Search Results (2,299)

Electrically conductive cement-based composites exhibit significant potential for a range of multifunctional applications. Nonetheless, the electrical and mechanical performance of ductile cement-based composites incorporating compound conductive additives has not been sufficiently explored. This study examines the effects of two distinct carbon-based fillers, namely carbon black and chopped carbon fibers, on strain-hardening cementitious composites (SHCC), and elucidates the synergistic mechanism of hybrid conductive fibers and fillers within SHCC. The findings indicate that a sufficiently high electrical conductivity can be achieved by incorporating 5 wt.% carbon black and 0.2–0.4 vol.% carbon fibers. The introduction of hybrid carbon-based fillers reduces the resistivity of SHCC by three orders of magnitude to less than 150 Ω∙cm, surpassing the performance of composites with a single carbon-based filler. Furthermore, the incorporation of hybrid carbon-based fillers and fibers enhances the compressive and flexural strength of cementitious composites. Compared to the referenced PE-SHCC, the tensile strength and strain of SHCC with 5 wt.% carbon black and 0.4 vol.% carbon fibers increased by 37.3% and 82.6%, respectively. A hybrid efficiency index (HEI) is proposed to assess both electrical conductivity and mechanical properties of SHCC incorporating with carbon-based fillers. The study’s findings offer an effective approach for utilizing hybrid carbon-based conductive fillers in the multifunctional applications of SHCC. Full article

This study examines decision-making in intelligent virtual agents (IVAs) and formalizes the distinction between tactical decisions (individual actions) and strategic decisions (composed of sequences of tactical actions) using a mathematical model based on set theory and the Bellman equation. Although the equation itself is not modified, the analysis reveals that the discount factor (γ) influences the type of decision: low values favor tactical decisions, while high values favor strategic ones. The model was implemented and validated in a proof-of-concept simulated environment, namely the Snake Coin Change Problem (SCCP), using a Deep Q-Network (DQN) architecture, showing significant differences between agents with different decision profiles. These findings suggest that adjusting γ can serve as a useful mechanism to regulate both tactical and strategic decision-making processes in IVAs, thus offering a conceptual basis that could facilitate the design of more intelligent and adaptive agents in domains such as video games, and potentially in robotics and artificial intelligence as future research directions. Full article

In the background of electricity market reform, combined heat and power (CHP) units must balance electricity market revenues with reliable heat supply. However, the flexibility of CHP units to confront various features of renewable outputs remains to be explored more thoroughly. In this study, day-ahead electricity price curves are classified into four typical categories adopting k-means clustering, featured by diverse temporal trends associated with the output of renewables. An integrated model—capturing the CHP, the battery energy storage system (BESS), and heating network dynamics—supports day-ahead operational optimization. The results suggest that distinct operational strategies are to be implemented under different price profiles. Moreover, incorporating a BESS and exploiting thermal inertia of the network expands arbitrage opportunities and profit from the electricity market. Lastly, an alternation in the operational goal of CHP units is proposed, namely, from thermal-economy-guided to comprehensive-economy-oriented. Comparative results underscore the benefits of the revised strategies. Full article

The correct identification of historical artists’ earth pigments is mandatory for cultural, scholarly, and historical applications. This paper focuses on the definition of the distinctive mineralogical, geological, and geochemical properties and the discussion of the geological genesis and place of origin of the natural Fe-Mn-based earth pigment named terra d’ombra (umber). It one of the dark-brown earth pigment most widely used by Italian and European painters from the Renaissance to the nineteenth century. The terra d’ombra earth pigment is a primary chemical sediment mainly composed of Fe (oxy)hydroxide and Mn oxide, produced by the authigenic precipitation from oceanic or lacustrine waters rich in metal solutes of volcanic hydrothermal origin. The principal areas of provenance are the island of Cyprus and the Monte Amiata volcano (southern Tuscany, Italy). Its peculiar properties in painting derive from this specific mineralogical composition and genetic process, which also exclude its definition as a particular type of ochre and as a clay pigment. Further misinterpretations include confusion with pigments composed of organic materials and the erroneous attribution of the name and area of origin to the Italian region of Umbria. Full article

