[go: up one dir, main page]

 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (169)

Search Parameters:
Keywords = method of L-moments

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
15 pages, 311 KiB  
Article
Analysis of Hydration Habits Before and During a Specific Training Session in Male Padel Athletes Aged over 65: Physiological and Psychological Implications
by Ana Júlia Lopes, Maria João Campos, Fátima Rosado, Luís Rama, Alex Silva Ribeiro, Diogo Martinho, Ana Teixeira and Alain Massart
Nutrients 2024, 16(20), 3513; https://doi.org/10.3390/nu16203513 - 16 Oct 2024
Viewed by 352
Abstract
(1) Background: Since older adults are more susceptible to dehydration and there is a lack of information on older athletes, this study observed a group of 12 male padel players in this age group (70.42 ± 3.50 years) to characterize their hydration habits, [...] Read more.
(1) Background: Since older adults are more susceptible to dehydration and there is a lack of information on older athletes, this study observed a group of 12 male padel players in this age group (70.42 ± 3.50 years) to characterize their hydration habits, physiological demands, and psychological responses before and during a 90 min padel training (PT). (2) Methods: After approval from the Ethics Committee (CE/FCDEF-UC/00022023) and the provision of signed informed consent, participants’ body mass, height, waist and hip circumferences, body mass index, waist-to-hip ratio, and waist-to-height ratio were measured. Habitual fluid intake was monitored by diary from the evening until before the PT; the subjects completed a Profile of Mood States questionnaire (POMS) and a satiety scale (SLIM). To assess hydration levels at different moments, we used a portable osmometer and an eight-point urine color chart and weighed the participants immediately before and after the PT. During the PT, heart rate (HR) and hydration were monitored. After the PT, subjects completed another POMS and SLIM. (3) Results: Subjects trained at 73.2 ± 12.3% of their maximum HR, with brief peaks at the anaerobic threshold or higher (130.00 ± 18.78 bpm). The mean urine osmolality indicated normal hydration or minimal dehydration. However, the urine color values indicated dehydration after the training. Subjects drank 438 mL of liquids at night, 333 mL before PT, and 900 mL during the PT, with a good repartition of the liquids. POMS and SLIM were not affected by the training. (4) Conclusions: Older male padel athletes achieved challenging yet safe training, staying within healthy intensity zones; their hydration patterns nearly met the recommendations for exercise and should be slightly increased. Full article
18 pages, 16437 KiB  
Article
CFD Simulation of Mixing Forest Biomass to Obtain Cellulose
by Adolfo Angel Casarez-Duran, Juan Carlos Paredes-Rojas, Christopher René Torres-San Miguel, Sergio Rodrigo Méndez-García, Fernando Eli Ortiz-Hernández and Guillermo Manuel Urriolagoitia Calderón
Processes 2024, 12(10), 2250; https://doi.org/10.3390/pr12102250 - 15 Oct 2024
Viewed by 226
Abstract
Obtaining cellulose from forest residues develops sustainable processes in the biotechnology industry, especially in producing biopolymers, which could replace or add petroleum-derived polymers. This research seeks to optimize the ideal conditions of the mixing process to maximize the efficiency in obtaining cellulose through [...] Read more.
