Novel porous chitosan microspheres were successfully produced by a freezing–lyophilization drying method in this study and were then used as adsorbents to remove a toxic iron metal, hexavalent chromium (Cr(VI)). The effects of the concentration of the chitosan solution, syringe diameter, and freezing time on the morphologies of porous chitosan microspheres were characterized. The metal ion adsorption for Cr(VI) was also studied. Results showed that freezing chitosan hydrogel beads at a temperature of −20 °C and subsequently lyophilizing the frozen structure allowed to easily obtain the porous chitosan microspheres with rough surfaces and large pores, which were more suitable for adsorption materials to remove metal ions. A chitosan solution concentration of 3% (w/v) and a syringe diameter of 500 μm allowed the porous microspheres to have a good sphericity, thinner pore walls, and small pore sizes. The adsorption capacity of porous chitosan microspheres for Cr(VI) increased with the increase in freezing time. The pH of the initial adsorption solution ranged from 3.0 to 5.0 and was beneficial to the maximum adsorption efficiency for Cr(VI). The porous chitosan microspheres prepared with 3% (w/v) chitosan solution at −20 °C for a freezing time of 72 h had a higher adsorption capacity of 945.2 mg/g for Cr(VI) than the those at 24-h and 48-h freezing times. Kinetic study showed that the adsorption process could be described by a pseudo-second order (PSO) kinetic model. The equilibrium adsorption rate constant and the adsorption amount at equilibrium for the porous chitosan microspheres increased with an increase in the freezing time, and those for the porous microspheres prepared with 3% chitosan solution at −20 °C for a 72-h freezing time were 1.83 × 10⁻⁵ g mg⁻¹ min⁻¹ and 1070.5 mg g⁻¹, respectively. The porous chitosan microspheres have good potential to facilitate the separation and recycling of expensive and toxic Cr(VI) from wastewater.

This study aims to promote the protection and inheritance of cultural heritage in private gardens in the Jiangnan area of China. By establishing a precise visual labeling system and accelerating the construction of a database for private garden features, we deepen the understanding of garden design philosophy. To this end, we propose an improved Jiangnan private garden recognition model based on You Only Look Once (YOLO) v8. This model is particularly suitable for processing garden environments with characteristics such as single or complex structures, rich depth of field, and cluttered targets, effectively enhancing the accuracy and efficiency of object recognition. This design integrates the Diverse Branch Block (DBB), Bidirectional Feature Pyramid Network (BiFPN), and Dynamic Head modules (DyHead) to optimize model accuracy, feature fusion, and object detection representational capability, respectively. The enhancements elevated the model's accuracy by 8.7%, achieving a mean average precision (mAP@0.5) value of 57.1%. A specialized dataset, comprising 4890 images and encapsulating various angles and lighting conditions of Jiangnan private gardens, was constructed to realize this. Following manual annotation and the application of diverse data augmentation strategies, the dataset bolsters the generalization and robustness of the model. Experimental outcomes reveal that, compared to its predecessor, the improved model has witnessed increments of 15.16%, 3.25%, and 11.88% in precision, mAP0.5, and mAP0.5:0.95 metrics, respectively, demonstrating exemplary performance in the accuracy and real-time recognition of garden target elements. This research not only furnishes robust technical support for the digitization and intelligent research of Jiangnan private gardens but also provides a potent methodological reference for object detection and classification research in analogous domains.

Porous chitosan/saccharomycetes adsorption microspheres were successfully prepared by using silica gel as porogen. The morphology of porous chitosan/saccharomycetes microspheres was characterized by scanning electron microscopy, the interaction between molecules was characterized by Fourier transform infrared spectroscopy, and the crystallization property of the microspheres was characterized by X-ray diffraction. The results showed that the adsorption sites of amino and hydroxyl groups had been provided by the porous chitosan/saccharomycetes microspheres for the removal of preservatives, pigments, and other additives in food. The surface roughness of microspheres could be improved by increasing the mass ratio of saccharomycetes. The increase in silica gels could make the microsphere structure more compact. The porous chitosan/saccharomycetes microspheres could be used as adsorbents to adsorb doxycycline in wastewater.

