Search Results (1,407)

Due to their excellent physicochemical properties, the nanoparticles (NPs) have been utilized in various potential applications, including environmental remediation, energy storage, and nanomedicine. In this work, the ultrasonic and manual stirring approaches were used to integrate yttrium oxide (Y₂O₃) nanoparticles (NPs) into reduced graphene oxide (RGO) and carbon nanotubes (CNTs) to enhance their photocatalytic and anticancer properties. Pure Y₂O₃NPs, Y₂O₃/RGO NCs, and Y₂O₃/CNTs NCs were characterized using different analytical techniques, such as XRD, SEM, EDX with Elemental Mapping, FTIR, UV-Vis, PL, and DLS to investigate their improved structural, surface morphological, chemical bonding, optical, and surface charge properties. XRD data confirmed the successful integration of Y₂O₃into RGO and CNTs, with minor changes in crystallite sizes. SEM images with EDX analysis revealed that Y₂O₃NPs were uniformly distributed on RGO and CNTs, reducing aggregation. Chemical bonding and interactions between Y₂O₃and carbon materials were investigated using Fourier Transform Infrared (FTIR) analysis. UV and PL results suggest that the optical studies showed a shift in absorption peaks upon integration with RGO and CNTs. This indicates enhanced light absorption and modifications to the band gap between (3.79–4.40 eV) for the obtained samples. In the photocatalytic experiment, the degradation efficiency of bromophenol blue (BPB) dye for Y₂O₃RGO NCs was up to 87.3%, outperforming pure Y₂O₃NPs (45.83%) and Y₂O₃/CNTs NCs (66.78%) after 120 min of UV irradiation. Additionally, the MTT assay demonstrated that Y₂O₃/RGO NCs exhibited the highest anticancer activity against MG-63 bone cancer cells with an IC50 value of 45.7 µg/mL compared to Y₂O₃CNTs NCs and pure Y₂O₃NPs. This work highlights that Y₂O₃/RGO NCs could be used in significant applications, including environmental remediation and in vivo cancer therapy studies. Full article

Nepal is currently facing critical water quality challenges due to urbanization, water management and governance issues, as well as natural disasters. This has resulted in the presence of harmful contaminants (e.g., pathogens, nitrates, arsenic) across multiple water sources, subsequently leading to waterborne disease risks (e.g., cholera and typhoid). In response to these environmental and public health concerns, we conducted a scoping review to assess microbial and chemical contaminants in drinking and irrigation water in Nepal, as well as their potential impacts on public health. Following the JBI Manual for Evidence Synthesis and the PRISMA-SCR guidelines, we systematically searched for peer-reviewed literature on Nepal’s water quality in seven databases. Of 3666 unique records screened using predefined inclusion criteria, 140 met our criteria. The studies encompassed a variety of methodological designs, with the majority focusing on water sources in the Bagmati province. Bacteria and arsenic emerged as the most prevalent contaminants. Additionally, diseases such as arsenicosis and typhoid remain widespread and may be linked to contaminated water sources. The review identified key gaps in Nepal’s water quality management, including limited geographic research coverage, inconsistent testing protocols, weak regulatory enforcement, and a lack of integration of water quality with public health planning. Our findings underscore the urgent need for effective surveillance systems and a robust regulatory framework to promptly respond to water contamination events in Nepal. Full article

