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Abstract Background This study aims to assess the diagnostic utility of vertebral CT value and CT value difference in distinguishing between fresh and old osteoporotic vertebral compression fractures (OVCF). Methods A retrospective analysis was conducted on 118 patients with OVCF who underwent both MRI and CT examinations at our hospital. The nature of the fractured vertebra was determined according to MRI. The CT value of the fractured vertebrae and the mean CT value of the adjacent normal vertebrae were measured separately, and the differences between these values were calculated. Independent samples t-tests were used to compare CT value and CT value difference among all groups. The receiver operating characteristic (ROC) curve was employed to determine the optimal cut-off value for both CT value and CT value difference in differentiating fresh and old fractures. Results The study included a total of 163 fractured vertebrae from 118 patients. The CT value of fresh fractured vertebrae was significantly higher than those of adjacent normal vertebrae, which was statistically different (P 0.05). There were significant differences in CT value and CT value difference between fresh fractured vertebrae and old fractured vertebrae (P

A cost-effective, high-performance Mg-2.0Zn-1.5Mn alloy was fabricated using closed forging extrusion (CFE). The results reveal that CFE can promote a dynamic recrystallization (DRX) ratio and enhance the residual dislocation density in deformed grains and subgrains. Grain refinement is achieved through multiple DRX mechanisms, particle-stimulated nucleation, and pinning effects. In addition, the basal texture and precipitation behavior are significantly influenced by pre-forging in CFE. Finally, grain refinement and substantial residual dislocations result in a good combination of strength and plasticity, with the ultimate tensile strength of 400 MPa and elongation of 22.1%, respectively. A novel strategy for regulating the bimodal grain structure is proposed to guide the optimization of the mechanical performance of rare-earth free Mg alloys.

Abstract Background Sacral screw loosening is a typical complication after internal fixation surgery through the vertebral arch system. Bicortical fixation can successfully prevent screw loosening, and how improving the rate of bicortical fixation is a challenging clinical investigation. Objective To investigate the feasibility of improving the double corticality of sacral screws and the optimal fixation depth to achieve double cortical fixation by combining the torque measurement method with bare hands. Methods Ninety-seven cases of posterior lumbar internal fixation with pedicle root system were included in this study. Based on the tactile feedback of the surgeon indicating the expected penetration of the screw into the contralateral cortex of the sacrum, the screws were further rotated by 180°, 360°, or 720°, categorized into the bicortical 180° group, bicortical 360° group, and bicortical 720° group, respectively. Intraoperatively, the torque during screw insertion was recorded. Postoperatively, the rate of double-cortex engagement was evaluated at 7 days, and screw loosening was assessed at 1 year follow-up. Results The bicortical rates of the 180° group, 360° group, and 720° group were 66.13%, 91.18% and 93.75%, respectively. There were statistically significant differences between the 180° group and both the 360° and 720° groups (P 0.05).The rates of loosening of sacral screws in the 180° group, 360° group, and 720° group were 20.97%, 7.35% and 7.81%, respectively. There were statistically significant differences between the 180° group and both the 360° and 720° groups (P 0.05). The bicortical 360° group achieved a relatively satisfactory rate of dual cortical purchase while maintaining a lower rate of screw loosening. Conclusion Manual insertion of sacral screws with the assistance of a torque measurement device can achieve a relatively satisfactory dual cortical purchase rate while reducing patient hospitalization costs.

Objective To investigate the correlation between magnetic resonance imaging-based vertebral bone quality (VBQ) score and screw loosening after dynamic pedicle screw fixation with polyetheretherketone (PEEK) rods, and evaluate its predictive value. Methods A retrospective analysis was conducted on the patients who underwent dynamic pedicle screw fixation with PEEK rods from March 2017 to June 2022. Data on age, sex, body mass index, hypertension, diabetes, hyperlipidemia history, long-term smoking, alcohol consumption, VBQ score, L1–4 average Hounsfield unit (HU) value, surgical fixation length, and the lowest instrumented vertebra were collected. Logistic regression analysis was employed to assess the relationship between VBQ score and pedicle screw loosening (PSL). Results A total of 24 patients experienced PSL after surgery (20.5%). PSL group and non-PSL group showed statistical differences in age, number of fixed segments, fixation to the sacrum, L1–4 average HU value, and VBQ score (p < 0.05). The VBQ score in the PSL group was higher than that in the non-PSL group (3.56 ± 0.45 vs. 2.77 ± 0.31, p < 0.001). In logistic regression analysis, VBQ score (odds ratio, 3.425; 95% confidence interval, 1.552–8.279) were identified as independent risk factors for screw loosening. The area under the receiver operating characteristic curve for VBQ score predicting PSL was 0.819 (p < 0.05), with the optimal threshold of 3.15 (sensitivity, 83.1%; specificity, 80.5%). Conclusion The VBQ score can independently predict postoperative screw loosening in patients undergoing lumbar dynamic pedicle screw fixation with PEEK rods, and its predictive value is comparable to HU value.

