Search Results (180)

Neutron capture reactions are the main contributors to the synthesis of heavy elements through the s-process. ²²Ne$(\alpha ,\mathrm{n})$²⁵Mg is the main neutron source in stars, together with ¹³C$(\alpha ,\mathrm{n})$¹⁶O. At energies ${\mathrm{E}}_{\mathrm{cm}}$ < 700 keV, limited data are available, i.e., reaction cross-section upper limits from direct experiments and highly uncertain estimates from indirect sources exist. The ERC project SHADES is currently performing direct cross-section measurements at these energies. We will present details on the ongoing experiment and discuss target characteristics, experimental backgrounds, and preliminary analyses on the detector efficiency and the 832 keV resonance. Full article

Non-fungible tokens (NFTs) are transforming the commercialisation of digital art by establishing unique blockchain identifiers that ensure authenticity and certify subsequent transactions. However, the transfer of control over an NFT does not automatically include the transfer of the associated copyrights, thereby creating legal uncertainty as to what rights are actually acquired. This interdisciplinary project between engineering and law proposes the design of a smart contract, based on the ERC-721 standard, to manage the transfer of property rights linked to digital artworks represented as NFTs. The accompanying legal contract incorporates essential clauses covering the identification of the parties, a description of the artwork and its link to the token, pricing, royalties, and the terms of rights transfer. The proposal seeks to integrate blockchain technology with existing legal frameworks, offering an innovative solution that strengthens legal certainty in the transfer of copyright within digital environments. Full article

Document authentication remains a pressing challenge in various domains, including financial services, academic credentialing, healthcare, and supply chain management. Existing centralized verification systems are vulnerable to manipulation, inefficiency, and limited transparency. Blockchain technology, with its immutability and tamper-resistant capabilities, offers a strong decentralized alternative; however, many current implementations lack structured, issuer-bound relationships for documents. This paper proposes a blockchain-based model that leverages a hierarchical token structure to authenticate and trace the provenance of high-value digital documents, with a focus on financial records. The model introduces the concept of an issuer-bound parent token and document-linked child tokens, enforcing a structured trust relationship between a legitimate institution and the documents it issues. By combining on-chain cryptographic hashing with off-chain file references, the approach is designed to balance verifiability with scalability. We implement a proof-of-concept using Ethereum-compatible smart contracts on a permissioned blockchain and evaluate it in a consortium-style financial setting. Our functional analyses demonstrate the model’s ability to ensure document integrity, provenance, and resistance to document fraud. This work offers a practical and extensible foundation for secure digital document authentication and verification in financial and other trust-sensitive settings. Full article

Multimodal Emotion Recognition in Conversation (ERC) has attracted attention as a key technology in human–computer interaction, mental healthcare, and intelligent services. However, deploying ERC in real-world settings remains challenging due to reliability gaps across modalities, instability in visual representations, and the high computational cost of large pretrained models. In particular, on resource-constrained edge devices, it is difficult to reduce model size and inference latency while preserving accuracy. To address these challenges, we jointly propose a knowledge-distillation-based multimodal ERC model, called DDVLM, with an edge-optimized Weight-Only Quantization (WOQ) pipeline for efficient edge deployment. DDVLM assigns the textual modality as the teacher and the visual modality as the student, transferring emotion-distribution knowledge to improve non-verbal representations and stabilize multimodal learning. In addition, Exponential Moving Average (EMA)-based self-distillation enhances the consistency and generalization capability of text features. Meanwhile, the proposed WOQ pipeline quantizes linear-layer weights to INT8 while preserving precision-sensitive operations in mixed precision, thereby minimizing accuracy loss and reducing model size, memory usage, and inference latency. Experiments on the MELD dataset demonstrated that the proposed approach achieves state-of-the-art performance while also enabling real-time inference on edge devices such as NVIDIA Jetson. Overall, this work presents a practical ERC framework that jointly considers accuracy and deployability. Full article

