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Based on the conventional triaxial compression test of marble, the microscopic parameters corresponding to the macroscopic mechanical properties of marble were obtained by PFC2D, and on this basis, discrete element method models were established to conduct numerical tests of triaxial compression of marble under different confining pressures and loading rates to study the effect of loading rates on the rock specimens. Under the same confining pressure, brittle damage occurs in marble when the loading rate is low, and the damage type transforms from brittle to ductile as the loading rate increases. The peak strength, cracking stress, damage stress, cohesion, and internal friction angle of marble appear to increase with the increase in the loading rate under the same confining pressure. The characteristic stresses and strength parameters are linearly related to the loading rate. The influence of the loading rate on the peak strength is the most significant. With the increase in the confining pressure, the fitting coefficient of the linear relationship between initiation stress and loading rate decreases from 18.9 to 15.4 for different confining pressures, indicating that the growth rate of initiation stress decreases with the increase in the confining pressure when the loading rate is increased, and the increase in confining pressure suppresses the growth rate of initiation stress with loading rate.

Automatic segmentation of early esophagus cancer (EEC) in gastrointestinal endoscopy (GIE) images is a critical and challenging task in clinical settings, which relies primarily on labor-intensive and time-consuming routines. EEC has often been diagnosed at the late stage since early signs of cancer are not obvious, resulting in low survival rates. This work proposes a deep learning approach based on the U-Net++ method to segment EEC in GIE images. A total of 2690 GIE images collected from 617 patients at the Digestive Endoscopy Center, West China Hospital of Sichuan University, China, have been utilized. The experimental result shows that our proposed method achieved promising results. Furthermore, the comparison has been made between the proposed and other U-Net-related methods using the same dataset. The mean and standard deviation (SD) of the dice similarity coefficient (DSC), intersection over union (IoU), precision (Pre), and recall (Rec) achieved by the proposed framework were DSC (%) ​= ​94.62 ​± ​0.02, IoU (%) ​= ​90.99 ​± ​0.04, Pre ​(%) = ​94.61 ​± ​0.04, and Rec (%) ​= ​95.00 ​± ​0.02, respectively, outperforming the others. The proposed method has the potential to be applied in EEC automatic diagnoses.

Studies have revealed that rewards promote long-term memory, even in an incidental way. However, most previous studies using the incidental paradigm have included two reward levels, and it is still not clear how the reward magnitude influences memory. Adopting the incidental paradigm and three reward levels, the current study revealed that the reward magnitude impacted 1-d delayed episodic memory in a nonlinear, inverted U-shaped pattern. An additional experiment showed that there was no reward effect in immediate episodic memory. Our results support the dopaminergic memory consolidation theory and further imply that the reward magnitude needs to be considered in the theory.

Ammonium, as a major inorganic source of nitrogen (N) for sweet potato N utilization and growth, is specifically transported by ammonium transporters (AMTs). However, the activities of AMT family members in sweet potatoes have not been analyzed. In the present study, the sweet potato cultivar ‘Pushu 32’, which is planted in a large area in China, was used in field experiments at the Agricultural Base of Hainan University (20°06′ N, 110°33′ E) in 2021, and Sanya Nanfan Research Institute of Hainan University (18°30′ N, 109°60′ E) in 2022. Four N levels were tested: 0, 60, 120, and 180 kg ha−1. The results are as follows. Twelve IbAMT genes were identified in the sweet potato genome, which were classified into three distinct subgroups based on phylogeny; the same subgroup genes had similar properties and structures. IbAMT1.3 and IbAMT1.5 were mostly expressed in the storage roots under N deficiency. Compared with the NN and HN groups, IbAMT1.3 and IbAMT1.5 expressions, N content in storage roots, N uptake efficiency at the canopy closure, N fertilization contribution rates, number of storage roots per plant, storage root weight, and yield were all increased in the MN group. Furthermore, there was a significant positive correlation between the expressions of IbAMT1.3 and IbAMT1.5 with N content in the storage roots of sweet potato. In a word, IbAMT1.3 and IbAMT1.5 may regulate N utilization, affect the development of the storage root. and determine the yield of sweet potato. The results provide valuable insights into the AMT gene family’s role in the use of N and effects on storage root development and yield in sweet potatoes.