Obtaining cellulose from forest residues develops sustainable processes in the biotechnology industry, especially in producing biopolymers, which could replace or add petroleum-derived polymers. This research seeks to optimize the ideal conditions of the mixing process to maximize the efficiency in obtaining cellulose through a process consisting of two treatment media for pine sawdust, specifically evaluating the impact of three types of impellers (propeller, flat blades, and 45° inclined flat blades) at speeds of (150, 250 and 350 rpm). DIN 28131 was used for the design of stirred tanks. Simulations were carried out with a volume of 50 L. CFD and FSI simulations of the agitation behavior of forest biomass in a stirred tank reactor were performed. The ALE method was applied, and the models were solved using the LS-DYNA computer program. The results indicate that agitation with propellers and flat blades inclined at 150 and 250 rpm was the most efficient, minimizing cell damage and optimizing energy consumption. The impeller with flat blades inclined at 45° proved to be the best option for cellulose extraction. The novelty of this research is that not only the flow fields and the agitation behavior were found, but also the stresses in the impellers were found, and the force, moment, and power required by the motor in each simulation were revealed at a different speed. The power curves shown help to understand how energy consumption varies under different conditions. Full article
Show Figures

Figure 1

Figure 1
<p>Methodology.</p>
Full article ">Figure 2
<p>Block diagram of each treatment.</p>
Full article ">Figure 3
<p>Three-dimensional modeling: (<b>a</b>) modeling with the propeller impeller; (<b>b</b>) modeling with the flat impeller; (<b>c</b>) modeling with the inclined flat-blade impeller.</p>
Full article ">Figure 4
<p>Boundary conditions of the impellers: (<b>a</b>) propeller; (<b>b</b>) flat blade; (<b>c</b>) inclined flat blade.</p>
Full article ">Figure 5
<p>Mix—biomass–alcohol: (<b>a</b>) power-vs.-RPM graph; (<b>b</b>) speed-stirring-vs.-RPM graph.</p>
Full article ">Figure 6
<p>Mix—biomass–sodium chlorite solution: (<b>a</b>) power-vs.-RPM graph; (<b>b</b>) speed-stirring-vs.- RPM graph.</p>
Full article ">
23 pages, 7892 KiB  
Article
Numerical Study on the Lateral Load Response of Offshore Monopile Foundations in Clay: Effect of Slenderness Ratio
by Ali Khezri, Hongbae Park and Daeyong Lee
Appl. Sci. 2024, 14(18), 8366; https://doi.org/10.3390/app14188366 - 17 Sep 2024
Viewed by 662
Abstract
To meet growing energy demands, offshore wind turbines (OWTs) with higher energy outputs are being developed, presenting increased challenges for their foundation design. Over the past decade, extensive research on the design optimization of OWT support structures has significantly reduced the anticipated costs [...] Read more.
To meet growing energy demands, offshore wind turbines (OWTs) with higher energy outputs are being developed, presenting increased challenges for their foundation design. Over the past decade, extensive research on the design optimization of OWT support structures has significantly reduced the anticipated costs of offshore wind farm development. Various design methods have been developed and applied in practice, each with its own advantages and limitations. In this study, 3D finite element (FE) modeling, validated against the measured response of a large-scale test monopile, is used to investigate the lateral load response of monopiles with different geometries and slenderness ratios in smaall and large displacements. The results are compared to the standard p–y method, and specific behavioral and design aspects of large-diameter monopiles, such as the moment contribution ratio from different resisting components and the minimum embedment length criteria, are evaluated and discussed. The results showed that the maximum and minimum differences between the 3D FE modeling and one-dimensional (1D) DNV p–y method are 41% and 11% for large displacements, and 32.5% and 13.3% for small displacements, respectively. As the slenderness ratio increases, the discrepancy between the finite element (FE) modeling results and the 1D DNV p–y method decreases, with an average difference of about 13% across all monopile diameters at an L/D ratio of 10, in both small and large displacements, indicating the reasonable accuracy of the 1D method for slenderness ratios of 10 and above. Among the three minimum embedment length criteria examined, the DNV recommended and vertical-tangent criteria offered shorter embedment lengths. The primary resisting moment across all slenderness ratios comes from the distributed lateral load along the monopile shaft (MCRpy), which increases as the L/D ratio increases. Full article
(This article belongs to the Section Civil Engineering)
Show Figures

Figure 1

Figure 1
<p>Schematics of an OWT support structure, loads acting on it, and resisting components in the foundation system.</p>
Full article ">Figure 2
<p>Typical mesh configuration used for the 3D finite element modeling of monopile.</p>
Full article ">Figure 3
<p>Summary of initial conditions adopted for Cowden site: (<b>a</b>) small-strain shear modulus (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) undrained shear strength in compression (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> </mrow> <mrow> <mi>u</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>c</b>) lateral earth pressure coefficient in terms of effective stress (<math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>K</mi> </mrow> <mrow> <mn>0</mn> </mrow> <mrow> <mo>′</mo> </mrow> </msubsup> </mrow> </semantics></math>); and (<b>d</b>) pore water pressure (U) (data from Zdravković et al. 2020a,b) [<a href="#B27-applsci-14-08366" class="html-bibr">27</a>,<a href="#B42-applsci-14-08366" class="html-bibr">42</a>].</p>
Full article ">Figure 4
<p>Comparison between the measured and 3D FEM predicted response of CL2 test (PISA field test data from [<a href="#B42-applsci-14-08366" class="html-bibr">42</a>], and PISA FEM data fro [<a href="#B27-applsci-14-08366" class="html-bibr">27</a>]) [<a href="#B27-applsci-14-08366" class="html-bibr">27</a>,<a href="#B42-applsci-14-08366" class="html-bibr">42</a>].</p>
Full article ">Figure 5
<p>Annular gaps formed around the pile following cyclic loading [<a href="#B46-applsci-14-08366" class="html-bibr">46</a>].</p>
Full article ">Figure 6
<p>Simulated stress–strain curve in undrained 3-axial compression test for a soil element at a depth of −35 m.</p>
Full article ">Figure 7
<p>Profile of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">ε</mi> </mrow> <mrow> <mn>50</mn> </mrow> </msub> </mrow> </semantics></math> with depth.</p>
Full article ">Figure 8
<p>Comparison between the 1D DNV and FE model’s mudline-load–displacement response of the D8-LD4 at (<b>a</b>) large displacements and (<b>b</b>) small displacements.</p>
Full article ">Figure 9
<p>Mudline-load–displacement response of the D8 and L/D of 4, 6, 8, and 10 based on (<b>a</b>,<b>b</b>) FE model and (<b>c</b>,<b>d</b>) 1D DNV model in large and small displacements.</p>
Full article ">Figure 9 Cont.
