Search Results (170)

Aeolian sand bodies unrelated either to coastal barrier systems of Holocene or earlier age or to modern beaches have been identified along the central New South Wales coast of southeast Australia. Some of these deposits cap headlands or are located above high sea-cliffs. Others lie below modern sea-levels, whilst one substantial dune field extends 12 km inland. Many of these have previously been interpreted as Early Holocene cliff-top dunes, the product of the migration of beach sands up aeolian sand ramps at the foot of the sea-cliffs of the region and onto the cliff tops. The rising sea-levels of the Middle Holocene eroded the ramps and cut off the supply of sand to the dunes, allowing them to stabilise. But re-investigation shows that these dune fields accumulated at times of low Quaternary sea-levels, with a particle-size distribution suggestive of an inland rather than a coastal origin. We therefore propose an alternative model for the accumulation of these features. At times of low sea-level, sediments exposed on the inner shelf were reworked onto the adjacent coast by onshore winds, where they accumulated in locations unconnected to the modern or the earlier Holocene coastal aeolian sedimentary regime. This model challenges the conventional story that the dominant glacial maximum winds across southeastern Australia were from the west (and thus offshore). This pattern of sediment accumulation and its associated wind regime may have been more stable (continuing for over 30 000 years) and more long-lived (repeated through at least the last two glacial cycles) than has previously been believed. Although the cliff-top dune model has been widely applied, we question its suitability in its type location and suggest a more cautious approach to its application elsewhere. We argue that the products of the landward aeolian reworking of sediment exposed on the continental shelf have been overlooked, despite their potential for the preservation of long-term environmental records. Full article

Current research suggests that the uranium enrichment in the Qianjiadian deposit, southwestern Songliao Basin (China), is closely related to hydrocarbon dissipation and deep thermal fluids. However, previous investigations have not carried out systematic in-depth research on the abundant calcite veins hosted in diabase within the ore district, especially regarding their types, genetic mechanisms, formation ages, and genetic links to uranium enrichment. In particular, whether their genesis is associated with the two critical ore-controlling factors (hydrocarbon dissipation and thermal fluid activities) remains poorly constrained and to be elucidated. Through analyses of major and trace element geochemistry, scanning electron microscopy, and fluid inclusion microthermometry on calcite veins within fractures of Lower Cretaceous diabase, this study confirms that the veins are products of epigenetic fluid infill with a medium-to-low temperature hydrothermal nature (115–215 °C). The direction of fluid migration was from north to south, consistent with the trend of hydrocarbon dissipation. In situ U-Pb dating yields Eocene (~42.9 Ma) and Pleistocene (1.57–2.82 Ma) ages for the calcite veins, which are highly consistent with the timing of diabase intrusion (early Eocene) and the main episodes of uranium mineralization (Eocene–Oligocene and Pleistocene). Carbon and oxygen isotope compositions and inclusion components indicate that the carbon source was mainly derived from dissipated hydrocarbons, rather than from sedimentary diagenesis or direct source rock generation. The C-O isotopic signatures reflect further carbon isotope fractionation following the interaction between dissipated hydrocarbons and groundwater, and the inclusion fluids, composed mainly of hydrocarbon gases and water, suggest that the carbon source for calcite vein formation was provided by dissipated hydrocarbons. The temporal coupling of hydrocarbon dissipation, calcite vein formation, uranium mineralization, and thermal input from diabase intrusion reflects the dynamic processes of basin evolution and tectonic reworking. The key dynamic backgrounds for this series of diagenetic and metallogenic events include Late Cretaceous tectonic inversion, Eocene–Oligocene tectonic uplift and erosion, and Pleistocene differential uplift and subsidence. The thermal effects from hydrocarbon dissipation and diabase intrusion were the primary factors driving the anomalous uranium enrichment that formed this super-large deposit. The formation of the calcite veins, along with their characteristics indicative of medium-to-low temperature hydrothermal activity and hydrocarbon dissipation, provides a critical window for understanding these processes and offers robust scientific evidence for this genetic model. This study, for the first time, systematically reveals that the calcite veins within the diabase of the Qianjiadian uranium mining area are of medium-to-low temperature hydrocarbon-bearing hydrothermal origin, and constrains their formation ages to the Eocene (~42.9 Ma) and Pleistocene (1.57–2.82 Ma), which are highly coupled with diabase intrusion and two episodes of uranium mineralization events. C-O isotopic and fluid inclusion evidence indicates that the formation of calcite veins directly records the process of hydrocarbon dissipation–groundwater mixing, providing a new mineralogical and geochronological evidence chain for thermal–hydrocarbon–uranium-coupled mineralization. Full article