In medical diagnostics and decision-making, particularly in dentistry where structural interpretation of radiographs plays a crucial role, accurate image segmentation is a fundamental step. One established approach to segmentation is the use of clustering techniques. This study evaluates the performance of five clustering algorithms, namely, K-Means, Fuzzy C-Means, DBSCAN, Gaussian Mixture Models (GMM), and Agglomerative Hierarchical Clustering for image segmentation. Our study uses two sets of real-world dental data comprising 140 adult tooth images and 70 children’s tooth images, including professionally annotated ground truth masks. Preprocessing involved grayscale conversion, normalization, and image downscaling to accommodate computational constraints for complex algorithms. The algorithms were accessed using a variety of metrics including Rand Index, Fowlkes-Mallows Index, Recall, Precision, F1-Score, and Jaccard Index. DBSCAN achieved the highest performance on adult data in terms of structural fidelity and cluster compactness, while Fuzzy C-Means excelled on the children dataset, capturing soft tissue boundaries more effectively. The results highlight distinct performance behaviours tied to morphological differences between adult and pediatric dental anatomy. This study offers practical insights for selecting clustering algorithms tailored to dental imaging challenges, advancing efforts in automated, label-free medical image analysis. Full article

Developing vehicle classification remains a fundamental challenge for intelligent traffic management in the Indian urban environment, where traffic exhibits high heterogeneity, density and unpredictability. In the Indian subcontinent, vehicle movement is erratic, congestion is high, and vehicle types vary significantly. Conventional global benchmarks often fail to capture these complexities, highlighting the need for a region-specific dataset. To address this gap, the present study introduced the EAHVSD dataset, a novel real-world image collection comprising 10,864 vehicle images from four distinct classes, acquired from roadside surveillance cameras at multiple viewpoints and under varying conditions. This dataset is designed to support the development of an automatic traffic counter and classifier (ATCC) system. A comprehensive evaluation of eleven state-of-the-art deep learning models, namely VGG16, VGG19, MobileNetV2, Xception, AlexNet, ResNet50, ResNet152, DenseNet121, DenseNet201, InceptionV3, and NASNetMobile, was carried out. Among these, the highest accuracy result has been achieved by VGG-16, MobileNetV2, InceptionV3, DenseNet-121, and DenseNet-201. We developed a stacking-based meta-ensemble framework to leverage the complementary strengths of its components and overcome their individual limitations. In this approach, a meta-learner classifier integrates the predictions of the best-performing models, thereby improving robustness, scalability, and real-world adaptability. The proposed ensemble model achieved an overall classification accuracy of 96.04%, a Cohen’s Kappa of 0.93, and an AUC of 0.99, consistently outperforming the individual models and existing baselines. A comparative analysis with prior studies further validates the efficacy and reliability of the stacking-based meta-ensemble method. These findings position the proposed frameworks as a robust and scalable solution for efficient vehicle classification under practical surveillance constraints, with potential applications in intelligent transportation systems and traffic management. Full article

Existing experiments have shown that in Al-Zn-Mg-Cu alloys, solute Cu, when substituting for Al atoms, can enter the interior of ${\eta }^{\prime }$ precipitate, changing its composition significantly, but the mechanical properties of the ${\eta }^{\prime }$ compound containing dissolved Cu has not yet been explored. In this study, we conducted a theoretical prediction to investigate the effect of dissolved Cu on the mechanical properties of the ${\eta }^{\prime }$ compound (Al₄Mg₂Zn₃). The results indicate that Cu, substituted for Al, tends to reduce the volume, increase the hardness, and raise the Debye temperature of the ${\eta }^{\prime }$ crystal. Although dissolved Cu weakly increases the brittleness of the crystal, the ${\eta }^{\prime }$ still retains its ductile nature. Additionally, we simulated the surface structure of the (0001) surface and discovered that there are five distinct surface terminations, namely Al1, Al2, Mg1, Mg2, and Zn. Exact calculations reveal that the surface energies of different terminations are influenced not only by the electronic structure of the surface atoms but also by the distance between the surface layer and the sub-surface layer of the corresponding surface supercell. Full article

