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Escitalopram normalizes decreased left inferior frontal gyrus activation in social anxiety disorder during self-referential processing
No full textPublisher Copyright: © 2025 The AuthorsBackground: Social anxiety disorder (SAD) is associated with negatively biased, self-focused attention in social situations. Neural correlates of self-referential processing and effects of selective serotonin reuptake inhibitors (SSRIs) on it remain, however, poorly known. Interestingly, these drugs have been shown to modify brain activation related to negative bias already before symptom relief in major depressive disorder. We hypothesized alteration in self-referential processing and modification of such alteration during short-term use of escitalopram in SAD. Methods: Thirty-eight subjects with SAD and 20 healthy controls were recruited from the University of Helsinki and Aalto University. During baseline fMRI participants categorized positive and negative self-referential adjectives and neutral control words. The SAD group was then randomized to receive either escitalopram 10 mg per day (n = 14) or placebo (n = 17). After one week, the SAD group repeated the categorization task during fMRI. Results: Compared with healthy controls, the SAD group showed weaker response to negative vs. positive adjectives in the left inferior frontal gyrus (p = 0.039). Compared with placebo, this activation increased after a one-week escitalopram treatment (p = 0.042) without any significant change in the State-Trait Anxiety Inventory Y1 scores. Limitations: Relatively small sample size and drop-outs diminished statistical power. Conclusion: SAD may be associated with decreased activation of the left inferior frontal gyrus to negative self-referential social cues. Escitalopram may normalize such activation. As left inferior frontal gyrus has been linked to inner speech while working on self-reflection tasks, the increased activation might relate to reappraising negative social cues.Peer reviewe
Study on the multiple recycling limit of asphalt binders containing high RAP content based on chemical and rheological properties
No full textPublisher Copyright: © 2025 The Author(s)Multiple recycling is an emerging strategy to maximize the use of reclaimed asphalt pavement (RAP), yet the evolution of binder performance during repeated rejuvenation and the feasible recycling limit remain unclear. To clarify this, binders extracted from laboratory-aged mixtures containing 60 % RAP underwent five aging and rejuvenation cycles with a bio-based rejuvenator. The optimal rejuvenator dosage was established based on key rheological indicators, followed by a comprehensive evaluation of chemical properties, rheological behavior, fatigue life, and low-temperature cracking resistance. The results demonstrate that key rheological requirements were satisfied without the need to progressively increase the bio-oil dosage. Despite accumulating asphaltenes, multiple rejuvenation cycles maintained colloidal stability and improved oxidative aging resistance. The low-temperature performance grade (PG) remained stable, while high-temperature performance improved, as Shenoy non-recovered compliance (Snr) decreased by up to 56 % and fatigue life increased by up to 214 % compared to the virgin binder, before both indicators declined in the fifth cycle. All properties, except the creep-rate critical cracking temperature (Tc, m), varied significantly from one cycle to the next. The rise in cracking susceptibility set a practical limit of four recycling cycles. Principal component analysis (PCA) revealed that three cycles provided optimal performance. This work quantifies the recycling limit for high-RAP binders, identifies low-temperature cracking susceptibility as the controlling mechanism, and provides guidance for sustainable pavement practice.Peer reviewe
Phase equilibria and excess enthalpy for tetrahydrofuran + 2-methylpyrazine, tetrahydrofuran + 2-methylpyridine and 2-methylpyridine + 2-methylpyrazine: Experimental measurement and predictive modeling
No full textPublisher Copyright: © 2025 The Author(s)Knowledge about the vapor–liquid equilibrium (VLE) behavior of systems containing 2-methylpyridine or 2-methylpyrazine is limited in the literature, despite their industrial importance. In this study, consistent VLE data for mixtures of tetrahydrofuran + 2-methylpyrazine and 2-methylpyridine + 2-methylpyrazine at 50 and 75 kPa, as well as the system of tetrahydrofuran + 2-methylpyridine at 50, 75, and 101 kPa are presented. The excess molar enthalpy (HE) of these binaries has been measured using an isothermal flow calorimeter at 298.15 K and 101 kPa. The vapor pressure data of the pure components were measured and correlated over the temperature range between 294 and 405 K. The measured VLE and HE data were successfully correlated with NRTL, UNIQUAC, and Wilson activity coefficient models. In addition, the acquired VLE and HE were compared with those predicted by COSMO-RS and different predictive group contribution (GC) based models, including the original UNIFAC, UNIFAC-Dortmund, Volume Translated Peng-Robinson (VTPR) and Predictive Soave–Redlich–Kwong (PSRK). A satisfactory agreement was observed between the calculated results and experimental VLE data for all predictive methods; however, these models exhibited lower accuracy in predicting HE compared to VLE. Attained phase equilibria were checked for thermodynamic consistency using Wisniak's l-W and Van Ness methods. All binaries exhibit nearly ideal behavior.Peer reviewe