This investigation was conducted to explore the impact of extrusion temperature on the microstructure, mechanical properties, and osteogenic differentiation of the as-extruded Mg-1Ho alloy. The Mg-1Ho alloy was extruded at three different temperatures, i.e., 320, 350, and 380 °C, leading to variation in its grain size and texture intensity. With decreasing extrusion temperature, a significant increase was achieved in its room-temperature ultimate tensile strength (UTS) and yield strength (YS). After being subjected to an extrusion temperature of 320 °C, furthermore, Mg-1Ho alloy can effectively promote osteogenic proliferation and differentiation, anti-inflammatory, along with osteogenic gene expression. Our findings emphasized that adding extract from Mg-1Ho alloy extruded at 320 °C enhanced the ability of osteogenesis, demonstrating its potential as a biomaterial to improve cell performance and fate.

As digital technology continues to advance rapidly, the substantial operational electricity costs associated with the extensive deployment of globally distributed internet data centers have become a significant concern. Addressing this challenging issue is crucial for the future expansion of internet data centers. In this paper, a coordinated strategy is proposed that leverages the spatial–temporal flexibility of internet data centers and their interaction with the power system. Firstly, an energy-aware internet data center loading model is introduced that incorporates multiple coupled scheduling methods to maximize the utilization of internet data centers' flexibility potential. Secondly, the proposed internet data centers loading model is integrated into a coordinated optimization model aimed at achieving higher profits through cost reduction in response to varying electricity prices across multiple regions. To facilitate the coordinated operation of geo-graphically internet data centers, an incentive profit-sharing mechanism based on Nash Bargaining theory is designed to fairly distribute coordination profits based on the contribution ratio of each data center in coordination. Through comprehensive case studies utilizing real-world datasets, the results demonstrate that the internet data center loading model, considering multiple coupled scheduling methods, can enhance internet data centers’ flexibility potential, resulting in a significant 11.73% reduction in total cost, with the coupling relationship accounting for 5.05% of this reduction. Furthermore, the proposed profit-sharing mechanism effectively fosters coordination and enthusiasm among geographically distributed internet data centers.

An effective scheduling method for ship arrival and departure is crucial for maximizing port resources and improving waterway navigation efficiency. In order to enhance the efficacy of ship arrival and departure scheduling, a scheduling model is developed with the objective of minimizing the total scheduling time and minimizing the total waiting time of the ship. Furthermore, an enhanced three-generation non-dominated sorting genetic algorithm, NSGA-III, is proposed as a solution to the ship scheduling model. The improved NSGA-III algorithm employs the Metropolis criterion in the simulated annealing algorithm in conjunction with the small habitat technique to optimize the initial population of NSGA-III. Additionally, it utilizes a multi-objective parallel strategy and an adaptive cross-variation strategy to enhance the convergence ability and robustness of NSGA-III, thereby preventing it from falling into a local optimum. The improved NSGA-III is employed to resolve the scheduling model under disparate operational conditions within the primary channel of Tianjin Port. The algorithm’s efficacy is evaluated in comparison to the classical NSGA-II and NSGA-III algorithms. The results show that the im-proved NSGA-III algorithm is better than the NSGA-II and NSGA-III algorithms. The optimal scheduling plan for ship entry and exit in the main channel of Tianjin Port and the sequence of ship arrival and departure scheduling were obtained by Pareto solving set and combining with Topsis evaluation method. The method proposed in this paper offers a novel approach to the optimization of ship arrival and departure scheduling.

