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Migraine is related to brain energy deficiency. Niacin is a required coenzyme in mitochondrial energy metabolism. However, the relationship between dietary niacin and migraines remains uncertain. We aimed to evaluate the relationship between dietary niacin and migraine. This study used cross-sectional data from people over 20 years old who took part in the National Health and Nutrition Examination Survey between 1999 and 2004, collecting details on their severe headaches or migraines, dietary niacin intake, and several other essential variables. There were 10,246 participants, with 20.1% (2064/10,246) who experienced migraines. Compared with individuals with lower niacin consumption Q1 (≤12.3 mg/day), the adjusted OR values for dietary niacin intake and migraine in Q2 (12.4–18.3 mg/day), Q3 (18.4–26.2 mg/day), and Q4 (≥26.3 mg/day) were 0.83 (95% CI: 0.72–0.97, p = 0.019), 0.74 (95% CI: 0.63–0.87, p < 0.001), and 0.72 (95% CI: 0.58–0.88, p = 0.001), respectively. The association between dietary niacin intake and migraine exhibited an L-shaped curve (nonlinear, p = 0.011). The OR of developing migraine was 0.975 (95% CI: 0.956–0.994, p = 0.011) in participants with niacin intake < 21.0 mg/day. The link between dietary niacin intake and migraine in US adults is L-shaped, with an inflection point of roughly 21.0 mg/day.

In the process of reaching consensus, it is necessary to coordinate different views to form a general group opinion. However, there are many uncertain factors in this process, which has brought different degrees of influence in group decision-making. Besides, these uncertain elements bring the risk of loss to the whole process of consensus building. Currently available models not account for these two aspects. To deal with these issues, three different modeling methods for constructing the two-stage mean-risk stochastic minimum cost consensus models (MCCMs) with asymmetric adjustment cost are investigated. Due to the complexity of the resulting models, the L-shaped algorithm is applied to achieve an optimal solution. In addition, a numerical example of a peer-to-peer online lending platform demonstrated the utility of the proposed modeling approach. To verify the result obtained by the L-shaped algorithm, it is compared with the CPLEX solver. Moreover, the comparison results show the accuracy and efficiency of the given method. Sensitivity analyses are undertaken to assess the impact of risk on results. And in the presence of asymmetric cost, the comparisons between the new proposed risk-averse MCCMs and the two-stage stochastic MCCMs and robust consensus models are also given.

By adopting the absolute nodal coordinate formulation, a novel and general nonlinear theoretical model, which can be applied to solve the dynamics of combined straight-curved fluid-conveying pipes with arbitrary initially configurations and any boundary conditions, is developed in the current study. Based on this established model, the nonlinear behaviors of a cantilevered L-shaped pipe conveying fluid with and without base excitations are systematically investigated. Before starting the research, the developed theoretical model is verified by performing three validation examples. Then, with the aid of this model, the static deformations, linear stability and nonlinear self-excited vibrations of the L-shaped pipe without the base excitation are determined. It is found that the cantilevered L-shaped pipe suffers from the static deformations when the flow velocity is subcritical, and will undergo the limit-cycle motions as the flow velocity exceeds the critical value. Subsequently, the nonlinear forced vibrations of the pipe with a base excitation are explored. It is indicated that period-n, quasi-periodic and chaotic responses can be detected for the L-shaped pipe, which has a strong relationship with the flow velocity, excitation amplitude and frequency.