Driver gene detection via causal inference on single cell embeddings
No full textDriver genes are pivotal in different biological processes. Current methods generally identify driver genes by associative analysis. Leveraging on the development of current large language models (LLM) in single cell genomics, we proposed a Causal inference based approach to Identify Driver genes (called CID) from scRNA-seq data. Through experiments on three different datasets, we show that CID can (1) identify biologically meaningful driver genes that have not been captured by current associative-analysis based methods, and (2) accurately predict the direction of expression changes in downstream target genes if a driver gene is knocked out. This study presents a resource-efficient in silico framework for identifying key regulatory genes from learned cell embeddings and simulated perturbations, thereby streamlining follow-up experiments and deepening our understanding of how gene-level interventions influence cellular phenotypes and disease.Peer reviewe
Electrically-Driven Polarized Nano-Light Sources Based on Suspended Graphene Nanoscrolls
No full textLow-dimensional nanomaterials hold great promise for on-chip light-emitting applications and are expected to profoundly influence the evolution of next-generation photonic chips. Currently, microlasers and light-emitting diodes represent the predominant on-chip integrated light sources. Exploring how to employ low-dimensional materials to realize more miniaturized and controllable light sources remains a key research focus over the past decade. In this work, we demonstrate a high-efficiency nanolight source (NLS) based on graphene nanoscrolls (GNSs), with its emission modulated via an external electric field and device structural design. The GNS NLS features a widely tunable emission spectrum, covering wavelengths from the infrared to the visible range. Besides, we investigated the super-Planckian radiation effect in GNSs, which arises from enhanced absorption in the low-dimensional nanostructure. The theoretical calculations reveal that the absorption coefficient of GNSs in the normal direction is larger than 1, thereby indicating their strong radiative emission according to Kirchhoff's Law of thermal radiation. Furthermore, the emission from GNSs can exhibit fast switching behavior (response time ∼ 75 ms), with the degree of polarization reaching 20% in the visible light range. This work provides important support for the study of the emission characteristics of GNSs and holds profound significance for promoting the development of on-chip integrated NLS technology.Peer reviewe
A deep learning method to predict ship short-term trajectory for proactive maritime traffic management
No full textPublisher Copyright: © 2025With the rapid growth of global maritime trade and the increasing density of vessel traffic, the risk of ship collisions has become a growing concern, especially in busy and complex waterways. To support proactive maritime traffic management and enhance navigational safety, this paper presents a deep learning-based approach for short-term ship trajectory prediction. Specifically, we propose a multi-scale fusion Temporal Convolutional Network (TCN) that learns vessel movement patterns using data from the Automatic Identification System (AIS). The model captures key motion features—such as trajectory changes, speed, acceleration, turning angles, and rotation rate—to better reflect the dynamic behavior of ships. By combining short-term variations with longer-term trends, the proposed TCN model achieves more accurate and reliable predictions. Experiments on real AIS datasets demonstrate that our method outperforms existing techniques in both accuracy and robustness, particularly in complex coastal environments. This research contributes to smarter traffic control and safer maritime navigation, and supports the development of intelligent maritime systems.Peer reviewe
Automating on-site object inspection with a quadruped robot and BIM
