Search Results (3,576)

By the reaction of AgNO₃, 2-methyl-2-propanethiol (HStBu), with various-sized halogen ions as templates, three multi-nuclear silver-thiolate cluster-based chain-like coordination polymers, [Ag₆(μ-SBu)₆]_n (USC-CP-2), [Ag₆(μ-StBu)₅Br]_n (USC-CP-4) and [Ag₁₄(μ-StBu)₁₂I₂]_n (USC-CP-3) constructed by different Ag(I)-nanocages, have been synthesized and characterized by X-ray diffraction analyses. With F⁻, Cl⁻ or without template, USC-CP-2 exhibits a one-dimensional structure composed of detached Ag₆-cages, absent of fluoride or chloridion. While with Br⁻ and I⁻, USC-CP-4 and USC-CP-3, two distinct halogen-templating multi-sliver cages-based chain-like polymeric structures have been observed, which are a mono-Br⁻ encapsulated Ag₈-cage, or a dual-I⁻ embedded Ag₁₆-cage, respectively. In these three compounds, the multi-Ag(I) cages were self-assembled by Ag-S bonds through bridged μ₂-StBu ligands, and stabilized argentophilic interactions between neighboring silver atoms. This study demonstrates that the halide anions of varying sizes play a critical role in inducing the nucleation and structural evolution of the silver-thiolate clusters. Full article

With growing community awareness of greenhouse gas emissions and their environmental consequences, distributed rooftop photovoltaic (PV) systems have emerged as a sustainable energy alternative in residential settings. However, the high penetration of these systems without effective operational strategies poses significant challenges for local distribution grids. Specifically, the estimation of surplus energy production from these systems, closely linked to complex outdoor weather conditions and seasonal fluctuations, often lacks an accurate forecasting approach to effectively capture the temporal dynamics of system output during peak periods. In response, this study proposes a recurrent neural network (RNN)- based forecasting framework to predict rooftop PV surplus in the context of micro-residential communities over time horizons not exceeding 48 h. The framework includes standard RNN, long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and gated recurrent unit (GRU) networks. In this context, the study employed estimated surplus energy datasets from six single-family detached houses, along with weather-related variables and seasonal patterns, to evaluate the framework’s effectiveness. Results demonstrated the significant effectiveness of all framework models in forecasting surplus energy across seasonal scenarios, with low MAPE values of up to 3.02% and 3.59% over 24-h and 48-h horizons, respectively. Simultaneously, BiLSTM models consistently demonstrated a higher capacity to capture surplus energy fluctuations during peak periods than their counterparts. Overall, the developed data-driven framework demonstrates potential to enable short-term smart energy scheduling in micro-residential communities, supporting electric vehicle charging from single-family detached houses through efficient rooftop PV systems. It also provides decision-making insights for evaluating renewable energy contributions in the residential sector. Full article

This study aims to enhance the efficiency of hydrogen production through alkaline water electrolysis by analyzing hydrogen bubble dynamics using high-speed image processing and machine learning algorithms. The experiments were conducted to evaluate the effects of electrical current and ultrasound oscillations on the system performance. The bubble formation and detachment process were recorded and analyzed using two segmentation models: Ilastik, a GUI-based tool, and U-Net, a deep learning convolutional network implemented in PyTorch. v. 2.9.0. Both models were trained on a dataset of 24 images under varying experimental conditions. The evaluation metrics included Intersection over Union (IoU), Root Mean Square Error (RMSE), and bubble diameter distribution. Ilastik achieved better accuracy and lower RMSE, while U-Net. U-Net offered higher scalability and integration flexibility within Python environments. Both models faced challenges when detecting small bubbles and under complex lighting conditions. Improvements such as expanding the training dataset, increasing image resolution, and adopting patch-based processing were proposed. Overall, the result demonstrates the automated image segmentation can provide reliable bubble characterization, contributing to the optimization of electrolysis-based hydrogen production. Full article

