High-precision apple recognition and localization method based on RGB-D and improved SOLOv2 instance segmentation

Intelligent apple-picking robots can significantly improve the efficiency of apple picking, and the realization of fast and accurate recognition and localization of apples is the prerequisite and foundation for the operation of picking robots. Existing apple recognition and localization methods primarily focus on object detection and semantic segmentation techniques. However, these methods often suffer from localization errors when facing occlusion and overlapping issues. Furthermore, the few instance segmentation methods are also inefficient and heavily dependent on detection results. Therefore, this paper proposes an apple recognition and localization method based on RGB-D and an improved SOLOv2 instance segmentation approach. To improve the efficiency of the instance segmentation network, the EfficientNetV2 is employed as the feature extraction network, known for its high parameter efficiency. To enhance segmentation accuracy when apples are occluded or overlapping, a lightweight spatial attention module is proposed. This module improves the model position sensitivity so that positional features can differentiate between overlapping objects when their semantic features are similar. To accurately determine the apple-picking points, an RGB-D-based apple localization method is introduced. Through comparative experimental analysis, the improved SOLOv2 instance segmentation method has demonstrated remarkable performance. Compared to SOLOv2, the F1 score, mAP, and mIoU on the apple instance segmentation dataset have increased by 2.4, 3.6, and 3.8%, respectively. Additionally, the model’s Params and FLOPs have decreased by 1.94M and 31 GFLOPs, respectively. A total of 60 samples were gathered for the analysis of localization errors. The findings indicate that the proposed method achieves high precision in localization, with errors in the X, Y, and Z axes ranging from 0 to 3.95 mm, 0 to 5.16 mm, and 0 to 1 mm, respectively

Physics-informed neural network for friction-involved nonsmooth dynamics problems

Friction-induced vibration (FIV) is very common in engineering areas. Analysing the dynamic behaviour of systems containing a multiple-contact point frictional interface is an important topic. However, accurately simulating nonsmooth/discontinuous dynamic behaviour due to friction is challenging. This paper presents a new physics-informed neural network approach for solving nonsmooth friction-induced vibration or friction-involved vibration problems. Compared with schemes of the conventional time-stepping methodology, in this new computational framework, the theoretical formulations of nonsmooth multibody dynamics are transformed and embedded in the training process of the neural network. Major findings include that the new framework not only can perform accurate simulation of nonsmooth dynamic behaviour, but also eliminate the need for extremely small time steps typically associated with the conventional time-stepping methodology for multibody systems, thus saving much computation work while maintaining high accuracy. Specifically, four kinds of high-accuracy PINN-based methods are proposed: (1) single PINN; (2) dual PINN; (3) advanced single PINN; (4) advanced dual PINN. Two typical dynamics problems with nonsmooth contact are tested: one is a 1-dimensional contact problem with stick-slip, and the other is a 2-dimensional contact problem considering separation-reattachment and stick-slip oscillation. Both single and dual PINN methods show their advantages in dealing with the 1-dimensional stick-slip problem, which outperforms conventional methods across friction models that are difficult to simulate by the conventional time-stepping method. For the 2-dimensional problem, the capability of the advanced single and advanced dual PINN on accuracy improvement is shown, and they provide good results even in the cases when conventional methods fail.Comment: 38 Pages, 24 figure

Theoretical calculation of cesium deposition and co-deposition with electronegative elements on the plasma grid in negative ion sources

We studied the work function of cesium deposition and co-deposition with the electronegative element on the plasma grid (PG) using the first-principles calculations. The impurity particles may exist in the background plasma and vacuum chamber wall, and the work function of the PG will be affected. The results indicate that the minimum work functions of pure cesium deposition on Mo (110), W (110), and Mo (112) are reached at a partial monolayer. They are 1.66 eV (σ = 0.56 θ), 1.69 eV (σ = 0.75 θ), and 1.75 eV (σ = 0.88 θ), respectively. An appropriate co-deposition model consisting of cesium with electronegative elements can further decrease the work function. The coverage of cesium and electronegative elements are both 0.34 θ in all the co-deposition models. The F-Cs co-deposition model where the Cs atom and F atom are aligned along the surface normal obtains the lowest work function. They are 1.31 eV for F-Cs on Mo (110), and 1.23 eV for F-Cs on W (110), respectively. The change in work function is linearly related to the change in dipole moment density with a slope of −167.03 VÅ. For pure cesium deposition, two factors control the change in dipole-moment density, one is the electron transfer between adsorbates and the substrate, and another one is the restructuring of surface atoms. There are two additional factors for the co-deposition model. One is the intrinsic dipole moment of the double layer, the other is the angle between the intrinsic dipole moment and the surface. The latter two factors play important roles in increasing the total dipole moment

