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S4 Table -
No full textS4A Table. Model for End Stage Liver Disease (MELD) Score calculation. S4B Table. Definition of Dialysis for calculation in MELD score. (DOCX)</p
Tugboat optimum operating program.
No full textWith the continuous prosperity of maritime transportation on a global scale and the resulting escalation in port trade volume, tugboats assume a pivotal role as essential auxiliary tools influencing the ingress and egress of vessels into and out of ports. As a result, the optimization of port tug scheduling becomes of paramount importance, as it contributes to the heightened efficiency of ship movements, cost savings in port operations, and the promotion of sustainable development within the realm of maritime transportation. However, a majority of current tugboat scheduling models tend to focus solely on the maximum operational time. Alternatively, the formulated objective functions often deviate from real-world scenarios. Furthermore, prevailing scheduling methods exhibit shortcomings, including inadequate solution accuracy and incompatibility with integer programming. Consequently, this paper introduces a novel multi-objective tugboat scheduling model to align more effectively with practical considerations. We propose a novel optimization algorithm, the Improved Grey Wolf Optimization (IGWO), for solving the tugboat scheduling model. The algorithm enhances convergence performance by optimizing convergence parameters and individual updates, making it particularly suited for solving integer programming problems. The experimental session designs several scale instances according to the reality of the port, carries out simulation experiments comparing several groups of intelligent algorithms, verifies the effectiveness of IGWO, and verifies it in the comprehensive port area of Huanghua Port to get the optimal scheduling scheme of this port area, and finally gives management suggestions to reduce the cost of tugboat operation through sensitivity analysis.</div
Results of orthogonal experiments.
No full textWith the continuous prosperity of maritime transportation on a global scale and the resulting escalation in port trade volume, tugboats assume a pivotal role as essential auxiliary tools influencing the ingress and egress of vessels into and out of ports. As a result, the optimization of port tug scheduling becomes of paramount importance, as it contributes to the heightened efficiency of ship movements, cost savings in port operations, and the promotion of sustainable development within the realm of maritime transportation. However, a majority of current tugboat scheduling models tend to focus solely on the maximum operational time. Alternatively, the formulated objective functions often deviate from real-world scenarios. Furthermore, prevailing scheduling methods exhibit shortcomings, including inadequate solution accuracy and incompatibility with integer programming. Consequently, this paper introduces a novel multi-objective tugboat scheduling model to align more effectively with practical considerations. We propose a novel optimization algorithm, the Improved Grey Wolf Optimization (IGWO), for solving the tugboat scheduling model. The algorithm enhances convergence performance by optimizing convergence parameters and individual updates, making it particularly suited for solving integer programming problems. The experimental session designs several scale instances according to the reality of the port, carries out simulation experiments comparing several groups of intelligent algorithms, verifies the effectiveness of IGWO, and verifies it in the comprehensive port area of Huanghua Port to get the optimal scheduling scheme of this port area, and finally gives management suggestions to reduce the cost of tugboat operation through sensitivity analysis.</div
Cell proliferation is stimulated by 17b-estradiol and an ERa agonist which is negated by tamoxifen: Incorporation of BrdU by breast cancer cells MCF7, T47D and BT483 as a percentage of the vehicle control (+/- SEM of 3 separate assays with 8 experimental replicates).
No full textCON = vehicle control (0.1% DMSO); E2 = 17b-estradiol (10nM); TAM = tamoxifen (2μM); PPT (100nM), ERB = ERB-041 (100nM) Cells were incubated for 48 hours. ANOVA (Dunnett’s multiple comparison) statistical significance is displayed on the graph above the bars (* denotes significance vs CON. # denotes significance vs E2.). *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001, ns non-significant.</p
Table showing suggested maximum experimental concentrations based upon the cytotoxicity observed in the WST-1 assays.
No full text2 log-fold dilutions from the maximum tolerated concentration were also tested in subsequent experiments. (DOCX)</p
S1 Data -
No full textIntroductionHamstring strain injuries (HSI) and re-injuries are endemic in high-speed running sports. The biceps femoris long head (BFlh) is the most frequently injured muscle among the hamstrings. Structural parameters of the hamstring muscle are stated to be susceptible to strain injuries at this location. This retrospective study targeted comparing the BFlh’s structural parameters between previously injured and uninjured athletes.MethodsNineteen male athletes with previous BFlh strain injury history and nineteen athletes without former lower extremity injury history were included in this study. Fascicle length, mid-muscle belly and distal musculotendinous (MTJ) passive stiffnesses of the biceps femoris long head (BFlh) were examined via b-mode panoramic ultrasound scanning and ultrasound-based shear-wave elastography. Parameter comparisons of both legs within and between athletes with and without injury history were performed.ResultsComparison of the BFlh fascicle length between the injured leg of the injured group and the legs of the controls revealed a trend to shorter fascicle lengths in the injured leg (p = 0.067, d = -0.62). However, the mid-muscle belly passive stiffness of the BFlh was significantly higher in the injured legs (p = 0.009, d = 0.7) compared with the controls. Additionally, the distal MTJ stiffness was much higher in the previously injured legs compared with controls (p d = 1.6).ConclusionsOutcomes support the importance of BFlh properties related to stiffness, and fascicle length for injury susceptibility in athletes. Future prospective studies should determine whether the higher stiffness in the injured athletes is a cause or consequence of the HSI. Physical therapy and rehabilitation programmes after HSI should focus on BFlh muscle properties i.e., elasticity and fascicle length for reducing re-injury and increasing sports performance.</div
Factors associated with treatment follow-up during the COVID-19 pandemic.
No full textFactors associated with treatment follow-up during the COVID-19 pandemic.</p
Characteristics of the participants in the E24 study (N = 901).
No full textCharacteristics of the participants in the E24 study (N = 901).</p
Risk factors associated with the severity of influenza A (H1N1) in adults, Brazil.
No full textRisk factors associated with the severity of influenza A (H1N1) in adults, Brazil.</p
Means ± standard deviations (95% confidence intervals) for propulsive kinetics and kinematics, phase duration, peak velocity decline, peak velocity maintenance and RPE for all 18 repetitions averaged within each protocol during the hang pull at 140% 1RM.
No full textMeans ± standard deviations (95% confidence intervals) for propulsive kinetics and kinematics, phase duration, peak velocity decline, peak velocity maintenance and RPE for all 18 repetitions averaged within each protocol during the hang pull at 140% 1RM.</p