Procambarus clarkii was found to have excellent anti-wear performance against abrasive materials. To improve the wear resistance performance of the soil-engaging component of agricultural machinery, in this study, the micro-thorn and convex hull coupled geometrical structured surfaces inspired from the cephalothorax exoskeleton of the Procambarus clarkii was selected as the bionic prototype. By adopting bionic engineering techniques, three types of novel geometrical structured surfaces were proposed, which were bionic single, double and triple micro-thorn coupled convex hull surfaces (Bionic Type 2, 3 and 4, respectively). The anti-abrasive wear properties of these proposed geometrical surfaces were compared with a conventional bionic convex hull structured surface (Bionic Type 1) and a surface without any structures (smooth). Abrasive wear tests were conducted by using a rotational abrasive wear testing system. The accumulative test time was 80 h and the total wear distance was 6.09 × 10⁵ m. By adopting the EDEM software (discrete element modeling), the Archard Wear model was selected to simulate the wear behavior of five different surfaces. In addition, the wear mechanisms of different surfaces were investigated. The results showed that the smooth surface suffered the most severe abrasive were, the abrasion loss reached 194.1 mg. The anti-abrasive properties of bionic geometric structured non-smooth surfaces were greatly improved; the reduction in terms of abrasion losses ranged between 20.4% and 94.1%, as compared with the smooth surface. The wear resistance property of micro-thorn and convex hull coupled structured surfaces were greatly improved as compared with convex hull and smooth surface. Bionic Type 3 was found to have the best anti-abrasive wear property: the abrasion loss was 11.5 mg. The wear morphology was observed by a scanning electron microscope. Smooth surface was characterized with wide, large size of grinding debris, while the bionic non-smooth surface featured narrow and small size abrasive dust. The results obtained from EDEM simulation agreed well with those of the aforementioned real scenario tests. It was revealed that the wear areas of the micro-thorn and convex hull coupled structured surface were mainly concentrated on the edge of convex hull and micro-thorn that faced the coming direction of particle flow. The geometric structure of the convex hull had beneficial effects on changing the movement behavior of particles, which means the stream of particle flow could be altered from a sliding to rolling state. Consequently, the ploughing and cutting phenomena of particles that act on the surfaces were greatly mitigated. Moreover, after being coupled with micro-thorns, the anti-abrasive wear preparty of the bionic convex hull geometrical structured surface was further improved. The rebound angle of particle flow that contacted the bionic micro-thorn coupled convex hull structured surface was greater than that of the conventional convex hull surface. Therefore, the dispersion effect of particle flow was further enhanced, since the movement behavior of the subsequent impact particle flow was altered. As a result, the wear of the bionic non-smooth surface was further reduced. This biconically inspired novel micro-thorn and convex hull coupled structured surface could provide theatrical and technical references to enhance the wear resistance performance of the soil-engaging component of agricultural machinery and mitigate the problem of abrasive wear failure.

Utilizing machine vision technology based on YOLOv5, a six-axis robot can quickly identify and classify targets. However, when the YOLOv5 model is used for the recognition and grasping of small workpieces, issues such as low precision and missed detections frequently occur. This paper proposes an enhanced object recognition algorithm, integrating a CBAM attention module and an improved loss function into YOLOv5 to control the hand–eye coordination of the six-axis robot during grasping. The CBAM attention module is incorporated into the backbone network of YOLOv5 to enhance its feature extraction capabilities, while the original loss function is modified to accelerate convergence and improve regression accuracy. An experimental platform for six-axis robot hand–eye coordination grasping was built, and grasping experiments were conducted. The proposed method significantly improves the robot’s grasping accuracy, with a 99.59% mAP0.5 and a 90.83% successful grasping rate, effectively addressing the challenges of low accuracy and missed detections in traditional systems.