Sport tickets pricing strategy with home team’s crowd effect

This paper investigates the impact of the crowd effect and financing constraints on pricing strategy by constructing an intertemporal model and introducing the crowd effect into a monopolistic home team’s decision-making framework. The results demonstrate that a stronger crowd effect and a larger depreciation rate are always beneficial to the expected profits of the home team and the home team may price along the inelastic portion of the static demand curve in periods 1–3, as long as the expected deferred marginal revenue and the additive price from the performance of the preceding match are sufficiently large.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/175898/1/mde3715.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/175898/2/mde3715_am.pd

To Explore the Low-dose CT and QCT “One-stop-shop”Scan Technology for Physical Examination Crowd

Objective: To explore the application of noise index combined with automatic tube current regulation technology in the one-stop scanning of chest and lumbar QCT physical examination. Method: 100 patients who unferwent thoracic CT and lumbar QCT scan in our medical examination were prospectively collected and randomly divided into two groups( conventional dose group and ow dose group). There were 50 patients in the conventianl group (noise index set to NI=8.5) and 50 patients in the low dose group (noise index set to NI=14). Their height, weight and BMI were recorded, as well as the mean BMD of L1, L2 in both radiation and low dose groups, and L1, L2 in the conventional dose group. The differences of radiation dose and mean bone mineral density between the two groups were compared. Results: The average scanning dose was 387.65 mGy in the conventional dose group and 73.18 mGy in the low dose group. There was statistical differences in radiation dose between the two groups. The mean bone mineral density (BMD) of L1 and L2 was 119.71 in the conventional dose group, and that of L1 and L2 was 123.65 in the low dose group. There was no statistical difference between the two groups. Conclusion: Low dose CT scan of thoracic and lumbar spine can not only meet the needs of lung screening and bone mineral density assessment but also greatly reduce radiation dose. It can be widely used in physical examination

Effect of Heat Input on Microstructure and Properties of Laser-Welded 316L/In601 Dissimilar Overlap Joints in High-Temperature Thermocouple

Heat input, a crucial factor in the optimization of high-temperature thermocouple laser welding, has a significant impact on the appearance and mechanical properties of dissimilar welded joints involving stainless-steel- and nickel-based alloys. This study focuses on laser overlay welding of austenitic stainless steels and nickel-based alloys. The findings indicate that an increase in heat input has a more pronounced effect on the penetration depth and dilution rate. Under high heat input, the weld has cracks, spatter, and other defects. Additionally, considerable amounts of chromium (Cr) and nickel (Ni) elements are observed outside the grain near the crack, and their presence increases with higher heat input levels. Phase analysis reveals the presence of numerous Cr2Fe14C and Fe3Ni2 phases within the weld. The heat input increases to the range of 30–35 J/mm, and the weld changes from shear fracture to tensile fracture. In the center of the molten pool, the Vickers hardness is greater than that of the base metal, while in the fusion zone, the Vickers hardness is lower than that of the base metal. The overall hardness is in a downward trend with the increase of heat input, and the minimum hardness is only 159 HV0.3 at 40 J/mm. The heat input falls within the range of 28–30 J/mm, and the temperature shock resistance is at its peak

