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Permutation flowshop design and optimization are crucial in industry as they have a direct impact on production scheduling and efficiency. The ultimate goal is to model the production system (PSM) based on revealing the fundamental principles of the production process, and to schedule or reschedule production release plans in real time without interrupting work-in-progress (WIP). Most existing PSMs are focused on static production processes which fail to describe the dynamic relationships between machines and buffers. Therefore, this paper establishes a PSM to characterize both the static and transient behaviors of automatic and manual machines in the permutation flowshop manufacturing system. Building upon the established PSM, based on Bernoulli's theory, discrete event model predictive control is proposed in this paper; its aim is to realize real-time optimization of production release plans without interfering with work-in-progress. According to the results of numerical examples, the discrete event model predictive control proposed in this paper is feasible and effective. The model established in this paper provides a theoretical basis for optimizing the effective operation of work-in-progress and replacement process systems. [ABSTRACT FROM AUTHOR]

Aeolian sand flow is identified as the main factor in the formation of sandstorms. However, conventional sand fixation methods cannot meet the current development requirements of environmental protection. In this paper, the method using Microbially Induced Calcite Precipitation (MICP) combined with basalt fiber reinforcement (BFR) was adopted to solidify the aeolian sand. Consolidated undrained triaxial shear tests were carried out to analyze the influence of fiber content, fiber length, confining pressure, and other factors on stress–strain characteristics, peak strength, brittleness index, and shear strength of aeolian sand. A shear strength model of aeolian sand solidification using MICP-BFR and considering the effect of fiber length and fiber content is established according to the test results. The results show that the peak strength of aeolian sand solidified by MICP-BFR is remarkably higher than that of aeolian sand solidified by MICP alone, and the peak strength rises with the increasing fiber length, fiber content, and confining pressure. The application of fiber can effectively reduce the brittleness index of aeolian sand solidified by MICP and improve the sample ductility. As fiber content and fiber length increase, the cohesion of solidified aeolian sand increases while the internal friction angle changes relatively little. In the limited range set by the test, the fiber length of 12 mm and the fiber content of 1.0% constitute the optimum reinforcement condition. The test results coincide with the model prediction results, indicating that the new model is fitting for predicting the shear strength of aeolian sand solidified by MICP-BFR. The research results provide an important reference value for guiding the practice of wind prevention and sand fixation in desert areas. [ABSTRACT FROM AUTHOR]

Siamese network-based trackers have developed rapidly in the field of visual object tracking recently. Many Siamese network-based trackers currently in use rely on result fusion to combine the classification result map and regression result map. However, these result maps are obtained from the multi-level feature map and are independent of each other. It is inappropriate and flawed to use result fusion. Additionally, classification module and regression module are independent of each other, which leads to feature misalignment. In this paper, we propose a feature-fusion approach that involves fusing similarity response maps using a novel scale attention mechanism and subsequently decoding the features. To reduce the feature misalignment and produce more precise tracking results, we suggest using Classification Supervised Regression Loss (CSRL), to train the model. Experiments conducted on three challenging benchmark datasets show that this method outperforms current models in terms of both performance and efficiency, running at 40 fps. [ABSTRACT FROM AUTHOR]

Torpedo anchors are a new type of anchoring system in deepwater that is much more economical than conventional anchoring methods. The dynamic penetration process is vitally important to the installation of torpedo anchors. Based on the spherical cavity expansion theory, the dynamic response characteristics of pressure-locked soils are analyzed using the Mohr-Coulomb criterion. The equations for the penetration of torpedo anchors with bullet-shaped heads are established considering rod friction. Subsequently, the analytical solutions for velocity, acceleration, and final penetration depth and the approximate analytical solution for penetration depth vs. time are obtained. The established penetration equation is solved using MATLAB software to obtain a semi-analytical solution, and the model tests on the penetration of a torpedo anchor with different initial velocities into saturated sand with different densities were conducted. A comparison of the test results shows that the analytical solution and the semi-analytical solution can well predict the model test results, indicating that the established analytical method can be used to analyze the penetration process of torpedo anchors. The research results can provide a guideline to the installation of torpedo anchors into the seabed in actual engineering. [ABSTRACT FROM AUTHOR]