The potential of invasive plants to serve as reservoirs for plant pathogenic fungi has been confirmed, but studies examining the seasonal effects on the community structure and transmission patterns of leaf pathogens within invasive plant populations remain scarce. In this study, we characterised the seasonal dynamics of pathogenic fungal communities in the leaf tissue of the invasive plant A. adenophora via culture-dependent and culture-independent methods. The study confirmed that fresh leaves of A. adenophora accumulate diverse pathogenic fungi, including Colletotrichum, Epicoccum, Toxicocladosporium, Mycosphaerella and Didymella. These genera are globally distributed and act as pathogens for a wide range of wild plants and economic crops. The pathogenic fungal communities exhibited seasonal dynamics, though the magnitude of change was less pronounced than that of the overall fungal community. Among four common environmental factors, namely, temperature, relative humidity, wind speed and precipitation, temperature had a greater effect on the overall community than the other environmental factors, whereas precipitation had the least effect. However, relative humidity has the strongest effect on the pathogenic fungal community; moreover, relative humidity distinctively affects the same species occurring in different microenvironments. Most foliar pathogenic fungi are actively transmitted in spring and autumn, and very few genera can transmit across all seasons. Moreover, most fungal genera can transmit from fresh leaves to dead leaves, suggesting that most foliar fungal pathogens associated with A. adenophora are likely necrotrophic. Our study strongly confirms the potential of the invasive plant A. adenophora to act as a reservoir of pathogenic fungi and provides preliminary insights into their potential transmission patterns. These findings underscore that, under suitable climatic and environmental conditions, A. adenophora may pose a latent risk of triggering disease transmission within ecosystems. Full article

This article undertakes a cross-cultural comparative inquiry into the motif of “women’s weaving” in medieval Daoism and Christianity. Although the two traditions developed with minimal historical contact, both elevate women’s textile labor into a central metaphor for cosmogenesis, sacred order, and individual salvation. Nevertheless, their hermeneutic trajectories diverge in essential ways. Working within a tripartite analytical framework (intellectual roots, artistic images, ritual practices) to argue that Daoism interprets “women’s weaving” as a proactive technique of transformation and nurture, based on a cosmology of immanent huasheng lun. In this reading, the image is affiliated with the cosmic creativity of nüxian, the inner transformation of their body, and the autonomous pursuit of transcendence. By contrast, within Christianity’s transcendent theological horizon of creatio ex nihilo, “women’s weaving” is configured primarily as an ethical discipline of responsive obedience, closely tied to the mystery of the Incarnation, the imitatio Dei, and communal spiritual exercises and charity under monasticism. The cross-cultural resonance of this motif, I contend, is grounded in the “men’s ploughing and women’s weaving” economic formation, patriarchal gender order, and shared symbolic cognition; its decisive bifurcation arises from contrasting deep cultural structures—namely, cosmology, conceptions of the body, soteriology, and church–state arrangements. Through this micro-case, the article further argues that the sacralization of secular gender roles constitutes an agentic cultural choice, one that indexes distinct civilizational pathways in understanding creation, nature, the body, and freedom. Full article