Battery formation is important for ensuring the quality and service life of cells in lithium-ion battery (LIB) production. During the formation process, fault cells, such as low open-circuit voltage cells, are screened offline after the charging stage since, in most formation protocols, the online screening process is absent. This can lead to energy waste and extend the rework cycle of the fault cells in the LIB formation process. To address this problem, this paper considers the online fault cell screening problem, the formation pre-screening, in the LIB formation process as a classification task and proposes a data-driven model based on incomplete time-series data for formation pre-screening. First, the proposed model transforms segments of the incomplete charging voltage curve (ICVC) of the LIB as tokens, which is a more compact and less redundant data representation of the ICVC. Then, the attention-based feature encoder, Transformer encoder (TE), captures the dependency between tokens to extract features for the formation pre-screening. Finally, a task-specified decoder, feature enhance decoder (FED), is used to screen out fault cells online. The effectiveness of the proposed model is verified using real-world production data collected from a specific type of 18,650 lithium-ion cell under one formation protocol. The results on the investigated industrial dataset show that the proposed model achieves an accuracy of 98.73% and a miss rate of 1.92% during formation pre-screening, which is a 2.49% improvement in accuracy and an 8.98% decrease in miss rate compared with the deep residual network baseline. These results demonstrate the feasibility of using incomplete formation-stage voltage curves for online fault-cell pre-screening, which has the potential to reduce unnecessary charging and rework time in LIB production. Full article

This article examines the spiritual, intellectual, and institutional legacy of Caterina Vigri (1413–1463) and the formation of a “school of holiness” within the Poor Clare monastery of Corpus Domini in Bologna. Through the analysis of key texts produced within the monastic milieu—including the Libro devoto (later known as The Seven Spiritual Weapons), the Ordinazioni, the epistolary Formulario, and the Book of Visions and Revelations by Valeria Campanazzi—the study explores how Vigri’s teachings were transmitted, received, and reworked across generations of nuns. Particular attention is devoted to the centrality of obedience as the defining principle of monastic life, which marks a significant shift from earlier Franciscan emphases on poverty. The article highlights the pedagogical dimension of these writings, their grounding in Sacred Scripture, and their role in shaping a collective religious identity within an Observant context. At the same time, it situates Vigri’s spiritual program within broader developments in late medieval and early modern Christianity, including the institutional consolidation of religious life and the circulation of diverse spiritual influences. By tracing both continuity and transformation within the Corpus Domini community, the study demonstrates the existence of a sustained intellectual and devotional tradition that extended well beyond the founder’s lifetime. The “school of Caterina” thus emerges as a dynamic space of female religious authority, literary production, and theological formation. Full article

Online grocery retailing remains effort-intensive because consumers must coordinate many item-level decisions, making basket construction and correction a key barrier to more frequent use. This study examines consumer acceptance of an AI-pre-filled basket in Austrian online grocery retailing and links Technology Acceptance Model (TAM) mechanisms to objective interaction performance. Using a field-proximate one-group pre–post design, participants edited an AI-pre-filled basket in a standardized online shop and completed pre- and post-task surveys using 0–100 slider scales; log data captured processing time and edit actions. Analyses are based on n = 297 valid cases. Results show a substantial and statistically significant within-person increase in online grocery usage intention after the AI-basket interaction, rising from 39.17 to 59.78. The TAM results support the core mechanism: perceived ease of use is positively associated with perceived usefulness, and perceived usefulness strongly predicts behavioral intention, whereas a direct ease-of-use effect on intention is not supported. Linking perceptions to log data shows that acceptance is more strongly associated with correction demand than with processing time. AI-basket acceptance depends less on speed than on reducing rework while preserving user control; retailers should therefore design AI baskets as controllable, editable, low-rework systems rather than speed-oriented automation tools. Full article

