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Tuning interfacial properties of C-A-S-H gels through Al/Si ratio control: Multiscale simulation insights
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The data that has been used is confidential.Understanding the role of aluminum incorporation in calcium-aluminosilicate-hydrate (CASH) gels is crucial for enhancing cement-based materials’ durability. The presented research employs molecular dynamics simulations and quantum chemical calculations to examine how changing the Al/Si ratio affects the interfacial tension of CASH gels with water. The results reveal that initial aluminum addition increases interfacial tension, while further increases in the Al/Si ratio lead to a gradual reduction, indicating an optimal aluminum content for minimizing solution transport. Analysis of the interface microstructure and lamellar interfacial tension suggests that increased Al/Si ratios contribute to a more homogeneous interface. Molecular interaction analysis shows that calcium is a key factor in interfacial bonding, with aluminum enhancing calcium adsorption and inhibiting its detachment. Quantum chemical analysis confirms that calcium adsorption occurs via electrostatic interactions, with weaker electron localization in aluminum-containing structures. These findings shed light on the mechanism by which aluminum in CASH gels inhibits transportation at the molecular level, offering valuable guidance for designing durable concrete materials.M. W. and D. H. financial support from the National key research and development project 2022YFE0133800, the National Natural science foundation of China under Grant U2006224, 52308263, Shandong Province Natural Science Foundation under Grant ZR2022YQ55, Shandong Provincial Education Department under Grant 2023KJ320, Qingdao Research Program 16–5–1–96-jch, 111 Project TMduracon20220022. Newton International Fellowship NIF\R1\242498
Hedge Fund Performance, Classification with Machine Learning, and Managerial Implications
Get PDFSupporting Information is available online at: https://onlinelibrary.wiley.com/doi/full/10.1111/1467-8551.70011#support-information-section .Prior academic research on hedge funds focuses predominantly on fund strategies in relation to market timing, stock picking and performance persistence, among others. However, the hedge fund industry lacks a universal classification scheme for strategies, leading to potentially biased fund classifications and inaccurate expectations of hedge fund performance. This paper uses machine learning techniques to address this issue. First, it examines whether the reported fund strategies are consistent with their performance. Second, it examines the potential impact of hedge fund classification on managerial decision-making. Our results suggest that for most reported strategies there is no alignment with fund performance. Classification matters in terms of abnormal returns and risk exposures, although the market factor remains consistently the most important exposure for most clusters and strategies. An important policy implication of our study is that the classification of hedge funds affects asset and portfolio allocation decisions, and the construction of the benchmarks against which performance is judged
Multiscale Modelling of Thermal Conductivity in Fumed Silica VIPs for Building Energy Conservation
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Data will be made available on request.Vacuum insulation panels (VIPs) with ultra-low thermal conductivity are widely studied for building applications to enhance energy efficiency, with fumed silica (FS) being one of the most effective core materials. However, existing analytical models are inadequate for FS due to its multiscale structure. This study develops a highly adaptable predictive model for analyzing and predicting the thermal conductivity of FS VIP cores. A three-dimensional physical model is first established to enable adaptable solid heat transfer analysis based on characterization data, such as particle diameter, porosity, and coincidence angle. A novel classification of coexisting micro- and nano-porosities is introduced to model gaseous heat transfer accurately, achieving high predictive accuracy at lower pressures. Validation results show that the predictive model performs well across different pressures. The predicted values closely match experimental data, even at near-atmospheric pressure. In the pressure range where gaseous conduction is significant (p > 1 kPa), the model achieves an average deviation of 3.7 % and a maximum deviation of 15 %. Overall, the proposed model reliably predicts thermal conductivity, offering valuable insights for designing, manufacturing, and maintaining FS cored VIPs
Becoming a friend of the foe: The evolving perspectives on the ‘cohabitation’ strategies of large-scale and artisanal and small-scale mining operations