The holes and defects in rock materials have a great impact on the mechanical properties and failure mechanism of rock, cracks often appear in the form of flat ellipses in natural rock mass, and the current research is still insufficient. For this purpose, based on the Particle Flow Code (PFC) of discrete element particle flow program, the numerical prefabricated fractured rock samples with the ratios of the long and short axes of the elliptical fractures being 5, 7.5, 10, 12.5, and 15 were simulated in order to obtain the strength and failure characteristics, stress concentration characteristics at tips of numerical rock samples in uniaxial compression test. The results of the numerical test simulation show that: (1) When the rock models with prefabricated elliptical crack were damaged, the initial cracks occurred at the end of the short axis of the elliptical crack, and penetrated up and down from the surface of the elliptical crack, the wing cracks occurred at both ends of the long axis, gradually formed a macro-crack, and the secondary cracks extended near the wing crack. (2) With the increase of the ratios a:b of long and short axes of the elliptical fracture, the strength and elastic modulus of the numerical rock samples gradually decreased, Poisson’s ratio gradually increased, and the total number of micro-cracks in the rock models decreased. (3) The numerical solutions of stress concentration factor k obtained by numerical simulations at the tip of the elliptical crack increased with the increase in the ratio of a:b; it was highly consistent with the variation law of the analytical solution of the stress concentration factor calculated by the theory of flat ellipse. The stress concentration is an important reason for failure of rock with elliptical cracks. Study on the crack tip will be very useful and significant.

Two Al-Cu-Mg(-Ag) aluminium alloys, having the same base composition of Al-5.11Cu-0.96 Mg-0.58Mn-0.12Zr (wt.%) but different Ag contents, 0 and 0.7 Ag (wt.%), and accordingly denoted 0A and 7A samples, were aged at 185 °C. In early-ageing, the formation of disk-like Mg-Cu and Mg-Ag nano(co–)clusters can be quantitatively examined by Small angle X-ray scattering (SAXS), respectively. In the prolonged ageing of the 0A samples, the thickening in the disk-like θ-precipitates leads to a lower aspect ratio. For S-precipitates, the change in the total surface area and the single-particle surface area indicates that the coalescence mechanism is prevalent from peak-ageing to over-ageing, and then after over-ageing, the precipitate coarsening dominates. The coarsening in S and θ precipitates presumably leads to a lower mechanical strength. Alternatively, in the aged 7A sample, the SAXS technique in conjunction with transmission electron microscopy (TEM) quantitatively reveals Ω-precipitates possessing a nearly constant thickness but an increase in diameter with ageing time. Additionally, the stable behaviors of the total surface and size of S-precipitates illuminate that the coalescence/coarsening mechanisms are significantly slowed down. The concurrently-existing precipitation kinetics of Ω and S have provided an in-depth understanding of the higher strength of the aged 7A sample.

The ability of organic photovoltaics (OPVs) to be deposited on flexible substrates by roll-to-roll (R2R) processes is highly attractive for rapid mass production. Many research teams have demonstrated the great potential of flexible OPVs. However, the fabrication of R2R-coated OPVs is quite limited. There is still a performance gap between the R2R flexible OPVs and the rigid OPVs. In this study, we demonstrate the promising photovoltaic characteristics of flexible OPVs fabricated from blends of low bandgap polymer poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)-benzo[1,2-b:4,5-b′]dithiophene))-alt-(5,5-(1′,3′-di-2-thienyl-5′,7′-bis(2-ethylhexyl)benzo[1′,2′-c:4′,5′-c′]dithiophene-4,8-dione)] (PBDB-T) and non-fullerene 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2′,3′-d′]-s-indaceno[1,2-b:5,6-b′]dithiophene (ITIC). We successfully R2R slot-die coated the flexible OPVs with high power conversion efficiency (PCE) of over 8.9% under irradiation of simulated sunlight. Our results indicate that the processing parameters significantly affect the PCE of R2R flexible OPVs. By adjusting the amount of solvent additive and processing temperature, as well as optimizing thermal annealing conditions, the high PCE of R2R slot-die coated OPVs can be obtained. These results provide significant insights into the fundamentals of highly efficient OPVs for the R2R slot-die coating process.

The human digestive system is susceptible to various viruses and bacteria, which can lead to the development of lesions, disorders, and even cancer. According to statistics, colorectal cancer has been a leading cause of death in Taiwan for years. To reduce its mortality rate, clinicians must detect and remove polyps during gastrointestinal (GI) tract examinations. Recently, colonoscopies have been conducted to examine patients’ colons. Even so, polyps sometimes remain undetected. To help medical professionals better identify abnormalities, advanced deep learning algorithms that can accurately detect colorectal polyps from images should be developed. Prompted by this proposition, the present study combined U-Net and YOLOv4 to create a two-stage network algorithm called UY-Net. This new algorithm was tested using colonoscopy images from the Kvasir-SEG dataset. Results showed that UY-Net was significantly accurate in detecting polyps. It also outperformed YOLOv4, YOLOv3-spp, Faster R-CNN, and RetinaNet by achieving higher spatial accuracy and overall accuracy of object detection. As the empirical evidence suggests, two-stage network algorithms like UY-Net will be a reliable and promising aid to image detection in healthcare.