Background: Pain is a disabling issue in athletes, with significant impact on performance and career longevity. Many randomized clinical trials (RCTs) have explored interventions to reduce pain, leading to multiple systematic reviews with meta-analysis, but their methodological rigor and clinical applicability remain unclear. Objective: To provide an overview of systematic reviews with meta-analysis on interventions aimed at alleviating pain intensity in athletes, identifying knowledge gaps and appraising methodological quality. Methods: CINAHL, Embase, Epistemonikos, PubMed, Scopus, SPORTDiscus, and Cochrane Library were searched from inception to February 2025. Systematic reviews with meta-analysis of RCTs evaluating interventions to manage pain in athletes were considered. Athletes without restrictions in terms of sports, clinical, and sociodemographic characteristics were included. Overlap between reviews was calculated using the corrected covered area. Results: Twelve systematic reviews met inclusion criteria. Physical exercise modalities (e.g., gait retraining, hip strengthening), acupuncture, photo biomodulation, and topical medication showed potential benefits in reducing pain intensity. Other interventions, such as certain manual therapy techniques, platelet-rich plasma, or motor imagery, did not show consistent effects. All reviews focused solely on pain intensity, with minimal stratification by sport or clinical condition which may affect the extrapolation of meta-analyzed findings to the clinical practice. Methodological quality was often low, with flaws in reporting funding sources, lists of excluded studies, and certainty of evidence (was mostly rated as low/very low). Overlap was variable across the interventions. Conclusions: Given low/sparse certainty and minimal sport-specific analyses, no strong clinical recommendations can be made; preliminary signals favor proximal hip strengthening, gait retraining, photo biomodulation (acute soreness), and topical NSAIDs pending higher-quality syntheses. Future reviews should consider mandatory GRADE; pre-registered protocols; sport- and condition-specific analyses; and core outcome sets including multi-dimensional pain. Full article

Various types of interfering signals are an integral part of ECGs recorded using wearable electronics, specifically during field monitoring, outside the controlled environment of a medical doctor’s office, or laboratory. The frequency spectrum of several types of interfering signals overlaps significantly with the ECG signal, making effective filtration impossible without losing clinically relevant information. In this article, we proceed from the practical assumption that it is unnecessary to analyze the entire ECG recording in real long-term recordings. Conversely, in the preprocessing phase, it is necessary to detect unreadable segments of the ECG signal. This paper proposes a novel method for automatically detecting unreadable segments distorted by superimposed interference in ECG recordings. The method is based on a convolutional neural network (CNN) and is comparable in quality to annotation performed by a medical expert, but incomparably faster. In a series of controlled experiments, the ECG signal was recorded during physical activities of varying intensities, and individual segments of the recordings were manually annotated based on visual assessment by a medical expert, i.e., divided into four different classes based on the intensity of distortion to the useful ECG signal. A deep convolutional model was designed and evaluated, exhibiting a 87.62% accuracy score and the same F1-score in automatic recognition of segments distorted by superimposed interference. Furthermore, the model exhibits an accuracy and F1-score of 98.70% in correctly identifying segments with visually detectable and non-detectable heart rate. The proposed interference detection procedure appears to be sufficiently effective despite its simplicity. It facilitates subsequent automatic analysis of undisturbed ECG waveform segments, which is crucial in ECG monitoring using wearable electronics. Full article

As a global staple ensuring food security, maize incurs 15–20% annual yield loss from pests/diseases. Conventional manual detection is inefficient (>7.5 h/ha) and subjective, while existing YOLO models suffer from >8% missed detections of small targets (e.g., corn armyworm larva) in complex fields due to feature loss and poor multi-scale fusion. We propose YOLO-FDLU, a YOLO11s-based framework: LAD (Light Attention-Downsampling)-Conv preserves small-target features; C3k2_DDC (DilatedReparam–DilatedReparam–Conv) enhances cross-scale fusion; Detect_FCFQ (Feature-Corner Fusion and Quality Estimation) optimizes bounding box localization; UIoU (Unified-IoU) loss reduces high-IoU regression bias. Evaluated on a 25,419-sample dataset (6 categories, 3 public sources + 1200 compliant web images), it achieves 91.12% Precision, 92.70% mAP@0.5, 78.5% mAP@0.5–0.95, and 20.2 GFLOPs/15.3 MB. It outperforms YOLOv5-s to YOLO12-s, supporting precision maize pest/disease monitoring. Full article