The AtoN department is responsible for mastering the drift characteristics of buoys, conducting targeted buoy inspections and resets, and providing accurate buoy position information for ship navigation. To analyze the buoy drift pattern, a K-Nearest Neighbor(KNN) improved Kernel Density Estimation(KED) method(KNN-KDE) is proposed to optimize the single bandwidth in the more complex distribution of the dataset can only depict the approximate trend of the data, while the details of the data changes can not be accurately estimated. KNN-KDE is utilized to estimate the coordinates of the buoy’s gyration center and its radius of gyration, which establishes a mathematical model for buoy drift. Based on this approach, the telemetry position data from typical buoys in the main channel of Xiamen Harbor is collected to analyze the drift pattern of the buoys. This analysis provides a useful reference for the safety of navigation.

The Clustering by Fast Search and Find of Density Peaks (DPC) algorithm is a clustering method that automatically identifies clustering centers based on density and relative distance. It has several advantages, including the ability to identify arbitrarily shaped clusters and requiring few input parameters. However, the density measure used in DPC does not consider the spatial distribution characteristics of the sample points in the data set. The clustering performance is suboptimal for datasets with significant differences in cluster density. Additionally, its non-central sample point assignment method is less error-tolerant, which can result in successive assignment errors and a domino effect, ultimately leading to poor clustering accuracy. To address these shortcomings, we propose an improved DPC algorithm based on shared nearest neighbor and multi-cluster fusion (SM-DPC). The local density of sample points is redefined using K-nearest neighbors, which makes the density metric more consistent with the local structural characteristics of the dataset. A two-step allocation strategy for non-central sample points based on shared nearest neighbors is proposed to improve the accuracy of allocation of non-central sample points. A multi-cluster fusion strategy is used to correct the centroid selection bias for datasets where sample points are not uniformly distributed. The experimental results demonstrate that SM-DPC is capable of clustering datasets with arbitrary shape and density distributions effectively. Furthermore, it exhibits superior performance and broader adaptability to different types of datasets compared to DBSCAN, K-means algorithms, and other DPC optimization algorithms.

Autonomous collision avoidance decision making for maritime autonomous surface ships (MASS), as one of the key technologies for MASS autonomous navigation, is a research hotspot focused on by relevant scholars in the field of navigation. In order to guarantee the rationality, efficacy, and credibility of the MASS autonomous collision avoidance scheme, it is essential to design the MASS autonomous collision avoidance algorithm under the stipulations of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). In order to enhance the autonomous collision avoidance decision-making capability of MASS in accordance with the relevant provisions of COLREGs, an improved NSGA-II autonomous collision avoidance decision-making algorithm based on the good point set method (GPS-NSGA-II) is proposed, which incorporates the collision hazard and the path cost of collision avoidance actions. The experimental results in the four simulation scenarios of head-on situation, overtaking situation, crossing situation, and multi-ship encounter situation demonstrate that the MASS autonomous collision avoidance decision making based on the GPS-NSGA-II algorithm under the constraints of COLREGs is capable of providing an effective collision avoidance scheme that meets the requirements of COLREGs in common encounter situations and multi-ship avoidance scenarios promptly, with a promising future application.

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a classic density-based clustering method that can identify clusters of arbitrary shapes in noisy datasets. However, DBSCAN requires two input parameters: the neighborhood distance value (Eps) and the minimum number of sample points in its neighborhood (MinPts), to perform clustering on a dataset. The quality of clustering is highly sensitive to these two parameters. This paper introduces a parameter-adaptive DBSCAN clustering algorithm based on the Whale Optimization Algorithm (WOA-DBSCAN) to tackle this issue. The algorithm determines the parameter range based on the dataset distribution and utilizes the silhouette coefficient as the objective function. It iteratively selects the two input parameters of DBSCAN within the parameter range using the WOA. This approach ultimately achieves adaptive clustering of DBSCAN. Experimental results on five typical artificial datasets and six real UCI datasets demonstrate the effectiveness of the proposed WOA-DBSCAN algorithm. Compared with DBSCAN and its related optimization algorithms, WOA-DBSCAN shows significant improvements. The F-values of WOA-DBSCAN increased by 9.8%, 13.2%, and 2%, respectively, in two-dimensional artificial datasets. Additionally, the accuracy values on low to medium dimensional real datasets increased by 22.3%, 10%, and 23.3%. Hence, WOA-DBSCAN can maintain the clustering ability of DBSCAN while achieving adaptive parameter clustering.