The complex microbiota of cheese starters plays a key role in determining the structure and flavour of the final product, primarily through their acid-forming capacity, protease activity, and exopolysaccharide synthesis. However, the specific microbial communities underlying the unique qualities of artisanal cheeses remain poorly understood. This study presents the microbiological and molecular genetic characterisation of the microbiome isolated from an artisanal cheese starter in Kosh-Agach, Altai, Russia. Metagenomic analysis of this starter revealed the presence of three bacterial genomes corresponding to those of Lactococcus lactis. Pure cultures from this starter were obtained by sequential subculture, and seventeen colonies displaying distinct characteristics on differential media were selected. Genome sequencing was performed for each colony. Bioinformatic analysis based on the rpoB gene grouped the isolates into three clusters, each corresponding to a distinct strain of Lactococcus lactis subsp. diacetilactis. This classification was further confirmed by microbiological and microscopic analyses. A notable finding was that none of the strains produced the characteristic aroma compounds of L. l. subsp. diacetilactis, namely, diacetyl and CO₂. The functional properties and metabolic characteristics of this starter consortium are discussed. Full article

The propagation of interfacial acoustic waves (IAWs) along a SiO₂/ZnO/SU-8/SiO₂ multilayer structure is theoretically predicted and experimentally validated. A two-dimensional finite-element analysis was performed using COMSOL Multiphysics, revealing that key IAW characteristics—such as the number of supported modes, propagation losses, and acoustic field distribution—are strongly influenced by the thickness of the intermediate SU-8 adhesive layer. In particular, the presence of the SU-8 layer enables the existence of IAW modes with opposite localization, namely upward- and downward-propagating IAWs. To validate the theoretical predictions, experimental measurements were carried out on delay lines fabricated on SiO₂/ZnO/SU-8/SiO₂ layered structures, revealing the propagation of three distinct IAW modes. The first two modes correspond to the downward and upward fundamental IAWs, while the third mode is a second-order mode identifiable as a downward leaky IAW (LIAW). The experimental results show excellent agreement with the theoretical predictions and establish a solid foundation for the future development of multifrequency IAW-based devices, including package-less acoustic components, microfluidic platforms, and gas and optical sensors designed for operation under harsh environmental conditions. Full article

The taxonomy of Tettigometra Latreille, 1804 s.l. (Hemiptera, Tettigometridae, Tettigometrini) has long remained unstable due to weak diagnostic characters, conflicting interpretations, and frequent misidentifications. Based on extensive examination of the illustrated literature and major museum collections, a new generic framework is proposed, relying primarily on comparative analyses of male genital morphology (particularly the mediodorsal aedeagal process and paired ventral anal processes) while external morphology alone is shown to be unreliable for stable delimitation. In discussing the need for a taxonomy that is both phylogenetically grounded and operational, allowing reliable identifications, preserving compatibility with past determinations despite the lack of molecular evidence, and remaining flexible enough to accommodate future results, we recognize two informal taxonomic groups and fourteen genera. The tettigometrinan group includes Tettigometra, Brachyceps, Metroplaca, Mimarada, Mediodentometra gen. nov., and Persiametra gen. nov.; the apexometrinan group includes Apexometra gen. nov., Erratometra gen. nov., Eurychila, Hystrigonia, Micracanthometra gen. nov., Mitricephalus, Stirometra, and Macrometrina. Following a conservative and operational taxonomic approach, we refrained from describing new species or accepting unsubstantiated synonymies, preferring to retain potentially distinct forms as provisionally valid species pending molecular confirmation. Each taxon is listed with its taxonomic and nomenclatural status, diagnosis, species composition, and distribution. Problematic taxa and misapplied names are clarified, and a key to genera is provided. Full article