Background/Objectives: Tumor-infiltrating lymphocytes (TILs) are emerging as a crucial prognostic biomarker in triple-negative breast cancer (TNBC). However, their clinical utility remains constrained by the subjectivity and interobserver variability of manual scoring, despite standardization efforts by the International TILs Working Group (TIL-WG). This study aimed to evaluate the interobserver agreement among pathologists in scoring stromal and intratumoral TILs from H&E-stained TNBC slides and to identify contributing histological factors. Methods: Two consultant pathologists at Hospital Canselor Tuanku Muhriz, Kuala Lumpur, independently assessed 64 TNBC cases using TIL-WG guidelines. Interobserver agreement was quantified using the intraclass correlation coefficient (ICC) and Cohen’s kappa coefficient. Cases with over 10% scoring discrepancies underwent review by a third pathologist, and a consensus discussion was held to explore the underlying confounders. Results: Our results showed moderate interobserver agreement for stromal TILs (ICC = 0.58) and strong agreement for intratumoral TILs (ICC = 0.71). Significant variability was attributed to three main confounding variables: heterogeneous TIL distribution, poorly defined tumor-stroma interface, and focal dense lymphoid infiltrates. Conclusions: These findings highlight the need for standardized TIL scoring protocols and suggest that validated AI-based tools may help mitigate observer variability in future TIL assessments. Full article

Human storytellers often orchestrate diverse narrative orders (chronological, flashback) for crafting compelling stories. To equip artificial intelligence systems with such capability, existing methods rely on implicitly learning narrative sequential knowledge, or explicitly modeling narrative order through pairwise event temporal order (e.g., take medicine <after> get ill). However, both suffer from imbalanced narrative order distribution bias and inadequate event temporal understanding, hindering generating high-quality events in the story that balance the logic and narrative order. In this paper, we propose a narrative-order-aware framework, TimeWeaver, which presents an event–order bidirectional pretrained model integrated with temporal mixture-of-experts to orchestrate diverse narrative orders. Specifically, to mitigate imbalanced distribution bias, the temporal mixture-of-experts is devised to route events with various narrative orders to corresponding experts, grasping distinct orders of narrative generation. Then, to enhance event temporal understanding, an event sequence narrative-order-aware model is pretrained with bidirectional reasoning between event and order, encoding the event temporal orders and event correlations. At the fine-tuning stage, reinforcement learning with multi-granular optimal transport reward is designed to boost the quality of generated events. Extensive experimental results on automatic and manual evaluations demonstrate the superiority of our framework in orchestrating diverse narrative orders during story generation. Full article

Background/Objectives: This in vitro study evaluated the effects of fluoride-free toothpaste, fluoride-containing toothpaste, and a color-correcting gel on the morphology, composition, and mechanical properties of demineralized human enamel. The hypothesis was that fluoride-containing formulations would better preserve enamel integrity compared to non-fluoride and cosmetic products. Methods: Extracted human teeth (n = 3 per group) were demineralized with 36% phosphoric acid and assigned to four groups: E0 (control), E1 (fluoride-free toothpaste), E2 (fluoride-containing toothpaste), and E3 (color-correcting gel). Brushing was performed manually twice daily for 7 days using standardized force. Surface morphology and elemental composition were assessed via SEM–EDX; chemical changes were analyzed by FTIR; mechanical properties were evaluated using the Vickers microhardness test. Results: E1 exhibited the highest microhardness (343.6 HV) but also the highest Ca/P ratio (2.37) and most pronounced surface roughness (p < 0.05 vs. control). E2 showed a balanced Ca/P ratio (2.07), smoother morphology, and detectable fluoride incorporation, despite a lower hardness value (214.5 HV). E3 presented moderate changes in both morphology and composition, with a Ca/P ratio similar to the control (2.06) but surface irregularities visible by SEM. The apparent paradox in E1—high hardness with structural damage—may be due to superficial mineral precipitation without true remineralization. Conclusions: Fluoride-containing toothpaste preserved enamel morphology and chemistry more effectively than the other formulations. Increased hardness in E1 does not necessarily indicate clinical benefit. In vivo studies with longer protocols and pH cycling are needed to confirm these findings. Full article