The Fracturing Behavior of Tight Glutenites Subjected to Hydraulic Pressure

Tight glutenites are typically composed of heterogeneous sandstone and gravel. Due to low or ultra-low permeability, it is difficult to achieve commercial production in tight glutenites without hydraulic fracturing. Efficient exploitation requires an in-depth understanding of the fracturing behavior of these reservoirs. This paper provides a numerical method that integrates the digital image processing (DIP) technique into a numerical code rock failure process analysis (RFPA). This method could consider the glutenite heterogeneities, including intrarock and interrock heterogeneities, and the practicability is verified through two numerical tests. Two-dimensional (2D) simulations show hydraulic fractures (HFs) can penetrate or deflect to propagate along the gravels, depending on the magnitude of stress anisotropy and gravel strength. Three-dimensional (3D) simulations with the consideration of gravel distribution orientation, gravel size and axial ratio show HFs could propagate past the gravel with no deflection, forming a bypass fracture that is not easy to observe in common laboratory experiments. HFs could also deflect to propagate along the gravels. The impacts of the gravel distribution orientation, gravel size and axial ratio are discussed in detail. The main propagation modes of HFs intersecting the gravels are summarized as: (1) penetrating directly; (2) deflecting to propagate along the gravels to form distorted HFs; (3) propagating to bypass the gravels; (4) a combination of (1) and (2), or (2) and (3)

Rolling circle amplification (RCA) -based biosensor system for the fluorescent detection of miR-129-2-3p miRNA

Herein, a versatile fluorescent bioanalysis platform for sensitive and specific screening of target miRNA (miR-129-2-3p) was innovatively designed by applying target-induced rolling circle amplification (RCA) for efficient signal amplification. Specifically, miR-129-2-3p was used as a ligation template to facilitate its ligation with padlock probes, followed by an RCA reaction in the presence of phi29 DNA polymerase. The dsDNA fragments and products were stained by SYBR Green I and then detected by fluorescence spectrophotometry. As a result, miR-129-2-3p concentrations as low as 50 nM could be detected. Furthermore, the expression of miR-129-2-3p in breast cancer patients was about twice that in healthy people. Therefore, the results indicated that the RCA-based biosensor system could be a valuable platform for miRNA detection in clinical diagnosis and biomedical study

Changes in Intestinal Microbiota Are Associated with Islet Function in a Mouse Model of Dietary Vitamin A Deficiency

Aims. The underlying mechanisms involved in Vitamin A- (VA-) related changes in glucose metabolic disorders remain unclear. Recent evidence suggests that intestinal microbiota is closely linked to the metabolic syndrome. Here, we explored whether and how intestinal microbiota affects glucose homeostasis in VA-deficient diet-fed mice. Methods. Six-week-old male C57BL/6 mice were randomly placed on either a VA-sufficient (VAS) or VA-deficient (VAD) diet for 10 weeks. Subsequently, a subclass of the VAD diet-fed mice was switched to a VA-deficient rescued (VADR) diet for an additional 8 weeks. The glucose metabolic phenotypes of the mice were assessed using glucose tolerance tests and immunohistochemistry staining. Changes in intestinal microbiota were assessed using 16S gene sequencing. The intestinal morphology, intestinal permeability, and inflammatory response activation signaling pathway were assessed using histological staining, western blots, quantitative-PCR, and enzyme-linked immunosorbent assays. Results. VAD diet-fed mice displayed reduction of tissue VA levels, increased area under the curve (AUC) of glucose challenge, reduced glucose-stimulated insulin secretion, and loss of β cell mass. Redundancy analysis showed intestinal microbiota diversity was significantly associated with AUC of glucose challenge and β cell mass. VAD diet-driven changes in intestinal microbiota followed the inflammatory response with increased intestinal permeability and higher mRNA expression of intestinal inflammatory cytokines through nuclear factor-κB signaling pathway activation. Reintroduction of dietary VA to VAD diet-fed mice restored tissue VA levels, endocrine hormone profiles, and inflammatory response, which are similar to those observed following VAS-controlled changes in intestinal microbiota. Conclusions. We found intestinal microbiota effect islet function via controlling intestinal inflammatory phenotype in VAD diet-fed mice. Intestinal microbiota influences could be considered as an additional mechanism for the effect of endocrine function in a VAD diet-driven mouse model