Suzhou Institute of Building Science Group (China)

As a transportation hub for the import and export transshipment of bulk cargo, the manual operation mode of bulk terminals can no longer meet the developmental demand for efficient unloading of bulk carriers. Therefore, this paper designs a whole-process intelligent unloading (WPIU) system for bulk carriers, including a series of intelligent unloading equipment and a robot-shore cooperative perception system. Secondly, a novel unloading strategy of bulk carriers that incorporates a sliding window detection algorithm rooted in three-dimensional feature distribution enables the creation of a real-time cargo hold and material model, facilitating the prediction of safer and more efficient grasping areas according to the materials’ dynamic distribution characteristics. Subsequently, by utilizing the structural features of the cargo hold and multi-sensor information, a robot-shore cooperative localization method integrating adaptive dual observation is proposed to obtain the relative position of the clearing robot and the grabber, achieving collision avoidance during the unloading operation. Finally, the WPIU system and its integrated intelligent algorithms were experimentally validated at two typical bulk ports handling grain and ore. The results demonstrate the system’s capability for intelligent and efficient unloading operations of bulk carriers.

This paper investigates the cross-correlation properties among the three major global crude oil futures markets: Brent, WTI, and Oman. We reveal that the cross-correlations between any two crude oil futures markets exhibit significant multifractality through integrated application of cross-correlation hypothesis testing and MF-DCCA methodology. Notably, the multifractality strength in cross-correlations involving the Oman market is particularly prominent, highlighting the distinctive characteristics of the Middle Eastern crude oil market.

The fabrication of three-dimensional (3D) biostructures through additive manufacturing relies on the critical role of ink development. With the growing demand for high-resolution manufacturing, digital light processing (DLP) technology has emerged as a promising technique requiring specialised photosensitive inks. Although gelatine methacryloyl (GelMA) has been the primary option for DLP, its mechanical properties, biocompatibility, and low stability still present limitations. The development of collagen-based ink is thus in high demand for a wider stiffness adjustment range, native bioactivities, and versatility in biomedical engineering applications. In this paper, we report a rapid and low-cost protocol for collagen methacryloyl (ColMA)/poly(ethylene glycol) diacrylate (PEGDA) ink for DLP printing. The ink demonstrated the highest printing resolution of ∼50 μm by using 405 nm visible light. The printability, mechanical properties and cell viability of the DLP-printed ColMA/PEGDA structures were comprehensively evaluated. The printed ColMA/PEGDA structures reached a compressive modulus over 100 kPa with 0.6 wt% collagen. The printed ColMA/PEGDA scaffolds promoted the attachment and proliferation of 3 T3 fibroblasts, demonstrating their potential in future applications in biomedical engineering.

Acute ischemic stroke (AIS) is a high mortality cerebrovascular disease associated with vessel curvature. However, the relevant mechanism remains unclear due to a lack of appropriate tortuous vascular models to investigate and validate. This study explores the combination of projection-based 3D bioprinting (PBP) with photo-stimulus-responsive techniques to fabricate a sodium alginate (SA)/acrylamide (AAM) hydrogel vascular scaffold capable of bending deformation. The coordination of Fe3+ ions with carboxylate groups in the alginate chains of the vascular scaffold acts as a molecular switch, which can be dissociated through photoreduction to enable the deformation response. Fourier Transform Infrared (FTIR) and X-ray Photoelectron Spectroscopy (XPS) results verified the deformation principle. By subjecting the scaffold to UV light exposure, Fe3+ is reduced to Fe2+ in spatially selected regions, resulting in the release of strain and subsequent deformation. Furthermore, it also controlled the degree and direction of curvature of the vessels. The cell seeding experiment verified that the vascular scaffold showed excellent biocompatibility. Overall, our approach could be used to generate an in vitro model of curved vascular pathology to investigate the pathogenesis and provide new directions for the diagnosis and treatment of vascular diseases in the future.

Cities today utilize a wide range of sensors to monitor the status of various utilities such as water distribution and the electricity grid. The gathered data can be analyzed in real-time to detect anomalies, allowing the city to rapidly identify and resolve the issue. Currently existing anomaly detection methods such as operate on the assumption of a static source environment [1, 2]. However, sensitivity of the sensors may degrade with time and background noise levels may vary as well. This leads to the generation of costly false positives and negatives, which we aim to minimize through the use of Hierarchical Temporal Memory (HTM). HTM is particularly suited for anomaly detection due to its ability to recognize patterns in a chronological stream of values [1]. In this paper, we analyze the efficacy of HTM anomaly detection for a series of 5 angular sensors measuring the alignment of a well. Additionally, we compare the results of feeding raw versus delta values from our sensors into an HTM algorithm, finding that the delta values produced a more consistently accurate result. Finally, we discuss recommendations for the applications of HTM in real city infrastructure situations.

The objective of this research was to select the most effective warm asphalt additives for mix practice based on a series of laboratory testing programs such as density, Marshall stability, freeze-thaw splitting strength, dynamic stability, and bending beam strain. The experimental design of warm mix asphalt included the use of three commonlyused additives, two typical aggregate gradations, one crushed aggregate, and one modified asphalt. Results showed that: (1) the bulk specific gravity and air voids of all the mix specimens were similar to those of controls; (2) the Marshall stability and flow values of the warm stone mastic asphalt were 6.8%–26.6% and 3.5%–10.3%% higher than those of controls, respectively, and those of the warm asphalt concrete were 6.1%–15.6% and 6.5%–9.7% higher than those of controls, respectively; (3) the indirect tensile strength of two types of mixtures was 1.7%–14.4% lower than that of controls, and the average tensile strength ratio of the warm stone mastic asphalt and asphalt concrete was 4.3% and 1.3% higher than that of controls, respectively; (4) the dynamic stability of warm mix specimens was 10.8%–16.6% lower than that of the controls; (5) the average bending failure strain of warm stone mastic asphalt was 7.6% higher than that of the controls, and that of warm asphalt concrete was 12.8% lower than that of the controls; (6) Overall, warm asphalt mixtures with Sasobit and Rediset had relatively best performances required in Southeast China, where rutting and stripping are the main failures of asphalt pavements.