<p>Mudline-load–displacement response of the D8 and L/D of 4, 6, 8, and 10 based on (<b>a</b>,<b>b</b>) FE model and (<b>c</b>,<b>d</b>) 1D DNV model in large and small displacements.</p>
Full article ">Figure 10
<p>Lateral load vs. L/D ratio at (<b>a</b>) 10 and (<b>b</b>) 1 percent of the monopile diameter based on the FE and 1D DNV results.</p>
Full article ">Figure 11
<p>The difference between the results of the FE model and 1D DNV method in (<b>a</b>) large and (<b>b</b>) small displacements.</p>
Full article ">Figure 12
<p>Deflection profile for the 8 m monopile in L/D ratios of 4, 6, 8, and 10 for the 5 MN load exerted at h = 40: (<b>a</b>) FE results and (<b>b</b>) 1D DNV p–y method results.</p>
Full article ">Figure 13
<p>Pile head displacement with increasing length for the 8 m monopile based on the results of FEM and 1D DNV p–y method.</p>
Full article ">Figure 14
<p>Comparison between the FE, 1D DNV p–y, and FE p–y curves for the mudline-load–displacement response of the D8 monopile at L/D ratios of (<b>a</b>,<b>b</b>) 4, (<b>c</b>,<b>d</b>) 6, (<b>e</b>,<b>f</b>) 8, and (<b>g</b>,<b>h</b>) 10.</p>
Full article ">Figure 14 Cont.
<p>Comparison between the FE, 1D DNV p–y, and FE p–y curves for the mudline-load–displacement response of the D8 monopile at L/D ratios of (<b>a</b>,<b>b</b>) 4, (<b>c</b>,<b>d</b>) 6, (<b>e</b>,<b>f</b>) 8, and (<b>g</b>,<b>h</b>) 10.</p>
Full article ">Figure 15
<p>Moment contribution ratio diagrams for the 8 m monopile with L/D ratios of (<b>a</b>) 4, (<b>b</b>) 6, (<b>c</b>) 8, and (<b>d</b>) 10.</p>
Full article ">
20 pages, 2872 KiB  
Article
Use of Eltrombopag to Improve Thrombocytopenia and Tranfusion Requirement in Anti-CD19 CAR-T Cell-Treated Patients
by Maria-Eva Mingot-Castellano, Juan Luis Reguera-Ortega, Denis Zafra Torres, Rafael Hernani, Oriana Lopez-Godino, Manuel Guerreiro, Blanca Herrero, Lucia López-Corral, Alejandro Luna, Lesli Gonzalez-Pinedo, Anabelle Chinea-Rodriguez, Ana Africa-Martín, Rebeca Bailen, Nuria Martinez-Cibrian, Pascual Balsalobre, Silvia Filaferro, Anna Alonso-Saladrigues, Pere Barba, Antonio Perez-Martinez, María Calbacho, Jose Antonio Perez-Simón, Jose Maria Sánchez-Pina and on behalf of the Spanish Group of Hematopoietic Transplant and Cell Therapy (GETH-TC)add Show full author list remove Hide full author list
J. Clin. Med. 2024, 13(17), 5117; https://doi.org/10.3390/jcm13175117 - 28 Aug 2024
Viewed by 1297
Abstract
Background/Objectives: Immune effector cell-associated hematotoxicity (ICAHT) is a frequent adverse event after chimeric antigen receptor (CAR)-T cell therapy. Grade ≥ 3 thrombocytopenia occurs in around one-third of patients, and many of them become platelet transfusion-dependent. Eltrombopag is a thrombopoietin receptor agonist (TPO-RA) able [...] Read more.