This work systematically investigates the impact of the dilute Sc addition on microstructures and mechanical properties in Mg alloys. Electron back scattered diffraction, slip traces analysis, transmission electron microscopy, and visco-plastic self-consistent polycrystal constitutive (VPSC) modeling were performed to investigate the deformation mechanisms in the tensile testing, especially the activation of slip. The results showed that as-solid solution samples only consisted of α-Mg phase. After extrusion, all samples exhibited a similar average grain size. With the increment of the Sc content, the ductility of the samples was significantly improved, which failure elongation (FL) of Mg-xSc (x = 0.3, 0.6, 0.9 wt.%) alloys improved from 14.4% to 24.8%. The yield strength of each alloy is similar, about 200 MPa. VPSC results indicated that the difference value of the initial slip resistance (τ0) between prismatic slip and basal slip decreases from 63 MPa to 49 MPa, and the difference value of τ0 between pyramidal slip and basal slip decreases from 72 MPa to 57 MPa. The VPSC and the two-beam diffraction results confirmed that the pyramidal slip and prismatic slip were activated in tensile testing. The quantitative analysis of the slip trace line verified that the volume of non-basal slip reached 49.5% when the Sc content increased to 0.9 wt.%. Therefore, the addition of Sc in solid solution increased the amount of pyramidal and prismatic dislocation activities during the deformation process, which was beneficial to coordinate the c-axis strain, and finally improved ductility of Mg alloy.

Probing ssDNA binding to TAR-DNA-binding protein-43 (TDP-43) prion-like domain (PLD) through NMR shows key interactions for nucleic acid to drive liquid-liquid phase separation (LLPS) of intrinsically-disordered proteins.

Within the scope of this study, the evolution of microstructures and mechanical properties in as-extruded Mg–Sc alloys were systematically explored with Mn content from 0.3 to 0.9 wt.%. The results showed that a completely recrystallized crystal structure was obtained in Mg-xMn-Sc alloys, and the average grain size decreased from 12.75 to 3.35 μm with the increase of Mn content. In addition, the increment of Mn content reduced the texture intensity from 14.95 to 7.65. Thus, Mg–Sc alloys’ tensile yield and ultimate strength significantly improved. Meanwhile, Mn addition led to the activation of non-basal slip, especially prismatic slip, which significantly enhanced the ductility of alloys. Moreover, the activation of non-basal slip by alloying Mn can be attributed to the reduction of the critical shear stress (CRSS) gap between basal slip and non-basal slip.

ObjectiveThis article studies the characteristics of the flow-induced vibration (FIV) of a cylinder with passive turbulence control and nonlinear springs in a wide range of Reynolds numbers in order to use the FIV of the PTC-cylinder to improve the efficiency of power generators.MethodsThe FIV of a PTC-cylinder supported by linear and nonlinear springs is studied by solving the 2-D URANS equations in combination with the Spalart-Allmaras turbulence model with dynamic mesh and user-defined-function (UDF) in FLUENT. The numerical simulation results are compared with the experimental results.ResultsCompared with linear springs, the amplitude of a cylinder with piecewise-linear springs is enhanced significantly, and the vortex mode becomes more complicated. When the spring stiffness of the first segment is greater than that of the second segment, the amplitude of the cylinder becomes larger, the oscillation frequency becomes smaller and the vortex mode of the cylinder becomes more complicated as the piecewise point of the piecewise-linear function becomes smaller.ConclusionsThe FIV of a PTC-cylinder with nonlinear springs is different from that with linear springs. The fluid-structure interaction is enhanced effectively with the reasonable selection of the piecewise point, providing theoretical and technical support for improving the efficiency of hydrokinetic energy conversion devices.

BackgroundAlthough the increase of perioperative complications in the elderly undergoing pancreaticoduodenectomy (PD) surgery has been recognized, the definition of the “old patient” of PD in the studies is different and there is no accepted cut-off value at present.Methods279 consecutive patients who have undergone PD in our center between January 2012 and May 2020 were analyzed. Demographic features, clinical-pathological data and short-term outcomes were collected. The patients were divided into two groups, and the cut-off value (62.5 years) is picked based on the highest Youden Index. Primary endpoints were perioperative morbidity and mortality, and complications were classified according to the Clavien-Dindo Score.ResultsA total of 260 patients with PD were included in this study. Postoperative pathology confirmed pancreatic tumors in 62 patients, bile duct tumor in 105, duodenal tumor in 90, and others in 3. Age (OR = 1.09, P