Azole selenoureas exhibit diverse biological functions. However, the synthesis and biological activity of benzothiazole and benzoxazole selenones remained unexplored. Herein, we report the base-catalyzed synthesis of N-difluoromethyl benzothiazole (or benzoxazole) selenone derivatives, which demonstrated significant antifungal efficacy against Rhizoctonia solani, Phytophthora infestans, Botrytis cinerea, and Fusarium oxysporum. Compound 3b exhibited exceptional antifungal activity against R. solani, with an EC₅₀ of 2.10 mg/L. Moreover, it substantially inhibited sclerotia germination (81.5% at 9 mg/L) and formation (79.3% at 9 mg/L), surpassing octhilinone. The protective effect on detached rice leaves and rice seedlings was found to be 43.4% and 85.2% at 100 mg/L, respectively, and 64.4% and 89.4% at 200 mg/L. These findings suggest that benzothiazole and benzoxazole selenones represent promising lead compounds for sustainable plant disease management. Full article

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system. Full article

Background: Intentional occlusion of the internal iliac artery (IIA) during endovascular repair of aorto-iliac aneurysms may predispose patients to pelvic ischemic complications such as gluteal claudication, erectile dysfunction, and bowel ischemia. Iliac branch devices (IBDs) have been developed to preserve hypogastric perfusion. E-Liac (Artivion/Jotec) is one of the latest modular IBDs yet reports on mid-term performance are limited to small single-center cohorts with short follow-up. The CAMpania PugliA bRanch IliaC (CAMPARI) study is a multicenter investigation of E-Liac outcomes. Methods: A retrospective observational cohort study was conducted across five Italian vascular centers. All consecutive patients undergoing E-Liac implantation for aorto-iliac or isolated iliac aneurysms between January 2015 and December 2024 were identified from prospectively maintained registries. Inclusion criteria comprised elective or urgent endovascular repair of aorto-iliac aneurysms in which an adequate distal sealing zone was not available without covering the IIA and suitability for the E-Liac device according to its instructions for use (IFU). Patients with a life expectancy < 1 year or hostile anatomy incompatible with the IFU were excluded. The primary end point was freedom from branch instability (occlusion/stenosis, kinking, or detachment of the bridging stent). Secondary end points included freedom from any endoleak, freedom from device-related reintervention, freedom from gluteal claudication, aneurysm-related and all-cause mortality, acute renal failure, and sac regression > 5 mm. Results: A total of 69 consecutive patients (68 male, 1 female, median age 72.0 years) received 74 E-Liac devices, including 5 bilateral implantations. The mean infrarenal aortic diameter was 45 mm and the mean CIA diameter 34 mm; 14 patients (20.0%) had a concomitant IIA aneurysm (>20 mm). Concomitant fenestrated or branched aortic repair was performed in 23% of procedures. Two patients received a standalone IBD without implantation of a proximal aortic endograft. Technical success was achieved in 71/74 cases (96.0%); three failures occurred due to inability to catheterize the IIA. Distal landing was in the main IIA trunk in 58 cases and in the posterior branch in 13 cases. Over a median follow-up of 18 (6; 36) months, there were four branch instability events (5.4%): three occlusions and one bridging stent detachment. Seven patients (9.5%) developed endoleaks (one type Ib, two type II, two type IIIa, and two type IIIc). Five patients (6.8%) required reintervention, and five (6.8%) reported gluteal claudication. There were seven all-cause deaths (10%), none within 30 days or related to aneurysm rupture; causes included COVID-19 pneumonia, acute coronary syndrome, melanoma, gastric cancer, and stroke. No acute renal or respiratory failure occurred. Kaplan–Meier analysis showed 92% (95% CI 77–100) freedom from branch instability in the main-trunk group and 89% (60–100) in the posterior-branch group (log-rank p = 0.69). Freedom from any endoleak at 48 months was 87% (95% CI 75–95), and freedom from reintervention was 93% (95% CI 83–98). Conclusions: In this multicenter cohort, the E-Liac branched endograft demonstrated high technical success and favorable early–mid-term outcomes. Preservation of hypogastric perfusion using E-Liac was associated with low rates of branch instability, endoleak, and reintervention, with no 30-day mortality or aneurysm-related deaths. These findings support the safety and efficacy of E-Liac for aorto-iliac aneurysm management, although larger prospective studies with longer follow-up are needed. Full article