Background/Objectives: Immune effector cell-associated hematotoxicity (ICAHT) is a frequent adverse event after chimeric antigen receptor (CAR)-T cell therapy. Grade ≥ 3 thrombocytopenia occurs in around one-third of patients, and many of them become platelet transfusion-dependent. Eltrombopag is a thrombopoietin receptor agonist (TPO-RA) able to accelerate megakaryopoiesis, which has been used successfully in patients with bone marrow failure and immune thrombocytopenia (ITP). Its role in managing thrombocytopenia and other cytopenias in CAR-T cell-treated patients has been scarcely addressed. Our aim was to report the safety and efficacy of this approach in patients included in the Spanish Group for Hematopoietic Transplantation and Cellular Therapy (GETH-TC) registry. Methods: This is a retrospective, multicenter, observational study. Patients who developed platelet transfusion dependence subsequently to CAR-T cells and received eltrombopag to improve platelet counts were recruited in 10 Spanish hospitals. Results: Thirty-eight patients were enrolled and followed up for a median (interquartile range [IQR]) of 175 (99, 489) days since CAR-T cell infusion. At the moment eltrombopag was indicated, 18 patients had thrombocytopenia and another severe cytopenia, while 8 patients had severe pancytopenia. After 32 (14, 38) days on eltrombopag, 29 (76.3%) patients recovered platelet transfusion independence. The number of platelet units transfused correlated with the time needed to restore platelet counts higher than 20 × 109/L (Rho = 0.639, p < 0.001). Non-responders to eltrombopag required more platelet units (58 [29, 69] vs. 12 [6, 26] in responders, p = 0.002). Nineteen out of twenty-three (82.6%) patients recovered from severe neutropenia after 22 (11, 31) days on eltrombopag. Twenty-nine out of thirty-five (82.9%) patients recovered red blood cell (RBC) transfusion independence after 29 (17, 44) days. Seven patients recovered all cell lineages while on treatment. No thromboembolic events were reported. Only two transient toxicities (cholestasis, hyperbilirubinemia) were reported during eltrombopag treatment, none of which compelled permanent drug withdrawal. Conclusions: Eltrombopag could be safely used to manage thrombocytopenia and accelerate transfusion independence in CAR-T cell-treated patients. Full article
(This article belongs to the Section Hematology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flowchart diagram of the study and patients finally enrolled. DP, disease progression; ELT, eltrombopag; LD, lymphodepletion; mo, months; PLT, platelets.</p>
Full article ">Figure 2
<p>Cytopenia recovery subsequent to treatment with eltrombopag (<b>A</b>) The number of patients who recovered PLT/RBC transfusion independence or recovered from ANC &lt; 0.5 × 10<sup>6</sup>/L, together with the total number of patients who required PLT/RBC transfusion or presented with ANC &lt; 0.5 × 10<sup>6</sup>/L before the start of eltrombopag are indicated above each histogram (left). The number of patients who achieved simultaneously either platelet/RBC transfusion independence and ANC ≥ 0.5 × 10<sup>6</sup>/L or recovery from the three severe cytopenias upon eltrombopag treatment is also indicated (right). (<b>B</b>) The same calculations are presented after stratifying patients according to the type of CAR-T cell used. ANC, absolute neutrophil counts; axi-cel, axicabtagene ciloleucel; Hgb, hemoglobin; PLT, platelets; RBC, red blood cells; tisa-cel, tisagenlecleucel.</p>
Full article ">Figure 3