Background and Objectives: The aim of this study is to evaluate impulsivity in childhood anxiety disorders and to examine its relationship with anxiety sensitivity and emotion regulation. Materials and Methods: The study group consisted of a total of 60 children aged 8–12 years diagnosed with generalized anxiety disorder (GAD, n = 30) and other anxiety disorders (n = 30). The control group consisted of 40 healthy children of similar age without a psychiatric diagnosis. Data collection forms included the Barratt Impulsiveness Scale Short Form (BIS-S), the Children’s Anxiety Sensitivity Index (ASI-3), the Emotion Regulation Checklist (ERC), and The Screen for Child Anxiety Related Emotional Disorders (SCARED). Results: Our study found no significant differences in BIS-S scores between GAD, other anxiety disorders, and the control group. The total/physical and ERC subscales of the ASI-3 were higher in the generalized anxiety disorder and other anxiety disorder group than in the control group. However, there were no significant differences in the social dimension and cognitive dimension scores of the ASI-3. It has been determined that anxiety sensitivity does not significantly mediate the relationship between emotion regulation and impulsivity, and that emotional variability/negativity is directly and completely related to impulsivity. Conclusions: Our study suggests that children with anxiety disorders experience greater difficulties in regulating their emotions compared to healthy children, and that emotional variability is directly related to impulsivity. In this context, enhancing emotion regulation skills in anxiety disorders may prove to be a pivotal factor in the efficacy of treatment and the maintenance of behavioral control. Full article

Background/Objectives: Sleep problems and physical activity are key lifestyle behaviors associated with children’s socioemotional development. However, their relative contribution to emotional regulation and emotional instability during middle childhood remains insufficiently clarified. This study aimed to examine the associations between sleep problems, habitual physical activity, and emotional regulation in elementary school children, while controlling for sociodemographic and lifestyle confounding variables. Methods: A cross-sectional study was conducted with 386 elementary school children (mean age = 11.15 ± 0.66 years; 45.6% boys) from southern Spain. Emotional regulation was assessed using the Emotion Regulation Checklist (ERC), sleep problems were measured with the Children’s Sleep Habits Questionnaire (CSHQ), and habitual physical activity was evaluated using the Physical Activity Questionnaire for Children (PAQ-C). Age, sex, socioeconomic status, and daily screen time were included as covariates. Pearson correlations and multiple linear regression analyses were performed. Results: Sleep problems were strongly associated with lower adaptive emotional regulation and higher emotional lability. In adjusted regression models, sleep problems emerged as the most robust independent predictor of both emotional regulation and lability. Although habitual physical activity was significantly associated with emotional outcomes at the bivariate level, its predictive strength decreased after adjustment for covariates and did not independently predict adaptive emotional regulation. Conclusions: Sleep problems appear to play a central role in children’s emotional functioning during middle childhood. Interventions aimed at promoting socioemotional well-being may benefit from prioritizing sleep health alongside physical activity within a comprehensive 24 h movement behavior framework. Full article

Background/Objectives: Malignant mesothelioma has a poor prognosis and limited therapeutic options. C-ERC/mesothelin is highly expressed in mesotheliomas and is a potential target for radioimmunotherapy (RIT). This study evaluated the radiolabeled anti-C-ERC/mesothelin antibody mAb 22A31 as a therapeutic agent. Methods: C-ERC/mesothelin expression in mesothelioma cell lines was assessed by Western blotting, and the specific binding of ¹²⁵I-labeled mAb 22A31 was examined. Biodistribution of ¹¹¹In-labeled mAb 22A31 was evaluated in a mesothelioma cell line, MSTO-211H tumor-bearing mice. The therapeutic efficacy of ⁹⁰Y-labeled mAb 22A31 was evaluated in subcutaneous and pleural dissemination models. Results: mAb 22A31 showed specific binding considering the level of C-ERC/mesothelin expression in each mesothelioma cell line. ¹¹¹In-mAb 22A31 accumulated in tumors with minimal uptake in normal tissues. ⁹⁰Y-mAb 22A31 significantly delayed the growth of subcutaneous tumors and improved survival in a pleural dissemination model. Conclusions: Radiolabeled mAb 22A31 specifically targeted C-ERC/mesothelin and demonstrated therapeutic efficacy in a mesothelioma xerograph model. Therefore, ⁹⁰Y-mAb 22A31 is a promising RIT agent and supports the further development of C-ERC/mesothelin-targeted therapy for mesothelioma. Full article