While sign language combines sequential hand motions with concurrent non-manual cues (e.g., mouth shapes and head tilts), current recognition systems lack multimodal annotation methods capable of capturing their hierarchical semantics. To bridge this gap, we propose GSP-MC, the first method integrating generative large language models into sign language recognition. It leverages retrieval-augmented generation with domain-specific large language models and expert-validated corpora to produce precise multipart descriptions. A dual-encoder architecture bidirectionally aligns hierarchical skeleton features with multi-level text descriptions (global, synonym, part) through probabilistic matching. The approach combines global and part-level losses with KL divergence optimization, ensuring robust alignment across relevant text-skeleton pairs while capturing sign semantics and detailed dynamics. Experiments demonstrate state-of-the-art performance, achieving 97.1% accuracy on the Chinese SLR500 (surpassing SSRL’s 96.9%) and 97.07% on the Turkish AUTSL (exceeding SML’s 96.85%), confirming cross-lingual potential for inclusive communication technologies. Full article

This study examines the portrayal of Ukrainian refugee women in Polish media, specifically in Gazeta Wyborcza and Rzeczpospolita, over three years of the full-scale Russian–Ukrainian war (24 February 2022–24 February 2025). Using an interdisciplinary approach that combines gender studies, critical discourse analysis, and migration studies, the research aims to identify dominant narratives, stereotypes, and framing strategies in media representations of Ukrainian refugee women. A mixed-methods analysis was conducted, incorporating both qualitative and quantitative techniques. A total of 235 articles were manually examined and categorized using a coding scheme that analyzed attitude of voice (positive, neutral, negative), dominant narratives (e.g., victimhood, resilience, economic impact), descriptors (e.g., hard-working, dependent, caring), and framing strategies (humanitarian, security, economic, cultural). Additionally, the study examined how a range of contextual factors—including political discourse, economic conditions, and social dynamics—influenced the framing and specificity of media coverage related to Ukrainian women refugees in Poland. The findings reveal key trends in the representation of Ukrainian refugee women, including their portrayal as victims, economic contributors, or burdens to society. By analyzing the construction of these narratives, this research contributes to a broader understanding of media-driven stereotypes and their impact on social attitudes and policymaking in Poland. Full article

Discourse markers have been extensively studied in spoken languages from different perspectives, covering monolingual, contrastive, and translation studies. However, research on these items remains limited for signed languages, with only a handful of scattered publications. Following a corpus-based approach, this paper aims to investigate discourse markers in French Belgian Sign Language (LSFB), including their types, functions, and translation/s into written French. An 18 min sample of three dialogues and six signers was analyzed using a two-level independent taxonomy (domain and function) previously applied to spoken and signed data. Overall, 251 discourse markers were identified in the LSFB sample. They can be manual, nonmanual, or a combination of both, the latter type being the most frequent. In contrast to the previous literature, discourse markers cannot be spatial in LSFB. Regarding their functional spectrum, most discourse markers belong to the sequential domain (i.e., they are mostly used to structure discourse) and express ‘addition’ (i.e., providing more information) or ‘monitoring’ (i.e., keeping control over one’s turn or over the interaction). When examining the translation of DMs, most are either omitted or substituted by other non-discourse marking items in the target texts. Although these results are generally similar to previous studies on DMs in spoken languages, more research on these items in other signed languages is needed to obtain a precise overview of their role in human communication. Full article

The energy consumption of buildings, the effectiveness of energy-saving measures, and the exploitation of energy-saving potential are strategic issues for improving the energy performance of public assets and limiting their environmental impact. However, small and medium municipalities (SMMs) encounter difficulties in identifying their energy-intensive units, a process that is often lengthy (3 to 18 months), costly, and dependent on traditional methods such as the Real Estate and Energy Master Plan (REMP) promoted by ADEME or the Cit’ergie system. These approaches, although structured, rely on time-consuming manual analyses that require significant technical and human resources. This article proposes an innovative solution, PG2E, based on a combinatorial approach that quickly identifies Energy-Saving Potential Scope (ESPSs) from energy consumption data. Backed by a realistic–critical stance to assess the limitations of existing systems and a constructivist–pragmatic approach to designing a tool adapted to SMMs, the PG2E solution uses simple statistical criteria (average, upper quartile). This study, conducted in the town of Quesnoy-Sur-Deûle, shows that PG2E identifies ESPS with a success rate of 60% to 100% while reducing time and costs. It thus offers an accessible digital alternative for initiating an approach that complies with the ISO 50001 standard. Full article