This study investigates the effect of support structures on the properties of Inconel 718 (i.e., IN718) parts produced by the laser powder bed fusion (LPBF) additive manufacturing process. Specifically, the effects of support structure shape (i.e., pin-type, angled-type, cone-type) and geometry (i.e., support wall thickness, and gap) on their composition, hardness, microstructure, and material/time consumption are investigated and compared to the conventionally fabricated Inconel 718. From the microstructural analysis, the deepest melt pools appeared to be formed in the sample fabricated on top of the pin-type support structure having a relatively low wall thickness. The XRD results conveyed that a proper selection of geometrical variables for designing support structure results in elevated levels of the strengthening phases of IN718. The sample fabricated on top of the pin-type support structure showed the highest Vickers hardness value of 460.5 HV, which was even higher than what was reported for the heat-treated wrought Inconel 718 (355–385 HV). Moreover, for the thinner support wall thickness, an improvement in the hardness value of the fabricated samples was observed. This study urges a reconsideration of the common approach of selecting supports for additive manufacturing of samples when a higher quality of the as-fabricated parts is desired. [ABSTRACT FROM AUTHOR]

Additive manufacturing technologies have been adopted in a wide range of industries such as automotive, aerospace, and consumer products. Currently, additive manufacturing is mainly used for small-scale, low volume productions due to its limitations such as high unit cost. To enhance the scalability of additive manufacturing, it is critical to evaluate and preferably reduce the cost of adopting additive manufacturing for production. The current literature on additive manufacturing cost mainly adopts empirical approaches and does not sufficiently explore the cost-saving potentials enabled by leveraging different process planning algorithms. In this article, a mathematical cost model is established to quantify the different cost components in the direct metal laser sintering process, and it is applicable for evaluating the cost performance when adopting dynamic process planning with different layer-wise process parameters. The case study results indicate that 12.73% of the total production cost could be potentially reduced when applying the proposed dynamic process planning algorithm based on the complexity level of geometries. In addition, the sensitivity analysis results suggest that the raw material price and the overhead cost are the two key cost drivers in the current additive manufacturing market. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the efficacy and safety of Houttuynia eye drops (a Chinese traditional medicine) atomization treatment in meibomian gland dysfunction (MGD)-related dry eye disease (DED) patients. Methods: A total of 240 eligible patients diagnosed with MGD-related DED were assigned either Houttuynia eye drops or placebo for atomization once daily for four weeks in a multi-center, randomized, double-blind, placebo-controlled clinical study. Primary outcome evaluations used included eye symptom score (using the Chinese Dry Eye Questionnaire), meibum quality, and tear break-up time (TBUT), while safety evaluations included adverse events (AEs), visual acuity, and intraocular pressure monitoring. Indicators were measured at baseline as well as one week, two weeks, and four weeks after treatment. Results: Primary outcome measures of the Houttuynia group were improved compared with their placebo counterparts following four-week treatment. Eye symptom scores were significantly reduced relative to the baseline in the Houttuynia group (mean ± standard error of the mean, 9.00 ± 0.61) compared with the placebo group (6.29 ± 0.55; p = 0.0018). Reduction in meibum quality score in the Houttuynia group (0.91 ± 0.10) was also significantly higher compared with the placebo group (0.57 ± 0.10; p = 0.0091), while TBUT in the treatment group (6.30 ± 0.22) was also longer than in the latter (5.60 ± 0.24; p = 0.0192). No medication-related adverse events were observed. Conclusions: Atomization treatment with Houttuynia eye drops is both clinically and statistically effective for the treatment of mild to moderate MGD-related DED patients. This approach is generally safe and was tolerated well by patients. [ABSTRACT FROM AUTHOR]