In the northeastern United States, sediments related to the expansion and contraction of the Laurentide ice sheet have been extensively mapped throughout New England, as well as in New Jersey and on Long Island. However, linking these deposits around New York City is challenging due to the extensive urbanization. Staten Island is less developed than the other boroughs of New York City, however outcrops of rock and surface sediment are limited, making interpretation of its geologic history challenging. When small areas of sediment are temporarily exposed, they can be used to improve our understanding of sediment erosion and deposition over time, helping to link the deposits mapped in New Jersey and Long Island. In this study of two small temporary outcrops, the beds of sediment were measured and described in the field and samples were collected for textural and compositional analyses. The results were interpreted in the context of previous work on similar exposures nearby. The sediments are sands and gravels of fluvioglacial origin containing reworked sediments of both the Pliocene Pensauken Formation and older Triassic rocks of the Newark Basin, interpreted to have been deposited on an outwash plain during the Illinoian glaciation (Marine Isotope Stage 6). They were deposited in a topographic low directly overlying Cretaceous sedimentary rocks, but adjacent to sediments of the Pensauken Formation which had in turn been deposited as an earlier valley fill. Similar sequences of repeated valley fills have been observed in New Jersey but have not been documented on Staten Island. This interpretation solves an apparent disagreement between previous studies by illustrating how both the Pensauken Formation and later fluvioglacial sediments can directly overly Cretaceous sediments across a distance of less than a kilometer. Full article

Late Jurassic–Early Cretaceous silicic volcanism is widespread along the Southeast China continental margin, yet the timing, magma plumbing, and geodynamic drivers of individual volcanic centers remain debated. Here, we integrate whole-rock geochemistry with zircon U–Pb geochronology, zircon trace elements, and in situ zircon Lu–Hf isotopes for high-silica rhyolites from the Bijiashan volcanic complex, eastern Guangdong, to constrain magmatic evolution and its link to Paleo-Pacific subduction dynamics. LA–ICP–MS zircon U–Pb analyses were used to define two dominant crystallization populations: 145.4 ± 1.2 Ma (n = 14; MSWD = 1.7) for sample BJS-18 and 141.4 ± 1.3 Ma (n = 14; MSWD = 1.6) for sample BJS-27, yielding dominant zircon U–Pb age populations of 141.1–145.4 Ma, thereby constraining the timing of the main silicic volcanism (magma crystallization immediately preceding eruption) to the Jurassic–Cretaceous boundary. Minor older peaks at 157.0 ± 1.6 Ma (BJS-18) and 153.1 ± 1.5 Ma (BJS-27) suggest antecrystic or inherited components from a long-lived trans-crustal magmatic system. Whole-rock data indicate subalkaline, high-K calc-alkaline rhyolitic affinities, with apparent peraluminous signatures affected by post-magmatic alkali mobility. The rhyolites are characterized by pronounced negative Eu anomalies (Eu/Eu* = 0.085–0.395), low Sr contents (5.9–29.0 ppm), and arc-like trace-element signatures with Nb–Ta–Ti depletions. Zircon trace elements indicate crystallization temperatures of 608–842 °C and redox states from ΔFMQ = −3.90 to +1.71, with syneruptive grains clustering near FMQ ± 1 and xenocrystic grains systematically more reduced and hotter, implying vertically and temporally zoned magma storage. Zircon εHf(t) values (−7.4 to −0.9) and Mesoproterozoic TDM2 ages (1.18–1.66 Ga) indicate substantial reworking of ancient Cathaysian crust. In contrast, the relatively radiogenic upper εHf(t) values and the occurrence of mafic lithic fragments suggest limited juvenile or mantle-derived input into the crust-dominated magmatic system. Together with tectonic discrimination diagrams indicating a continental arc affinity, these results support Early Cretaceous arc-related silicic magmatism during a regional transition from compression to extension, plausibly linked to Paleo-Pacific slab rollback beneath Southeast China. Full article

With the global emphasis on sustainable development, supply chain management is facing new challenges and opportunities. Enterprises often face a large number of suppliers when selecting suppliers, which makes the selection process complex. Considering the crucial role of supplier selection in sustainable supply chains, a sustainable supplier selection model based on multi-attribute utility analysis and a fuzzy approximation ideal solution ranking method is proposed to reduce carbon emissions and environmental pollution. This model helps companies scientifically evaluate and select suppliers by comprehensively considering three aspects: environment, economy, and society. Meanwhile, the study utilizes an optimized genetic algorithm-based order allocation model to raise the efficacy and fairness of order allocation. Reducing procurement costs often relies on improving resource utilization and reducing production waste, which directly lowers the energy consumption and carbon emission intensity per unit of product. At the same time, reducing product damage and delivery delay rates can avoid additional greenhouse gas emissions caused by rework, abandonment, and emergency transportation. By improving supplier productivity and optimizing order allocation, the developed model can not only reduce economic costs but also control environmental pollution and carbon footprints from the source of the supply chain. The outcomes indicate that technological level is a crucial factor influencing supplier selection, with a significant positive impact on supplier willingness to choose, and its standard path coefficient is 0.199, with a significance level of 0.001. Meanwhile, the optimized genetic algorithm exhibits strong stability and convergence in order allocation. This optimization model has high efficiency in handling large-scale orders. This provides strong support for the decision-making of enterprises in sustainable supply chain management and a valuable reference for China’s exploration and practice in the field of sustainable development. Full article