Social researchers have extensively examined the systematic role played by digital platforms, algorithms and datafication processes in shaping social life. In response to the overwhelming power asymmetries, datafication processes and extractive conditions imposed on users, different scholars have emphasized the need for educational initiatives that foster forms of critical digital literacy. This article explores how critical pedagogical approaches can be embedded into research and teaching practices to support the analysis of everyday media experiences. Specifically, we discuss four case studies drawn from our prior and ongoing research on youth: (i) the use of autoethnographic diaries; (ii) the constitution of youth juries; (iii) the development of a critical digital literacy educational manual; (iv) the implementation of interactive workshops. We contend that these interventions share three key elements, i.e., a critical theory stance, a qualitative orientation, and the cultivation of situated knowledge, the intertwinement of which can promote instances of critical awareness and reflexivity, challenging the individualism and resignation frequently characteristic of contemporary digital life. We use this set of cases to offer a practical, multi-level approach for researchers and educators, showing how the theoretical principles of critical pedagogy can be put into concrete practices, addressing critical digital literacy across different levels. Full article

The value of electronic waste as an urban mine has been extensively demonstrated, particularly regarding its rich content in precious metals. However, little is known about the economic feasibility in informal recovery contexts like in Burkina Faso. Previous studies were focused on formal and industrialized systems, overlooking informal dynamics in low-income countries. This study addressed that gap by applying a scenario-based Extended Cost–Benefit Analysis to assess metal recovery pathways in Burkina Faso. Six scenarios were modeled, combining technological selectivity, variations in local collection costs, and policy incentives such as Extended Producer Responsibility and eco-taxes as well as socio-environmental co-benefits. Results showed that e-waste recovery in the informal sector became economically viable when technological, financial, and policy instruments were combined. At a reduced e-waste cost of 5 USD/kg, manual dismantling and bioleaching technologies allowed for net benefits of 6.34 and 6.85 USD/kg, respectively, corresponding to improvements of 136% and 133% compared to baseline losses. Even at 10 USD/kg, both methods remained viable with positive returns and benefit–cost ratios above 1.06. It is impossible to generate net benefits with an e-waste purchase price of 10 USD/kg without EPR or eco-tax mechanisms, unless the price is reduced to 5 USD/kg; this could impose enormous constraints on collection activities. These findings confirmed that no single factor is sufficient to achieve profitability, highlighting the need to integrate supportive policies, technological appropriateness, and environmental co-benefits, a combination that aligns with circular economy principles and is essential to unlock the full potential of e-waste recovery in low-income countries. Full article

Saffron (Crocus sativus L.), a perennial plant of the Iridaceae family, which is also known as “red gold”, is one of the most expensive spices throughout the world. Originally, it was mainly used as a condiment and natural dye for food, and as a medicinal plant in folk medicine. Its cultivation is characterized by an extensive use of labor, since most of the crop management techniques (e.g., sowing, weeding, flower picking, and stigma separation) are performed manually. The aim of this work is to investigate how the adoption of sustainable cultivation techniques could improve the profitability of saffron at the primary level. Thus, economic and technical data were collected directly on a farm in a marginal area in Northwestern Italy, in order to compare the productivity and profitability of traditional and innovative cultivation techniques. The effect of sustainable practices, such as the use of beneficial microorganisms, that is, arbuscular mycorrhizal fungi (AMF), on the productivity of saffron was considered. In a previous work, AMF inoculation with Rhizophagus intraradices and Funneliformis mosseae led to an increase in the flower and saffron spice yields, compared to uninoculated controls. The profitability of the saffron (including tepals, its by-product) considered in our case study, expressed as economic profit (pure profit), was found to be slightly negative for the traditional cultivation method (without the use of AMF) and also, albeit to a lesser extent, for the innovative technology (with the use of AMF). This slightly negative result is mainly due to the implicit cost of family labor for both the traditional and innovative cultivation techniques. The results of our study can be considered a further step in favor of the use of cultivation techniques that improve crop productivity and, at the same time, are sustainable. They also support the spread of minor crops, which, nevertheless, are important to maintain agricultural activities in marginal territories. Full article