No full textPublisher Copyright: © 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/Deploying robots into construction sites and built environments using Building Information Modeling (BIM) is difficult due to environmental changes and inconsistencies between BIM and real-world structures. To overcome these challenges, an integrated framework is proposed for automated inspection featuring adaptive BIM-driven navigation for a quadruped robot. The framework addresses challenges of localization, mapping, and navigation in challenging environments. By leveraging BIM for initialization and planning, it dynamically verifies BIM elements through sensor data, updating the map to distinguish between fixed structures, missing elements, and dynamic obstacles. This enables robust navigation despite environmental uncertainties. The capability supports automated tasks across the building lifecycle, demonstrated through object inspection using adaptive next-best-view (NBV) planning and vision–language model (VLM) analysis without task-specific training. Both simulated experiments and real-world validation confirm strong performance despite dynamic obstacles and BIM discrepancies. The approach enhances robotic adaptability in construction and facility management contexts while reducing manual inspection requirements.Peer reviewe
Model linking for low-carbon transitions : Technical and conceptual challenges and best practices
No full text| openaire: EC/HE/101056306/EU//IAM COMPACT Publisher Copyright: © 2025 The AuthorsLinking existing models to extend energy system and integrated assessment analysis is an increasingly common practice. Despite this, and unlike in the field of environmental and earth sciences, little attention has so far been paid to the details of it, to the trade-offs involved and the way in which the model linking affects the interpretation of the outcomes of the interlinked model system. Our aim in this paper is to first focus on a set of key technical and methodological problems that are common in model linking and suggest how these could be approached in different model linking contexts. We then further explore how model linking may affect the nature of the knowledge produced, and how this should be considered in the model linking process. Reflecting our literature driven assessment of the issues and possible solutions, we compile “a check list” to assist in the process of decision making for model linking.Peer reviewe
Conditions for breaking the extinction symmetry in electromagnetic scattering
No full textPrevious studies have shown that the extinction efficiency of reciprocal scatterers of arbitrary shape is the same under illumination with plane electromagnetic waves of opposite incident directions with the same field polarizations. It has also been shown that to break this symmetry, all related symmetries, including time-reversal, spatial inversion, and rotational symmetries, should be broken. In this paper, we further investigate the conditions for breaking the extinction symmetry. Our numerical experiments indicate that breaking the time-reversal and geometrical symmetries is not sufficient, rather the object should also be non-reciprocal. However, while non-reciprocity is necessary, it is not sufficient: a certain asymmetry with respect to the incident plane wave is also required. To break the extinction symmetry with these conditions, the polarization of the incident waves has to be linear or elliptical. For circular polarization, the extinction invariance cannot be broken with any geometry or non-reciprocity. Additionally, with characteristic modes, we study and explain the observation that for opposite illumination directions, the electromagnetic fields can be completely different while the corresponding extinction cross-sections coincide.Peer reviewe
Advances in polysaccharide-based food packaging: Functionalization strategies and sustainability considerations
No full textThe food packaging industry generates escalating environmental challenges due to the pervasive use of single-use petroleum-derived plastics, which contribute to climate change, pollution, and microplastic contamination. Polysaccharides have emerged as promising renewable alternatives for food packaging materials. This review critically evaluates recent advances regarding functionalization strategies aimed at improving the mechanical, barrier, and functional properties of polysaccharide-based packaging films. Special attention is paid to chemical modification, blending with bioactive agents, and incorporation of nanomaterials. These strategies significantly enhance the material properties and extend the functionality of polysaccharide-based films, such as antimicrobial, UV-blocking, and pH-indicating capabilities. Life cycle assessment (LCA) and material circularity considerations are provided to compare the environmental sustainability of polysaccharide-based packaging against conventional petroleum-derived plastics, highlighting the environmental trade-offs associated with the adoption of biopolymer-based materials. Additionally, the review critically examines the current limitations and challenges related to scaling up production and achieving cost-effectiveness, thus offering insights into the practical implementation of these materials in the food packaging industry. Finally, key research opportunities are identified, emphasizing the need for further studies to address the challenges of large-scale implementation and cost efficiency in the transition to more sustainable food packaging solutions.Peer reviewe