Combining landscape studies with historical studies and archeology is a scientific challenge: through the skills of historians, archeologists, agronomists, and computer scientists, an integrated and interdisciplinary methodology was adopted. The aim was to backtrack historical landscape changes and permanences in the rural landscape around Staffarda Abbey (Piedmont, Northwest Italy), a medieval monastery founded in the XII century on a surface of 1356 ha and its farms. Surveys, field observations, landscape observations, and historical and archival analyses (XII–XX century) were performed. Several document types, such as historical cartography, iconographies, cadastral maps, notes, descriptions, topographic maps, inventories, and photographs, were deeply analyzed. These documents referred to different historic periods (XII–XXI century) and provided qualitative and quantitative data. Using a fixed-wing drone, the aerial photographs were reworked and georeferenced. QGIS was used to perform diachronic analyses at the landscape level. The advanced land analysis methodologies were compared with the post-medieval cartographic data that were collected. The landscape dynamics and land-use changes were quantified over time, and routes, tree lines, hedgerows, and canals were recognized as qualifying elements. In this study, qualitative and quantitative data were collected, processed, systematized, and analyzed using a digital platform. Using different scales, readings, and interpretations, the landscape dynamics of a rural medieval site were reconstructed. Full article

Manual assembly of multi-pin cable harnesses remains vulnerable to miswiring issues when conductors are visually indistinguishable. This paper presents an industrial case study of a quick-connect harness composed of two connectors (receptacle-type and pin-type) linked by 16 black conductors (2.5 mm² and 200 mm length), where the dominant failure mode is a two-wire swap that breaks correct pin-to-pin mapping and may cause downstream equipment damage. In the baseline state, end-of-line verification relies on visual inspection only (1 min/unit), resulting in an internal nonconformity rate of 4% (repairable). To achieve the operational goal of zero defects (zero escapes), we proposed and integrated an electronic pin-to-pin continuity and mapping fixture as a deterministic End-of-Line (EOL) quality-gate implementing poka-yoke logic (“no PASS—no shipment”) and enabling structured traceability records. Using a before–after workload model that includes a mandatory retest after rework, the fixture reduces test time to 0.33 min/unit. For a monthly volume of 1500 units, total quality workload (test + rework + retest) decreases from 31 h/month to 13.58 h/month, releasing 17.42 h/month. Global quality productivity increases from 48.39 units/h to 110.46 units/h (+128%). The proposed architecture couples deterministic electrical verification with data logging aligned to digital-thread and data-driven quality-management concepts to sustain continuous improvement and prevent customer escapes. Full article

Rework continues to be a critical issue in construction projects, contributing to cost escalation, schedule delays, and compromised quality. While earlier studies have identified isolated causes such as design deficiencies, communication failures, and inadequate workmanship, the structural relationships among these factors have not been sufficiently examined. This study investigates the interdependencies among major rework causation domains using Structural Equation Modelling (SEM) based on survey responses from 200 construction professionals. A total of 43 observed variables, identified through an extensive literature review, were grouped into four latent constructs: contractor-related, owner-related, design-related, and resource/workforce-related factors. Confirmatory Factor Analysis (CFA) was conducted to validate the measurement model, followed by structural path analysis to examine causal linkages. The findings reveal that design-related and owner-related factors exert the most significant direct and indirect influence on rework, followed by contractor- and workforce-related factors. The proposed model demonstrates satisfactory goodness-of-fit indices, confirming its reliability and applicability. Compared to conventional ranking and fuzzy-based approaches, SEM provides a more systematic and comprehensive understanding of rework dynamics. The findings provide practical guidance for project managers and decision-makers by identifying the most critical drivers of rework, enabling targeted mitigation strategies and improved resource allocation to enhance overall construction project performance. Full article

Early-stage remote site analysis is often hindered by fragmented media that fail to convey sufficient spatial context to off-site collaborators. To address this challenge, we propose SiteSync, a real-time remote collaborative system that combines live video, coarse mesh streaming, georeferenced pose tracking, and 3D spatial annotations to establish a shared spatial understanding between on-site and remote collaborators. The system was evaluated through a counterbalanced within-subject study with 24 participants, comparing the synchronous SiteSync workflow against a traditional asynchronous baseline. The results showed that SiteSync significantly improved task performance by reducing completion time and rework while increasing overall accuracy (all p < 0.001). Participants also reported lower cognitive workload and higher usability. Remote users benefited most significantly. These findings show that the synchronous workflow can improve collaboration efficiency and user experience in early-stage site analysis. Full article