<p><b>Median time elapsed in each one of the phases of the study.</b> The median number of days was considered for each leg. The number of patients submitted to BT and LD, the number (percent) of patients who developed PLT transfusion dependence (above), severe neutropenia (middle), or RBC transfusion dependence (below), and the number (percent) of patients who achieved or did not achieve recovery before the end of the study are indicated. * Only those patients who developed platelet transfusion dependence (above), severe neutropenia (ANC &lt; 0.5 × 10<sup>6</sup>/L, middle), or RBC transfusion dependence (below) were considered. <sup>†</sup> Only those patients who achieved platelet transfusion independence (above), reached ANC levels ≥ 0.5 × 10<sup>6</sup>/L (middle), or achieved RBC transfusion independence (below) were considered. <sup>‡</sup> Only those patients who did not recover from platelet transfusion requirement (above), ANC drop to levels &lt; 0.5 × 10<sup>6</sup>/L (middle) or RBC transfusion requirement (below) were considered. ANC, absolute neutrophil counts; BT, bridging chemotherapy; LD, lymphodepleting chemotherapy; PLT, platelets; RBC, red blood cells.</p>
Full article ">Figure 4
<p><b>Time course of platelet count recovery with eltrombopag.</b> Patients who presented with platelet counts &lt; 20 × 10<sup>9</sup>/L after CAR-T cell therapy and started treatment with eltrombopag were considered. Kaplan-Meier curves were constructed considering the time elapsed between the first administration of eltrombopag and the recovery of platelet counts either ≥20 × 10<sup>9</sup>/L (blue line, <span class="html-italic">n</span> = 29) or ≥50 × 10<sup>9</sup>/L (red line, <span class="html-italic">n</span> = 26). Tick marks indicate those patients whose data were censored at the last follow-up date, either because of exitus or loss to follow-up, without having achieved PLT counts ≥ 20 × 10<sup>9</sup>/L (blue, <span class="html-italic">n</span> = 9) or &gt;50 × 10<sup>9</sup>/L (red, <span class="html-italic">n =</span> 12). ELT, eltrombopag; PLT, platelets.</p>
Full article ">Figure 5
<p>Correlation between total transfused platelet units and time between the start of eltrombopag and platelet transfusion independence achievement. The correlation between the total amount of transfused platelet units and the time elapsed between the start of eltrombopag therapy and the achievement of platelet transfusion independence is shown (<span class="html-italic">n</span> = 29). The one-tailed Rho Spearman test was used. ELT, eltrombopag; PLT, platelets.</p>
Full article ">Figure 6
<p>PLT transfusion requirement according to response to eltrombopag. (<b>A</b>) The amount of platelet units used in the patients who achieved platelet transfusion independence while in treatment with eltrombopag (responders) was compared against the platelet units used in those who had not achieved transfusion independence by the end of follow-up (non-responders). (<b>B</b>) The same comparison was performed within the group of responders, between those who achieved transfusion independence earlier (early responders) or later (late responders) than 30 days after the first dose of eltrombopag was administered. The one-tailed Mann-Whitney U test was used for comparisons. PLT, platelets.</p>
Full article ">Figure 7
<p>Transfusional requirement according to CAR-T cell type. The amount of platelet units (<b>A</b>) or RBC units (<b>B</b>) used in the patients who achieved platelet or RBC transfusion independence, respectively, is shown after categorizing them according to CAR-T cell type. The one-tailed Mann-Whitney U test was used for comparisons. Axi-cel, axicabtagene ciloleucel; PLT, platelets; RBC, red blood cells; tisa-cel, tisagenlecleucel.</p>
Full article ">
16 pages, 3418 KiB  
Article
Biomechanical Study of Symmetric Bending and Lifting Behavior in Weightlifter with Lumbar L4-L5 Disc Herniation and Physiological Straightening Using Finite Element Simulation
by Caiting Zhang, Yang Song, Qiaolin Zhang, Ee-Chon Teo and Wei Liu
Bioengineering 2024, 11(8), 825; https://doi.org/10.3390/bioengineering11080825 - 12 Aug 2024
Viewed by 738
Abstract
Background: Physiological curvature changes of the lumbar spine and disc herniation can cause abnormal biomechanical responses of the lumbar spine. Finite element (FE) studies on special weightlifter models are limited, yet understanding stress in damaged lumbar spines is crucial for preventing and rehabilitating [...] Read more.