This study presents the first computational investigation of hybrid propeller configurations that combine toroidal and conventional blade geometries. Using Delayed Detached Eddy Simulation (DDES) with the Shear Stress Transport (SST) $k-\omega$ model for flow analysis and the Ffowcs Williams and Hawkings (FW–H) formulation for aeroacoustic prediction, five hybrid propeller designs were evaluated: a baseline model and four variants with modified loop-element spacing. The results show that the V-Gap-S configuration achieves the highest figure of merit (FM), producing over 10% improvement in propeller performance relative to the baseline, while also exhibiting the lowest turbulence kinetic energy (TKE) levels across multiple radial planes. Aeroacoustic analysis reveals quadrupole-like directivity for primary tonal noise, primarily driven by blade tip–vortex interactions, with primary tonal noise strongly correlated with thrust. Broadband noise and overall sound pressure level (OASPL) exhibited dipole-like patterns, influenced by propeller torque and FM, respectively. Comparisons of surface pressure, vorticity, and time derivatives of acoustic pressure further elucidate the mechanisms linking blade spacing to aerodynamic loading and noise generation. The results demonstrate that aerodynamic performance and aeroacoustics are strongly coupled and that meaningful noise reduction claims require performance conditions to be matched. Full article

Malaria remains a major global health burden, and the emergence of resistance to blood stage antimalarials underscores the need for new interventions targeting earlier stages of the parasite’s life cycle. The pre-erythrocytic liver stage represents a critical bottleneck and an attractive target for chemotherapeutic and prophylactic interventions. In this study, we functionally characterized the putative E3 ubiquitin ligase Trophozoite Exported Protein 1 (TEX1; PBANKA_0102200) in Plasmodium berghei using gene knockout, tagging, and imaging approaches across the mosquito and liver stages. TEX1 knockout parasites (PbTEX1-KO) showed impaired development during mosquito-stage transitions, with significant reductions in ookinete formation, oocyst numbers, and sporozoites reaching the salivary glands. In hepatic stages, TEX1-KO parasites displayed reduced growth, abnormal nuclear division, and impaired liver stage maturation, ultimately leading to a dramatic decline in detached cell formation and blood stage infectivity. Endogenous C-terminal tagging of TEX1 with GFP and 3×HA revealed a discrete subnuclear localization pattern, indicating a critical role in DNA synthesis and/or mitotic regulation. Our findings reveal that TEX1 is required for nuclear replication and division and successful development in both the mosquito and liver stages of Plasmodium. Given its pivotal role and nuclear localization during hepatic schizogony, TEX1 represents a promising target for the development of liver stage antimalarial interventions. Full article

Vulcanized NR-SBR is widely used in vehicle components; however, its irreversible crosslinking limits recyclability and contributes to the large number of tires discarded annually worldwide, and in this context, this work presents an experimental comparative assessment of the tribological behavior of conventional tire rubber and silicone VMQ, motivated by a wheel concept based on a detachable tread aimed at improving durability and sustainability rather than proposing an immediate material substitution. Wear and friction behavior were investigated under abrasive and self-friction conditions using pin-on-disk testing with an abrasive counterpart representative of asphalt, supported by optical and scanning electron microscopy. The results show that NR-SBR undergoes severe abrasive and erosive wear, characterized by deep and irregular wear tracks, pronounced fluctuations in the dynamic friction coefficient, and strong sensitivity to load and sliding speed, particularly during the initial stages of track formation. In contrast, VMQ exhibits mild abrasive wear dominated by viscoelastic deformation, leading to shallow and stable wear tracks, lower friction coefficients, and significantly reduced material loss once the contact track is fully developed. These differences are attributed to the distinct mechanical responses of the elastomers, as the higher hardness and limited strain capacity of rubber promote micro-tearing and unstable material removal, while the high elasticity of silicone enables stress redistribution and stable contact conditions under abrasive loading. UV aging increases stiffness of rubber, resulting in reduced wear and friction, while silicone remains largely unaffected after 750 h due to the stability of its Si–O–Si backbone. Self-friction tests further indicate that smooth silicone sliding against rubber yields the lowest friction values, highlighting a favorable material pairing for detachable tread concepts. Factorial design analysis confirms material type as the dominant factor influencing both wear and friction. Overall, for the specific materials and operating conditions investigated, VMQ demonstrates higher durability, greater tribological stability, and improved aging resistance compared to NR-SBR, providing experimental evidence that supports its potential for long-life, more sustainable detachable tread applications. Full article