Abstract Pancreatic diseases, a serious threat to human health, have garnered considerable research interest, as they are associated with a high mortality rate. However, owing to the uncertain etiology and complex pathophysiology, the treatment of pancreatic diseases is a challenge for clinicians and researchers. Exosomes, carriers of intercellular communication signals, play an important role in the diagnosis and treatment of pancreatic diseases. Exosomes are involved in multiple stages of pancreatic disease development, including apoptosis, immune regulation, angiogenesis, cell migration, and cell proliferation. Thus, extensive alterations in the quantity and variety of exosomes may be indicative of abnormal biological behaviors of pancreatic cells. This phenomenon could be exploited for the development of exosomes as a new biomarker or target of new treatment strategies. Several studies have demonstrated the diagnostic and therapeutic effects of exosomes in cancer and inflammatory pancreatic diseases. Herein, we introduce the roles of exosomes in the diagnosis and treatment of pancreatic diseases and discuss directions for future research and perspectives of their applications.

Background: The clinically relevant postoperative pancreatic fistula (CR-POPF) is significantly correlated with a high post-pancreaticoduodenectomy (PD) mortality rate. Several studies have reported an association between visceral obesity and CR-POPF. Nevertheless, there are many technical difficulties and controversies in the measurement of visceral fat. The aim of this research was to determine whether the visceral pancreatic neck anterior distance (V-PNAD) was a credible predictor for CR-POPF. Methods: We retrospectively analyzed the data of 216 patients who underwent PD in our center between January 2016 and August 2021. The correlation of patients’ demographic information, imaging variables, and intraoperative data with CR-POPF was assessed. Furthermore, areas under the receiver operating characteristic curves for six distances (abdominal thickness, visceral thickness, abdominal width, visceral width, abdominal PNAD, V-PNAD) were used to identify the best imaging distance to predict POPF. Results: In the multivariate logistic analysis, V-PNAD (P 3.97 cm or females with a V-PNAD >3.66 cm were included into the high-risk group. The high-risk group had a higher prevalence of CR-POPF (6.5% vs. 45.1%, P 3.97 cm; females, V-PNAD >3.66 cm) have a high incidence of CR-POPF and poor short-term post-PD prognosis. Therefore, surgeons should perform PD carefully and take adequate preventive measures to reduce the incidence of pancreatic fistula when the patient has a high V-PNAD.

Vessel trajectory data are currently the most important data source for vessel trajectory data mining research. However, vessel AIS data have a short sampling time interval and a large amount of data redundancy, which hampers the efficient utilization of AIS data. In order to effectively remove redundant information from AIS data and improve its usage efficiency, a compression algorithm for vessel trajectory data compression algorithm considering critical region identification (VATDC_CCRI) is proposed. The VATDC_CCRI algorithm identifies the critical regions of a vessel’s trajectory by analyzing the distribution of node variation rates. It employs the Douglas–Peucker (DP) algorithm to compress the data in these critical regions, reducing the distortion of the trajectory after compression. Additionally, the algorithm utilizes a sliding window approach to process the initial trajectory to improve the quality of the compressed vessel trajectories and retain as many spatiotemporal characteristics of the original trajectories as possible. It combines the feature nodes from the crucial regions in the vessel’s trajectory with the results obtained from the sliding window algorithm, effectively compressing the vessel’s trajectory. Experiments conducted on individual and multiple trajectories demonstrate that the VATDC_CCRI algorithm achieves higher compression rates and exhibits faster processing speeds compared to other classical vessel trajectory compression algorithms while preserving the shape of the vessel’s trajectory significantly.

The additions of alloying elements can significantly improve the mechanical properties of magnesium (Mg) alloys, mainly due to the fact that their additions change the critical shear stresses (CRSS) for dislocation slips. In this work, experimental and computational methods were used to explore the mechanisms responsible for the roles of Sm element addition in affecting the mechanical properties of Mg. The results showed that the addition of Sm obviously improves the microstructure and mechanical properties. It promotes the formation of twins and beneficially activated the non-basal slip at the initial stage of plastic deformation, resulting in a high ductility. The Visco-Plastic Self-Consistent (VPSC) and the two-beam diffraction results confirmed that the pyramidal slip and prismatic slip were activated during tensile testing. The quantitative analysis of slip traces verified that the volume of non-basal slips reached 35 % after Sm addition. The additions of Sm with solid solution increased the activities of pyramidal dislocation during deformation, which was beneficial to accommodate the c-axis strain, and finally improved the room temperature ductility of Mg. First-principle calculations demonstrate that the solute Sm atoms would reduce the stacking fault energy for basal and prismatic slips.