Sustainable manufacturing performance is increasingly influenced by the quality of decisions embedded in Quality Management System (QMS) activities, particularly those related to problem analysis and preventive action. In industrial environments such as welded bus chassis production, recurring quality defects—although involving small components—can generate sustainability impacts through rework, inspection effort, and energy consumption. Although artificial intelligence (AI) is increasingly adopted to support quality-related tasks, its contribution is often assessed in terms of automation rather than its effect on decision quality. This study presents an AI-supported, prompt-driven decision framework designed to strengthen preventive performance within QMS. The framework is implemented through a deterministic software application that formalizes prompt engineering as a rule-based process, transforming informal human problem descriptions into structured prompts suitable for external AI reasoning tools. The application itself does not embed AI and does not generate decisions; instead, it functions as a transparent decision interface that reduces variability in problem formulation and supports methodological consistency. The framework was validated through an industrial case study conducted in a bus chassis manufacturing plant experiencing recurring defects related to missing or incorrectly positioned welded brackets. Quantitative evaluation using Key Performance Indicators demonstrates reduced analysis cycle time, improved completeness of problem definitions, higher corrective action implementation rates, and lower defect recurrence. Full article

The construction industry faces persistent challenges in productivity, efficiency, and sustainability. Digital twin (DT) technology has emerged as a promising pathway for lifecycle optimisation, yet its construction adoption remains limited. Key barriers include fragmentation across project phases, weak data continuity at handover, and conceptual ambiguity between DT and Building Information Modelling (BIM). This systematic literature review analyses 160 peer-reviewed studies (2018–2026) selected from 463 Scopus records using a PRISMA-guided process and inter-rater reliability testing (Cohen’s κ = 0.83). The review clarifies that DTs extend beyond BIM in three ways: they enable bidirectional, automated physical-digital data exchange; integrate heterogeneous real-time sources such as IoT sensors and operational systems; and maintain lifecycle continuity from design through to end-of-life. Select advanced implementations report notable performance gains. These include rework and logistics reductions of up to 80%, cost savings of approximately 5%, schedule acceleration of around two months, energy reductions of 15–30%, and maintenance cost reductions of 10–25%. These figures reflect case-level outcomes from high-performing pilots and should not be read as typical industry benchmarks. Broader adoption remains constrained by interoperability gaps, data quality challenges, digital maturity deficits, misaligned stakeholder incentives, and paper-based regulatory environments. DTs represent a socio-technical transformation, not a standalone technology upgrade. Realising their potential requires coordinated progress in standards development, governance frameworks, collaborative delivery models, and workforce capability. Future research should focus on scalable interoperability, longitudinal lifecycle value validation, human-centred adoption strategies, and sustainability assessment methods to support evidence-based diffusion of DTs in the built environment. Full article

The geometric variability of industrial components represents a persistent challenge in robotic arc welding, particularly in high-volume manufacturing environments where parts are positioned in fixtures based on nominal CAD assumptions. Even moderate deviations in dimensions or seating conditions can lead to weld defects, rework, and reduced process capability when conventional offline programming is employed. This paper presents an applied industrial workflow for adaptive robotic welding trajectory correction that integrates full-field 3D optical metrology with a data-driven deep reinforcement learning (DRL) model. Prior to welding, each component is scanned using a structured-light 3D system, and critical geometric deviations are extracted relative to the nominal CAD model. These deviations define a compact state representation that is mapped, via a trained DRL agent, to corrective translational and rotational adjustments of the welding trajectory. Importantly, all trajectory corrections are computed offline, ensuring compatibility with standard industrial robot controllers and avoiding real-time computational overheads. The proposed approach is validated using real production data from an industrial batch of 5000 components characterized by significant dimensional variability and limited process capability. Experimental results demonstrate a reduction in welding defects exceeding 90%, elimination of rework associated with improper part positioning, and an improvement of the overall process performance to a sigma level of 5.219. The results show that combining 3D optical metrology with learning-based trajectory adaptation enables robust compensation of part-level geometric deviations without mechanical fixture modifications. The proposed method provides a practical and scalable solution for improving welding quality in manufacturing environments affected by upstream variability and imperfect part positioning. Full article