This study aimed to prepare experimental calcium silicate repair cements (ERCs) incorporating zirconium (Ca₃ZrSi₂O₉; CZS) or strontium substitution (Sr₅(PO₄)₂SiO₄; SPS), and to compare their physicochemical properties with white MTA-Angelus (WMTA), grey MTA-Angelus (GMTA), and Biodentine (BD). After synthesizing the CZS and SPS phases, powder–liquid cements were formulated. The setting time and radiopacity were assessed according to ISO 6876/12 and ASTM C266, the volumetric solubility by micro-CT, the pH by a pH meter, and the calcium/strontium ion release by FAAS/ICP-OES. Data were analyzed using ANOVA and Tukey’s tests (5%). The initial setting time was 11 min for SPS and 6 min for CZS (p < 0.05), while the final setting was significantly longer for SPS (49 min). Both ERCs showed radiopacity above the 3.0 mm Al minimum, with higher values for CZS (4.58 mm Al). The solubility remained controlled, with CZS presenting the highest value (3.09%). Both materials exhibited an alkaline pH, peaking at 24 h (CZS: 9.70; SPS: 10.04) and decreasing until 168 h (CZS: 7.80; SPS: 8.31). Sustained ionic release was observed: CZS showed intermediate calcium release (25.96 mg/L at 3 h), whereas SPS displayed lower values (10.95 mg/L at 168 h), without significant difference from WMTA (p > 0.05). Under these conditions, the experimental ERCs demonstrated adequate physicochemical performance comparable with commercial materials. Full article

Recently, epoxy resin concrete (ERC) has shown significant potential in rapid repair applications, such as bridge expansion joints, owing to its early strength gain, rapid hardening, excellent adhesion, and durability. Based on the background of rapid repair scenarios for small- and medium-span bridges, this study designed a mix proportion of ERC. A systematic investigation was conducted on its mechanical properties and constitutive model under various curing temperatures (5 °C, 20 °C, and 35 °C) and ages. Experimental results indicate that the designed ERC cures within 2 to 6 h and achieves a compressive strength of 15 MPa at 1 day, meeting the requirement for early traffic reopening. Both material strength and elastic modulus increase significantly with age, reaching a compressive elastic modulus of 16 GPa at 90 days. Based on the measured uniaxial compressive and tensile stress–strain data, a temperature-dependent constitutive model was established. The fitting parameters exhibit a quadratic functional relationship with curing temperature. The model demonstrates high fitting accuracy under all tested conditions (R² ≥ 0.9293). This study provides a theoretical basis and data support for the application and numerical simulation of ERC in bridge engineering. Full article

Background: Bucket-wheel excavators are critical assets in surface mining operations, where structural modifications to increase productivity must be validated through rigorous stress analysis to ensure operational safety. Following modification of an ERc 1400-30/7 excavator’s bucket wheel from 18 to 20 buckets, increased operational loads necessitated experimental verification of structural integrity. Methods: A custom 10-channel strain-gauge data acquisition system with 0–10 kHz bandwidth measured stresses in cable anchoring lugs and H-type diagonal members under operational conditions at the Jilț lignite mine, Romania. Measurements were performed during both left and right bucket-wheel rotation. Finite element analysis validated experimental results. Results: Maximum equivalent stresses of 210.0 MPa and 167.1 MPa were measured in the left and right anchoring lugs, respectively, during left bucket-wheel rotation, representing 59% and 47% of material yield strength with safety factors of 1.69 and 2.12. Significant load asymmetry was observed, with left rotation inducing 220–284% higher stresses than right rotation. FEA validation showed <15% agreement with measurements. Dynamic stress amplification of 15–32% above quasi-static values was attributed to bucket–soil interaction and structural vibration. Conclusions: Despite increased operational loads, measured stresses remain below yield strength, confirming structural adequacy. Both anchoring lugs require prioritized monitoring due to elevated stress levels and load asymmetry. The validated methodology provides a framework for post-modification verification of large mining equipment. Full article