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No data was used for the research described in the article.As mining governance regimes become far more welcoming to foreign investors, the dispossessed and disenchanted small-scale miners have staked their own claims to part of the mining wealth in the majority of mineral-rich regions across the globe. Alongside large-scale mineral extraction, there has been a proliferation of smaller mines operated by artisanal and small-scale mining (ASM) actors. The coexistence of all forms of mining – large and small, formal and informal – have often come at the cost of significant socio-economic and environmental impacts. Thus, the concept and the practice of ‘cohabitation’ and ‘autonomy’ have dominated the policy and scholarly discourse on large-scale mining (LSM) and ASM interactions for decades, with an upsurge in the amount of scholarly literature reporting on the conflictual relations. In this vein, we review the LSM-ASM research and integrate it with the stream of theoretical scholarship: the ‘partnership’ perspective. Our perspective holds that the failure of past cohabitation arrangements, particularly in sub-Saharan Africa, can be attributed to i) legitimacy and legality issues, ii) a focus on containment over collaboration, and iii) environmental remediation oversights. LSM companies often have to negotiate with informal or unlicensed ASM operators. Consequently, cohabitation agreements frequently overlook the legitimacy and legality of these arrangements, resulting in a lack of legally binding contracts. Hence, of critical importance, attention to ‘partnership’ principles, encapsulating among other things, attention to LSM economic-related interests, and ASM environmental-remediation obligations could help both scales and types of mining partner to flourish together. Our work has important implications for research and policy decisions on the mining landscape and suggests important directions for the practice of both LSM and ASM
Federated Learning for Early Cardiac Anomaly Prediction in Cross-Silo IoMT Environments
Get PDFEarly detection of cardiovascular anomalies remains critical for proactive patient care, especially within the growing ecosystem of Internet of Medical Things (IoMT) devices. This study explores the application of Federated Learning (FL) to predict early cardiac events using electrocardiogram (ECG) signals across heterogeneous IoMT silos without centralized data sharing. We focus on Premature Ventricular Contraction (PVC) as an example of early event prediction. Using three realworld ECG datasets (PTB-XL, Chapman-Shaoxing, and MITBIH), we simulate cross-silo environments where local models are trained independently and aggregated through FL. Our experiments demonstrate that local models can already achieve high classification performance, but global models obtained via FL lead to consistent improvements in macro precision, recall, and F1-scores across datasets. Visual analysis of early ECG segments further highlights inter-dataset variability, emphasizing the importance of silo-specific characteristics. The results validate that FL is a promising strategy to enable scalable, privacypreserving, and accurate early cardiovascular event prediction in IoMT systems, bridging clinical silos while safeguarding sensitive patient data
Joint optimisation model for light source position based on a combined target
Get PDFPhotometric stereo vision, as a non-contact three-dimensional imaging technology, can achieve fast and high-precision reconstruction of normal vectors and three-dimensional morphology of object surfaces by resolving the intensity changes under different angles of illumination. However, the existing near-field photometric stereo vision system is limited by the complexity of the light source calibration process and the error accumulation, which seriously restricts the expansion of the application of this technology. This paper addresses the problem of accurately determining the centre of a spherical mirror target combined with a planar calibration board. We proposed a joint optimization model that simultaneously estimates both the light source positions and the sphere centre coordinates. The model defines a unified objective function to guide the optimization. The calibration is implemented using the Ceres Solver, based on near-field photometric stereo principles. Compared with the pre-optimization results, the error in the estimated sphere centre is reduced from 0.541 mm to 0.228 mm.This research was funded by the National Natural Science Foundation of China (62371311, 62275173, 62175109), the Shenzhen Research Program (JCYJ20220531101204010), and Shenzhen Universit
SharkNet-5G wireless link integration technology research