Objective To compare the clinical outcomes of a modified arthroscopic triple‐row (TR) repair technique with the suture bridge (SB) repair technique in treating L‐shaped delaminated rotator cuff tears. Various surgical techniques for L‐shaped delaminated rotator cuff tears have been reported, many of which aid in increasing the contact area and pressure of the rotator cuff. However, there is still debate over which technique yields superior results. Methods From January 2017 to March 2020, 61 cases of L‐shaped delaminated rotator cuff tears were included in this study. Of these, 34 cases underwent the modified arthroscopic triple‐row repair technique, while 27 cases were addressed with the suture bridge repair technique. Functional assessment was conducted using the American Shoulder and Elbow Surgeons (ASES) score, the University of California Los Angeles (UCLA) shoulder score, the Constant score (CS), and the visual analogue scale (VAS) score. Magnetic Resonance Imaging (MRI) assessments for rotator cuff healing were performed at the 24‐month postoperative mark. Statistical evaluations were conducted using SPSS for Windows (Version 25.0, IBM, Armonk, NY, USA), employing the Wilcoxon signed‐rank test to compare preoperative and postoperative data and ROM differences, and the Mann–Whitney U test for statistical differences in clinical outcome scores between the two groups. A p‐value of less than 0.05 was considered statistically significant. Results Comparative analysis of the preoperative and final follow‐up scores revealed a substantial enhancement in shoulder function, as indicated by the ASES, UCLA, CS, and VAS scores, with statistical significance (p < 0.001). At both the preoperative stage and final follow‐up, no notable differences were observed in ASES, UCLA, CS, and VAS scores between the two groups. However, the TR repair group exhibited lower VAS scores than the SB group at 1 and 3 months postoperatively. Active range of motion (ROM) showed significant improvement in both groups. No significant differences in ROM were noted between the two groups either before the surgery or at the final follow‐up. Conclusion The study demonstrates that both the modified arthroscopic TR and SB techniques for L‐shaped delaminated cuff tears yield satisfactory outcomes, with no significant differences in overall clinical performance. Notably, early postoperative pain management appears more effective with the modified TR technique, suggesting its potential for enhanced early recovery experiences. This technique's design, promoting securer fixation and optimal contact conditions, is implied to facilitate superior long‐term healing, warranting further investigation into its long‐term benefits. The study compared the modified arthroscopic triple‐row repair technique and suture bridge repair technique for L‐shaped delaminated rotator cuff tears, finding both methods yielded satisfactory clinical outcomes with no significant difference; however, the modified triple‐row technique offered better pain relief in the early postoperative period and potentially superior long‐term healing benefits. The schematic illustration represents the modified arthroscopic triple‐row repair technique.

This study proposes the use of artificial neural network (ANN) and semi-empirical models for predicting mean drop size and drop size distribution in an L-shaped pulsed packed extraction column under non-mass-transfer conditions, employing toluene-water (T/W) and n-butyl acetate-water (B/W) systems. The ANN model was trained using the Levenberg–Marquardt algorithm and demonstrated excellent predictive performance, achieving R 2 values of 0.981 and 0.986 for drop size distribution and mean drop size, respectively. Furthermore, the ANN model demonstrated superior accuracy in predicting mean drop size, with an average absolute relative error (AARE) of only 2%, significantly outperforming the semi-empirical model’s AARE of 6%. Moreover, the ANN model significantly reduced the maximum prediction error in drop size distribution, particularly under conditions where the semi-empirical model showed poor performance. The findings underscore the critical role of pulsation intensity and interfacial tension in determining drop size. Notably, higher pulsation intensities were found to significantly reduce the influence of interfacial tension. Finally, new semi-empirical correlations derived from the experimental data were established to predict both mean drop size and drop size distribution.

This paper addresses the problem of the two-dimensional direction-of-arrival (2D DOA) estimation of low-elevation or non-low-elevation targets using L-shaped uniform and sparse arrays by analyzing the signal models’ features and their mapping to 2D DOA. This paper proposes a 2D DOA estimation algorithm based on the dilated convolutional network model, which consists of two components: a dilated convolutional autoencoder and a dilated convolutional neural network. If there are targets at low elevation, the dilated convolutional autoencoder suppresses the multipath signal and outputs a new signal covariance matrix as the input of the dilated convolutional neural network to directly perform 2D DOA estimation in the absence of a low-elevation target. The algorithm employs 3D convolution to fully retain and extract features. The simulation experiments and the analysis of their results revealed that for both L-shaped uniform and L-shaped sparse arrays, the dilated convolutional autoencoder could effectively suppress the multipath signals without affecting the direct wave and non-low-elevation targets, whereas the dilated convolutional neural network could effectively achieve 2D DOA estimation with a matching rate and an effective ratio of pitch and azimuth angles close to 100% without the need for additional parameter matching. Under the condition of a low signal-to-noise ratio, the estimation accuracy of the proposed algorithm was significantly higher than that of the traditional DOA estimation.