Asbestos, a group 1 carcinogen, has generated a serious health and environmental liability in Pedro Leopoldo/MG, Brazil, even after its national ban in 2017. This study aims to analyze the silent epidemic of asbestos-related diseases (ARDs) through the lens of social injustice. We used a qualitative, socio-historical, and clinical approach within the framework of an Expanded Research Community (ERC), based on ergology, with content analysis of interviews with workers and institutional documents. The evidence reveals a pattern of institutional silencing and omission, marked by corporate fraud, denial of risk, and medical underreporting, perpetuating occupational, domestic, and environmental exposure. In response, the Brazilian Association of Asbestos-Exposed Individuals of Minas Gerais (ABREA/MG) emerged as a central actor in the struggle for recognition and justice. It is concluded that overcoming this injustice requires structured public policies of recognition, integrated surveillance, historical reparation, and strengthening of the SUS (Unified Health System), with collective resistance being fundamental to transforming suffering into memory and social demands. Full article

The Earnings Response Coefficient (ERC) has emerged as a pivotal topic in academic literature and financial practice, elucidating the critical relationship between corporate earnings information and market response, which directly impacts corporate performance evaluation and investment decision-making. This study aims to identify the most frequently researched topics in the Earnings Response Coefficient domain, explore the basic concepts and theoretical frameworks underlying ERC research, and propose potential future research directions in the field, all within finance and investment management. This research employs bibliometric analysis to use data from Google Scholar and Scopus, accessed through Publish or Perish (PoP), to evaluate the literature’s performance, explore related topics, and identify research trends, thereby deepening the understanding of ERC studies. The findings reveal that income smoothing and intellectual capital disclosure have a significant impact but low connectedness, indicating a need for deeper exploration to heighten their relevance in ERC studies. Research on corporate social responsibility exhibits a high degree of interconnectedness and substantial impact. Underexplored topics such as economic uncertainty and analysts’ influence require greater attention to understand their contributions fully. This study identifies publication trends and citation networks related to ERC, provides insights into researcher collaborations, and offers guidance for academics, practitioners, and policymakers to enrich their understanding, develop more effective earnings management strategies, and design regulations that bolster market transparency and efficiency in the realm of finance and investment management. This research is particularly beneficial for practitioners, as it helps evaluate more effective earnings management strategies and understand the market’s response to earnings information, ultimately enhancing firm value. For policymakers, this study provides a framework for designing regulations and policies that support financial information transparency and market efficiency to enhance economic stability and investor confidence. Full article

The accelerating adoption of electric vehicles (EVs) is intensifying pressure on urban power grids, particularly during evening peak hours. Existing smart-charging frameworks remain constrained by centralized control, static pricing, and limited integration of predictive intelligence. This study presents SMARGE, a hybrid AI–Blockchain smart charging platform that combines load forecasting, dynamic pricing, and cryptocurrency-based incentives to enhance decentralized EV energy management in Gaziantep Province. An ensemble of forecasting models (SARIMA, LightGBM, N-BEATS, and TFT) predicts 2026 hourly electricity demand, while an adaptive inverse-sigmoid pricing mechanism generates real-time incentives and disincentives for EV charging behavior. A fuzzy logic-based behavioral model simulates both unmanaged and managed charging across three scenarios. Results show that managed charging reduces peak load by 22.43%, shifts 67.45% of energy demand to off-peak periods, and achieves 94.86% charging fulfillment under constrained grid conditions. The blockchain layer—implemented through a custom ERC-20 token (SMARGE) on the Ethereum Sepolia testnet—enables secure, transparent, and low-cost microtransactions with an average confirmation time of 0.63 s. These findings demonstrate that tightly coupling AI forecasting with tokenized blockchain incentives can improve grid stability, lower operational costs, and enhance user autonomy in a scalable and decentralized manner. While promising, the study is limited by assumptions of synthetic user behavior and ideal communication conditions; future work will validate the platform in real-world pilot deployments and across different urban regions. Full article