Ternary magnesium-based alloys with an aluminum content of 0.5 wt.% and a varying manganese content of x = 1, 2, and 3 wt.% (Mg-xMn-0.5Al) were prepared and characterized. The study focused on the effect of Mn addition on the formation of ultrafine grains (UFGs, average grain size

Real-time accurate detection of three-dimensional (3D) objects is a fundamental necessity for self-driving vehicles. Most existing computer vision approaches are based on convolutional neural networks (CNNs). Although the CNN-based approaches can achieve high detection accuracy, their high energy consumption is a severe drawback. To resolve this problem, novel energy efficient approaches should be explored. Spiking neural network (SNN) is a promising candidate because it has orders-of-magnitude lower energy consumption than CNN. Unfortunately, the studying of SNN has been limited in small networks only. The application of SNN for large 3D object detection networks has remain largely open. In this paper, we integrate spiking convolutional neural network (SCNN) with temporal coding into the YOLOv2 architecture for real-time object detection. To take the advantage of spiking signals, we develop a novel data preprocessing layer that translates 3D point-cloud data into spike time data. We propose an analog circuit to implement the non-leaky integrate and fire neuron used in our SCNN, from which the energy consumption of each spike is estimated. Moreover, we present a method to calculate the network sparsity and the energy consumption of the overall network. Extensive experiments have been conducted based on the KITTI dataset, which show that the proposed network can reach competitive detection accuracy as existing approaches, yet with much lower average energy consumption. If implemented in dedicated hardware, our network could have a mean sparsity of 56.24% and extremely low total energy consumption of 0.247mJ only. Implemented in NVIDIA GTX 1080i GPU, we can achieve 35.7 fps frame rate, high enough for real-time object detection.

In the existing research on the intelligent navigation of ships, navigation route planning often regards light buoys as fixed obstructions. However, due to factors such as water ripples, the position of the buoys keeps periodically changing. If the buoys are set to a fixed range of avoidance areas in the process of ship navigation, it is easy to allow a collision between the ship and the light buoys. Therefore, based on historical motion trajectory data of the buoys, a SARIMA-based time-series prediction model is proposed to estimate the offset position of a given buoy in a specified time. Furthermore, the collision-free path planning approach is presented to dynamically recommend an accurate sailing path. The results of the simulation experiment show that this method can effectively deal with collisions of ships caused by the offset position of the light buoys during the navigation of the large and low-speed autonomous ships.

Mg–Al binary alloys in the concentration range from 0 to 4.0 wt.% Al have been prepared under conventional casting conditions. The as-cast Mg and Mg–Al alloys after solution treatment were processed via hot extrusion at 350 °C. The results show that Al has a positive influence on grain refinement and solution strengthening. The as-extruded Mg–Al alloys are fully recrystallized, and the tensile yield strength of the binary alloys is two times higher than that of pure Mg. Furthermore, the elongations of Mg–Al alloys are much higher than that of pure Mg. In addition, Mg and Mg–Al alloys were further studied by the viscoplastic self-consistent (VPSC) model to explore the activation and evolution of deformation modes. The simulation results match well with the experimental results.

The effect of Mn on the microstructure and mechanical properties of as-extruded Mg-0.5Sr alloy were discussed in this work. The results showed that high Mn alloying (2 wt.%) could significantly improve the mechanical properties of the alloys, namely, the tensile and compressive yield strength. The grain size of as-extruded Mg-0.5Sr alloys significantly was refined from 2.78 μm to 1.15 μm due to the pinning effect by fine α-Mn precipitates during the extrusion. Moreover, it also showed that the tensile yield strength and the compressive yield strength of Mg-0.5Sr-2Mn alloy were 32 and 40 percent age higher than those of Mg-0.5Sr alloy, respectively. Moreover, the strain hardening behaviors of the Mg-0.5Sr-2Mn alloy were discussed, which proved that a large number of small grains and texture have an important role in improving mechanical properties.

Hot rolling was carried out in this study to modify the microstructures of an extruded Mg–6Al–1Sn–0.3Mn alloy sheet and investigate its effects on mechanical properties. After hot rolling, the grains and second phase of the extruded alloy sheet were remarkably refined, and the c-axis of a few grains was parallel to the transverse direction. The strength improvement was mainly attributed to the grain and Mg17Al12 particle refinement due to the Hall–Petch effect and the Orowan mechanism. The random orientation of the fine grains resulted in improving ductility and anisotropy.