land quality is of the essence for the sustenance of grain production and food security. The continuous monitoring of the physical and chemical properties of arable land is instrumental in facilitating a comprehensive understanding of the evolution patterns of soil quality. This, in turn, provides fundamental evidence that is crucial for the optimization of cultivation practices, the establishment of appropriate plough layers, and the enhancement of soil quality. The near-surface sensing methodologies facilitate the acquisition of soil data at reduced scales, thus signifying a pivotal research trajectory for the procurement of soil-related information. The present study undertakes an examination of the current state of research on acquiring key parameters of farmland soil and provides an overview of the fundamental ground-level techniques employed for the assessment of farmland soil parameters. These techniques encompass single-parameter fixed-point detection, encompassing Soil Moisture Content (SMC), Soil Electrical Conductivity (EC), and nutrient analysis, multi-parameter fusion detection, and dynamic parameter monitoring. The study systematically reviews field sensing methods for major soil physicochemical parameters (such as SMC, Soil Penetration Resistance (SPR), EC, and nutrients) while analyzing the current application of Artificial Intelligence (AI) in soil parameter detection. The present paper proposes a developmental trajectory that shifts from “single-parameter static” to “multi-parameter dynamic” monitoring. This trajectory is proposed as a building upon the analysis of existing research. This evolution emphasizes intelligent algorithm-driven data enhancement to improve detection accuracy, forming a closed-loop progression of “dynamic detection—precise modeling—decision support”. This framework provides a reference for the advancement of soil sensing monitoring technologies and the scaling of precision agriculture applications. Full article