Emotion recognition in conversations (ERC) is a significant task in natural language processing, aimed at identifying the emotion of each utterance within a conversation. Current research predominantly relies on pre-trained language models, often incorporating sophisticated network architectures to capture complex contextual semantics in conversations. However, existing approaches have not successfully combined effective task-specific adaptation with adequate modeling of conversational context complexity. To address this, we propose a model named TAMC-ERC (Task-Adaptive and Multi-level Contextual Understanding for Emotion Recognition in Conversations). The model adopts a progressive recognition framework that sequentially builds on foundational utterance representations, integrates conversation-level contexts, and leads to a task-adaptive classification decision. First, the Task-Adaptive Representation Learning module produces highly discriminative utterance representations. It achieves this by integrating emotion space information into prompts and employing contrastive learning. Subsequently, the Multi-Level Contextual Understanding module performs in-depth modeling of the conversational context. It synergistically integrates both macroscopic narratives and microscopic interactions to construct a comprehensive emotional context. Finally, the classifier is directly parameterized by the emotion concept vectors from the task-adaptive stage. This creates a coherent task adaptation process, maintaining task-specific awareness from representation learning through to the final decision. Experiments on three benchmark datasets demonstrate that TAMC-ERC achieves highly competitive performance: it attains weighted average F1 scores of 71.04% on IEMOCAP, 66.95% on MELD, and 40.99% on EmoryNLP. These results set a new state of the art and demonstrate that the model outperforms most existing baselines. This work validates that integrating task adaptation with multi-level contextual modeling is key to addressing conversational complexity and improving recognition accuracy. Full article

Despite growing concerns about the ecological and health risks of nanoplastics at environmentally relevant concentrations (ERCs), the effects of polyurethane nanoplastics (PU NPs) on environmental organisms remain unclear. This study assessed the toxicity of PU NPs in the μg/L range in Caenorhabditis elegans (C. elegans) through chronic exposure. Our results showed that 10 μg/L PU NP exposure significantly reduced brood size, head thrashes, and body bends, while 100 μg/L PU NP exposure decreased lifespan, and 1000 μg/L PU NP exposure increased mortality in wild-type C. elegans. Analysis of oxidative stress showed that both 10 and 1000 μg/L PU NP exposures elevated reactive oxygen species (ROS), SKN-1::GFP, and GST-4::GFP levels. Notably, while ROS production rose at 1000 μg/L, SKN-1::GFP and GST-4::GFP expression decreased compared to the 10 μg/L group, suggesting a compensatory response in C. elegans at lower exposure levels. The expression of oxidative stress-related genes and phenotype of differentially expressed genes indicated that C. elegans was in a compensatory phase when exposed to 10 μg/L of PU NPs, participating in the protective response of C. elegans to PU NPs. However, when exposed to 1000 μg/L of PU NPs, C. elegans was in a decompensatory phase, participating in the toxic regulation of PU NPs. In addition, under 10 μg/L PU NP exposure, cinnamon essential oil (CIEO) can enhance the expression of more antioxidant enzymes, thereby increasing the protective effect. Under 1000 μg/L PU NP exposure, CIEO could alleviate the toxic response of C. elegans to PU NPs exposure by promoting the expression of skn-1. Molecular docking analysis showed that the main active component of CIEO, cinnamaldehyde (CID), has a strong affinity with SKN-1/Nrf2. Our study is the first to emphasize the toxic effects of PU NPs on environmental organisms at ERCs and that CIEO might serve as a potential antidote for nanoplastic poisoning. Full article