Sharp declines in temperature pose a significant risk for mass mortality events in the Chinese soft-shelled turtle (Pelodiscus sinensis). To assess the effects of acute cold stress on intestinal health, turtles were exposed to temperatures of 28 °C (control), 14 °C, and 7 °C for 1, 2, 4, 8, and 16 days. The results showed that acute cold stress at 14 °C and 7 °C induced time-dependent alterations in intestinal morphology and histopathology. The damage was more severe at 7 °C, characterized by inflammatory cell infiltration, lymphoid hyperplasia, and extensive detachment and necrosis across the villi, muscle layer, and submucosa. 16S rDNA sequencing revealed significant shifts in intestinal microbiota composition in the 7 °C group, dominated by Helicobacter and Citrobacter. Transcriptomic analysis identified differentially expressed genes (DEGs) that respond to acute cold stress and are involved in the Toll-like receptor signaling pathway (Tlr2, Tlr4, Tlr5, Tlr7, and Tlr8), the NOD-like receptor signaling pathway (Traf6, Traf2, Casr, Rnasel, Pstpip1, Plcb2, Atg5, and Mfn2), apoptosis (Tuba1c, Ctsz, Ctsb, Kras, Hras, Pik3ca, Bcl2l11, Gadd45a, Pmaip1, Ddit3, and Fos), and the p53 signaling pathway (Serpine1, Sesn2, Ccng2, Igf1, Mdm2, Gadd45a, Pmaip1, and Cdkn1a). Metabolomic profiling highlighted differentially expressed metabolites (DEMs) that cope with acute cold stress, such as organic acids (oxoglutaric acid, L-aspartic acid, fumaric acid, DL-malic acid, and citric acid) and amino acids (including L-lysine, L-homoserine, and allysine). The integrated analysis of DEGs and DEMs underscored three key pathways modulated by acute cold stress: linoleic acid metabolism, neuroactive ligand–receptor interaction, and the FoxO signaling pathway. This study provides a comprehensive evaluation of intestinal health in Chinese soft-shelled turtles under acute cold stress and elucidates the underlying mechanisms. Full article

This study investigated the metabolic mechanisms driving physiological functional remodeling in RFM by analyzing plasma biochemical parameters and metabolomic profiles at key peripartum timepoints (21 and 7 d prepartum and 4 h postpartum), integrated with placental and fetal membrane metabolic characteristics. The results revealed that RFM cows exhibited significant negative energy balance (NEB) as early as 21 days before parturition, characterized by elevated plasma levels of non-esterified fatty acids, β-hydroxybutyrate, and malondialdehyde, alongside reduced activity of antioxidant enzymes (GSH-Px, CAT) (p ≤ 0.05). Metabolomic analysis demonstrated persistent lipid metabolism dysregulation, amino acid imbalance, and nucleotide metabolism disturbances in RFM cows from 21 days prepartum to 4 h postpartum, indicating premature mobilization of adipose and muscle tissues. Further metabolomic analyses of the placenta and fetal membranes confirmed that metabolic dysfunction compromises energy supply during parturition, adversely affecting immune homeostasis and extracellular matrix degradation in the placenta and fetal membranes of RFM dairy cows. These physiological dysfunctions have the potential to impede the timely expulsion of fetal membranes after calving. In conclusion, RFM is closely associated with early-onset metabolic dysfunction during the periparturient period, where insufficient energy supply due to NEB, oxidative stress, and immune-endocrine disruptions collectively impair normal fetal membrane detachment. Full article