Background/Objectives:Pereskia aculeata and Pereskia grandifolia belong to the Cactaceae family, despite their foliar and woody stem characteristics. Both species are commonly known as Ora-pro-nóbis (derived from Latin, meaning “pray for us”), a name rooted in their historical use in colonial Brazil due to their nutritional value, particularly P. aculeata, which is frequently described as a high-protein food source. The goal of the present study was to compare these species based on phytochemical composition and antioxidant capacity. Methods: Both species were investigated for their chemical antioxidant properties (DPPH and phosphomolybdenum complex) and cellular anti-ROS activity using the CACO-2 cell line. A comprehensive phytochemical analysis was performed using LC-MS and GC-MS. Results: P. aculeata exhibited a more abundant content of phenolics and flavonoids, with greater structural variability in phenolic compounds and glycosylated flavonoids than P. grandifolia. Still, P. aculeata showed a more potent chemical antioxidant effect. By contrast, in P. grandifolia, a series of novel saponins was now discovered and characterized. In addition, the compounds from this species exhibited a greater cellular antioxidant activity than those of P. aculeata. Tryptophan-derived alkaloids, such as abrine (N-methyltryptophan), were present in both species, but hypaphorine only in P. aculeata. Conclusions: Both species of Pereskia exhibit potential health benefits, including distinct antioxidant activity, among other unexplored effects, given their significant variability in phytochemicals. These differences could be investigated in greater depth using combined LC-MS and GC-MS, thereby enabling more confident structural investigations of these natural compounds. Full article

Carboxyxanthones containing carboxylic acid groups linked to lipophilic aromatic rings resemble the key pharmacophoric features of many nonsteroidal anti-inflammatory drugs (NSAIDs). This structural similarity makes them attractive scaffolds for the development of new anti-inflammatory agents. This study describes the production, cytocompatibility, and anti-inflammatory potential of ten carboxyxanthones (1–10) and two intermediates (11–12) by evaluating their effects on key pro-inflammatory mediators, namely interleukin 6 (IL-6) and prostaglandin E2 (PGE₂). As these compounds are produced by distinct mechanisms, their multi-target potential will be evaluated. Carboxyxanthones were obtained by multi-step pathways using different synthetic approaches through classical benzophenone or diaryl ether intermediates synthesis followed by intramolecular acylation. To the best of our knowledge, the synthesis of carboxyxanthones 3 and 5 is described herein for the first time. All tested compounds were cytocompatible with lipopolysaccharide (LPS)-stimulated macrophages. The most notable carboxyxanthones were 3, 4, 7, and 8, which were able to significantly reduce IL-6 production by approximately 60%. Molecular docking simulations between compounds 1–12 and cyclooxygenase-2 were conducted to characterize the structural features underlying molecular recognition, and to identify the most promising candidates for subsequent PGE₂ assays. Carboxyxanthones 3, 5, and 6, as well as intermediate 12, were predicted to be the best. In the human in vitro inflammation model used, carboxyxanthone 6 exhibited the most potent and consistent inhibitory effect on PGE₂ production. At the highest concentration tested (100 µM), it presented an efficacy comparable to that of celecoxib. Carboxyxanthones 3 and 5 demonstrated a biphasic effect, decreasing and increasing PGE₂ production at lower (5, 12.5, and 25 µM) and higher (50 and 100 µM) concentrations, respectively. These results highlight the potential of carboxyxanthones as promising modulators of inflammatory pathways, paving the way for further studies aimed at elucidating their mechanisms of action, optimizing structural features, and assessing their safety and therapeutic potential in relevant disease models. Full article

Building on prior work, this study examined cognitive profiles of children with reading disabilities (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity (ADHD + RD) compared to typically developing (TD) peers. Participants included 151 Grade 1–3 students, where there were 31 students with RD, 43 with ADHD, 27 with ADHD + RD, and 50 TD in China. Children were assessed in four cognitive domains: attention, inhibition, working memory, and rapid automatized naming (RAN), with age statistically controlled. Significant group differences emerged in each domain. The TD group consistently outperformed all groups. The comorbid ADHD + RD group showed pronounced deficits in attention, inhibition, and RAN. One-way ANCOVAs and multivariate analyses indicated that both RD and ADHD groups showed weaknesses in attention and RAN, with RD group weaker in working memory and ADHD group in inhibition. A 2 × 2 factorial ANCOVA confirmed significant main effects of RD and/or ADHD across domains, with no significant interaction effects, supporting an additive model. Findings highlight distinct and overlapping cognitive challenges associated with RD and ADHD and underscore the need for domain-specific intervention planning. Full article