Get PDFIntelligent manufacturing environment puts forward multi-dimensional requirements for industrial control networks, such as flexibility, mobility and dynamic adaptability, etc. SharkNet, as a high-performance fieldbus protocol, possesses significant advantages, such as strong real-time, low latency, and high reliability, but its wired connection method seriously limits its coverage, application flexibility and dynamic adaptability in complex industrial environments. Aiming at the above problems, this paper proposes for the first time a protocol depth adaptation scheme for SharkNet and 5G protocols. Firstly, by analysing the frame structure and communication timing characteristics of SharkNet and 5G protocols in detail, a protocol semantics-based conversion mechanism is designed to achieve a seamless connection between the two protocols; secondly, a wireless link system prototype containing a protocol adaptation module is developed, and its performance is evaluated through systematic experiments. The experimental results show that the protocol adaptation scheme has significant advantages over the transparent transmission method: when the number of packets increases from 500 to 5000, the end-to-end delay grows only 9.85 ms, which is reduced by 8-12 ms on average compared with the transparent transmission scheme; when the control command period is 100 ms, the transmission reliability is as high as 99.80%
NEAT-based 3D path planning for mobile robotic arms in NDT with offline inverse kinematics validation
Get PDFTo address the challenges of coverage completeness and path executability in mobile robotic arm planning for industrial ultrasonic nondestructive testing (NDT), this study proposes a 3D path planning method that combines the Neuro-Evolution of Augmenting Topologies (NEAT) algorithm with offline inverse kinematics (IK) checking. First, a graph structure is built from the point cloud data of the target surface, and the NEAT algorithm is used to evolve an access strategy that simultaneously optimizes coverage, path smoothness, and path length. An offline IK validation step is introduced to pre-evaluate the reachability of each node using a standard solver in ROS. Based on the IK results, the node selection is further optimized to reduce the risk of execution failure. For nodes that are unreachable by the robotic arm, static position adjustments of the mobile chassis (Husky) are applied to help maintain overall path coverage. Simulation results on the ROS + Rviz platform across different surface geometries show that the proposed method achieves 100% surface coverage in all tested cases, with no collisions occurring during execution. It provides a practical solution for inspection scenarios where arm reachability and surface complexity present significant challenges
A review of non-destructive testing using robot
Get PDFWith the wide application of new materials, new structures, and new technology in modern industry especially in the aerospace industry, the range of non-destructive testing has not been limited on normal materials or normal shapes, the test of complex components will bring new chance and challenge to non-destructive testing. The combination of manipulator, robotic machine, which is widely used in industry, and non-destructive test can replace human to realize precise test on complex component, and it can get more efficiency and more security. The article reviews single manipulator gripping transducer, single manipulator gripping work piece and manipulator radiographic test respectively according to different test way, and the range of application to different test way is analyzed
Targeting runoff hotspots for sustainable rainwater harvesting in arid regions
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Upon request.Code availability:
Upon request.Declaration of Generative AI and AI-assisted technologies in the writing process:
During the preparation of this paper, the authors employed ChatGPT 5.0 to improve solely the clarity, structure, and language of the manuscript, followed by a thorough review and manual editing of the content.Rainwater harvesting (RWH) is a crucial strategy for enhancing water availability in arid regions and supporting local livelihoods, including those of Bedouin communities. Rainwater. This study focuses on Wadi Sudr, located opposite Ras Sudr city in the Sinai Peninsula, to identify optimal RWH sites and recommend suitable harvesting techniques. A weighted spatial probability model (WSPM) was developed within a Geographic Information System (GIS) framework, incorporating eight morphometric parameters. Two scenarios were evaluated: 1) equal weighting of all factors and 2) analytical hierarchy process (AHP) based weighting. The resulting maps classified the watershed into five RWH potential categories. Scenario 1 (equal weighting) identified 49.6% of the area as high or very high potential. In contrast, Scenario 2 (AHP-based) refined this to 18.2%, emphasising the role of basin shape, slope, and valley floor area. High- and very high-priority zones guided recommendations for two surface storage dams in Al-Mleha, with capacities of 25,000–30,000 m³, and Al-Athamy, with capacities of 70,000–80,000 m³, sub-catchments, complemented by cisterns to support remote communities. By integrating GIS, WSPM, and AHP into a unified framework, this study delivers a replicable methodology for prioritising RWH in arid regions, balancing efficiency with accessibility to strengthen sustainable water resource management.This study did not receive any funding
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