Scientific literacy is a key element in today’s society, shaping everyday life and fostering informed decision-making and critical thinking. However, the traditional transmission of science, among other factors, has fostered a simplistic and negative view of this field of knowledge, leading to a detachment of the population from it. In this context, teachers need to assume a transformative role. To this end, it must be recognised that didactic change cannot be limited to cognitive aspects, given the relevance of attitudes as a key component of professional knowledge and as a driver of a consolidated shift. Concern about this reality leads us to describe the structure and content of scientific knowledge related to the study of Primary Education teachers’ attitudes towards the teaching of the Nature of Science and Technology. A mixed-methodological design was employed, comprising a documentary-bibliometric study with a science-mapping approach and documentary analysis. The results showed that studies often focus on the cognitive component of attitudes, mainly on beliefs about knowledge or self-efficacy. However, studies on affective or conative components remain scarce, and none have been found that comprehensively address all three components of attitudes, despite their potential to provide a deeper understanding of their role in educational change. The need to address teachers’ attitudes holistically is highlighted to better understand the evaluative and motivational factors that guide teaching practices. Likewise, the importance of moving towards studies based on educational interventions that promote the development of science as useful for life is emphasised. Full article

High-Performance Computing (HPC) has become essential for training medium- and large-scale Artificial Intelligence (AI) models, yet two bottlenecks remain under-exploited: the semantic coherence of training data and the interaction between distributed deep learning runtimes and heterogeneous HPC architectures. Existing work tends to optimise multi-node, multi-GPU training in isolation from data semantics or to apply semantic technologies to data curation without considering the constraints of large-scale training on modern clusters. This paper introduces SemanticHPC, an experimental framework that integrates ontology and Resource Description Framework (RDF)-based semantic preprocessing with distributed AI training (Horovod/PyTorch Distributed Data Parallel) and hardware-aware optimisations for Non-Uniform Memory Access (NUMA), multi-GPU and high-speed interconnects. The framework has been evaluated on 1–8 node configurations (4–32 GPUs) on a production-grade cluster. Experiments on a medium-size Open Images V7 workload show that semantic enrichment improves validation accuracy by 3.5–4.4 absolute percentage points while keeping the additional end-to-end overhead below 8% and preserving strong scaling efficiency above 79% on eight nodes. We argue that bringing semantic technologies into the training workflow—rather than treating them as an offline, detached phase—is a promising direction for large-scale AI on HPC systems. We detail an implementation based on standard Python libraries, RDF tooling and widely adopted deep learning runtimes, and we discuss the limitations and practical hurdles that need to be addressed for broader adoption. Full article

To address the inefficiency and high labor intensity associated with traditional manual mussel seedling unloading, this study proposes an automated traction-rope mussel unloading machine. This study focuses on the thick-shelled mussel (Mytilus coruscus) as the research subject. Furthermore, the key mussel unloading processes were simulated using the EDEM software to analyze mechanical interactions during detachment. A breakable mussel discrete element model was developed, and its Bonding V2 model parameters were systematically calibrated. Using the ultimate crushing displacement (2.25 mm) and ultimate crushing load (552 N) as response variables, the model was optimized through a sequential experimental design comprising Plackett–Burman screening, the steepest ascent method, and the Box–Behnken response surface methodology. The results demonstrate that the optimal parameter combination consists of unit area normal stiffness (2.48 × 10¹¹ N/m³), unit area tangential stiffness (3.80 × 10⁸ N/m³), critical normal stress (3.15 × 10⁶ Pa), critical tangential stress (2.90 × 10⁷ Pa), and the contact radius (1.60 mm). The model’s accuracy was validated through integrated discrete element simulations and prototype testing. The equipment achieves an exceptionally low mussel damage rate of only 1.2%, effectively meeting the operational requirements for mussel unloading. This study provides both theoretical foundations and practical insights for the design of mechanized mussel unloading systems in China. Full article