A feasible alternative to the production of fossil fuels is the production of biofuels. In order to minimize the costs of producing biofuels, we developed a stochastic programming formulation that optimizes the inbound delivery of biomass. The proposed model captures the variability in the moisture and ash content in the biomass, which define its quality and affect the cost of biofuel. We propose a novel hub-and-spoke network to take advantage of the economies of scale in transportation and to minimize the effect of poor quality. The first-stage variables are the potential locations of depots and biorefineries, and the necessary unit trains to transport the biomass. The second-stage variables are the flow of biomass between the network nodes and the third-party bioethanol supply. A case study from Texas is presented. The numerical results show that the biomass quality changes the selected depot/biorefinery locations and conversion technology in the optimal network design. The cost due to poor biomass quality accounts for approximately 8.31% of the investment and operational cost. Our proposed L-shaped with connectivity constraints approach outperforms the benchmark L-shaped method in terms of solution quality and computational effort by 0.6% and 91.63% on average, respectively.

The recognition of data matrix (DM) codes plays a crucial role in industrial production. Significant progress has been made with existing methods. However, for low-quality images with protrusions and interruptions on the L-shaped solid edge (finder pattern) and the dashed edge (timing pattern) of DM codes in industrial production environments, the recognition accuracy rate of existing methods sharply declines due to a lack of consideration for these interference issues. Therefore, ensuring recognition accuracy in the presence of these interference issues is a highly challenging task. To address such interference issues, unlike most existing methods focused on locating the L-shaped solid edge for DM code recognition, we in this paper propose a novel DM code recognition method based on locating the L-shaped dashed edge by incorporating the prior information of the center of the DM code. Specifically, we first use a deep learning-based object detection method to obtain the center of the DM code. Next, to enhance the accuracy of L-shaped dashed edge localization, we design a two-level screening strategy that combines the general constraints and central constraints. The central constraints fully exploit the prior information of the center of the DM code. Finally, we employ libdmtx to decode the content from the precise position image of the DM code. The image is generated by using the L-shaped dashed edge. Experimental results on various types of DM code datasets demonstrate that the proposed method outperforms the compared methods in terms of recognition accuracy rate and time consumption, thus holding significant practical value in an industrial production environment.

This study numerically evaluates fluid flow and natural convection heat transfer of a porous square cylinder in an L-shaped enclosure using the Lattice Boltzmann method. Three layouts along vertical and horizontal centrelines are explored, investigating the effects of Rayleigh number (Ra) (10 3  ≤ Ra ≤ 10 6 ), Darcy number (Da) (10 −6  ≤ Da ≤ 10 −2 ), and cylinder size. Results show that increasing Rayleigh numbers enhances heat transfer, with higher Mean Nusselt number (Nu Mean ) values observed. Doubling the cylinder’s width at Da = 10 −6 increases Nu Mean by 46.5%, and tripling the width results in a 118% enhancement. Higher Rayleigh values enhance buoyant forces’ intensity, improving heat transfer; for example, at Ra = 10 5 and Da = 10 –2 , there is a 42% increase in Nu mean for a cylinder with a 0.6 L side length compared to Ra = 10 3 . Optimal cylinder orientation significantly maximizes convective heat transfer, especially at high Rayleigh and Darcy numbers. This study provides valuable insight for optimizing the orientation of electronic blocks in compact L-shaped enclosures for better thermal management.

A novel passive asymmetric quasi-zero stiffness vibration isolator (AQZS-VI) comprising two linear springs acting in parallel with one negative stiffness element (NSE) is proposed, of which the NSE is mainly constructed by the combination of cantilever plate spring and L-shaped lever (CPS-LSL). The static model of the isolator is deduced considering the geometrical nonlinearity of the NSE and the bending deformation of plate spring. The nonlinear stiffness properties of the CPS-LSL and the AQZS-VI, as well as the nonlinear damping properties of the AQZS-VI, are discussed. The absolute displacement transmissibility of the AQZS-VI under base displacement excitation is obtained using harmonic balance method, and the effects of different excitation amplitudes and damping factors on the vibration isolation performance are analyzed. Better than other quasi-zero stiffness vibration isolators (QZS-VI) whose NSEs do not provide supporting force at zero stiffness point, the NSE of the AQZS-VI provides more supporting force than the parallel connected linear springs, which is very beneficial for improving the bearing capacity of the isolator. Compared with a typical symmetric QZS-VI with same damping property, the AQZS-VI has longer stroke with low stiffness and lower peak value of displacement transmissibility. The prototype experiments indicate that the AQZS-VI outperforms the linear counterpart with much smaller starting frequency of vibration isolation and lower displacement transmissibility. The proposed AQZS-VI has great potential for applying in various engineering practices with superior vibration isolation performance.