Background: Physiological curvature changes of the lumbar spine and disc herniation can cause abnormal biomechanical responses of the lumbar spine. Finite element (FE) studies on special weightlifter models are limited, yet understanding stress in damaged lumbar spines is crucial for preventing and rehabilitating lumbar diseases. This study analyzes the biomechanical responses of a weightlifter with lumbar straightening and L4-L5 disc herniation during symmetric bending and lifting to optimize training and rehabilitation. Methods: Based on the weightlifter’s computed tomography (CT) data, an FE lumbar spine model (L1-L5) was established. The model included normal intervertebral discs (IVDs), vertebral endplates, ligaments, and a degenerated L4-L5 disc. The bending angle was set to 45°, and weights of 15 kg, 20 kg, and 25 kg were used. The flexion moment for lifting these weights was theoretically calculated. The model was tilted at 45° in Abaqus 2021 (Dassault Systèmes Simulia Corp., Johnston, RI, USA), with L5 constrained in all six degrees of freedom. A vertical load equivalent to the weightlifter’s body mass and the calculated flexion moments were applied to L1 to simulate the weightlifter’s bending and lifting behavior. Biomechanical responses within the lumbar spine were then analyzed. Results: The displacement and range of motion (ROM) of the lumbar spine were similar under all three loading conditions. The flexion degree increased with the load, while extension remained unchanged. Right-side movement and bending showed minimal change, with slightly more right rotation. Stress distribution trends were similar across loads, primarily concentrated in the vertebral body, increasing with load. Maximum stress occurred at the anterior inferior margin of L5, with significant stress at the posterior joints, ligaments, and spinous processes. The posterior L5 and margins of L1 and L5 experienced high stress. The degenerated L4-L5 IVD showed stress concentration on its edges, with significant stress also on L3-L4 IVD. Stress distribution in the lumbar spine was uneven. Conclusions: Our findings highlight the impact on spinal biomechanics and suggest reducing anisotropic loading and being cautious of loaded flexion positions affecting posterior joints, IVDs, and vertebrae. This study offers valuable insights for the rehabilitation and treatment of similar patients. Full article
(This article belongs to the Special Issue Advances in Trauma and Injury Biomechanics)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>CT image: (<b>a</b>) sagittal plane (left); (<b>b</b>) coronal plane (right).</p>
Full article ">Figure 2
<p>Modeling process.</p>
Full article ">Figure 3
<p>(<b>a</b>) Human body symmetrical bending and lifting objects schematic; (<b>b</b>) static force analysis of lumbar spine.</p>
Full article ">Figure 4
<p>Boundary and loading conditions in FE model.</p>
Full article ">Figure 5
<p>Displacement cloud diagram and rotation cloud diagram when simulating lifting a 15 kg object. In Abaqus, U1, U2, and U3 represent displacements along the X, Y, and Z axes, respectively. The X-axis represents left-right displacement, the Y-axis represents front-back displacement, and the Z-axis represents up-down displacement. UR1, UR2, and UR3 represent rotations around the X, Y, and Z axes in the local coordinate system. Rotation around the X-axis indicates flexion and extension; rotation around the Y-axis indicates left-right bending; and rotation around the Z-axis indicates left-right rotation.</p>
Full article ">Figure 6
<p>(<b>a</b>) Global stress distribution in the lumbar spine; (<b>b</b>) vertebral stress distribution; (<b>c</b>) IVD stress distribution. From top to bottom are L1-L2IVD, L2-L3IVD, L3-L4IVD, and L4-L5IVD.</p>
Full article ">
19 pages, 1004 KiB  
Article
An Evaluation of Sex-Specific Pharmacokinetics and Bioavailability of Kokusaginine: An In Vitro and In Vivo Investigation
by Kaiqi Shang, Chengyu Ge, Yindi Zhang, Jing Xiao, Shao Liu and Yueping Jiang
Pharmaceuticals 2024, 17(8), 1053; https://doi.org/10.3390/ph17081053 - 9 Aug 2024
Viewed by 753
Abstract
Kokusaginine is a bioactive ingredient extracted from Ruta graveolens L., which has a range of biological activities. Its pharmacokinetic (PK) properties are particularly important for clinical applications; however, they have not been fully elucidated. In addition, the effect of sex differences on drug [...] Read more.
Kokusaginine is a bioactive ingredient extracted from Ruta graveolens L., which has a range of biological activities. Its pharmacokinetic (PK) properties are particularly important for clinical applications; however, they have not been fully elucidated. In addition, the effect of sex differences on drug metabolism is increasingly being recognized, but most studies have ignored this important factor. This study aims to fill this knowledge gap by taking an in-depth look at the PK properties of kokusaginine and how gender affects its metabolism and distribution in the body. It also lays the foundation for clinical drug development. In this study, a sensitive ultra-high-performance liquid chromatography (UPLC) method was developed and validated for quantifying kokusaginine in Sprague Dawley (SD) rat plasma and tissue homogenates. Metabolic stability was evaluated in vitro using gender-specific liver microsomes. Innovatively, we incorporated sex as a variable into both in vitro and in vivo PK studies in SD rats, analyzing key parameters with Phoenix 8.3.5 software. The developed UPLC method demonstrated high sensitivity and precision, essential for PK analysis. Notably, in vitro studies revealed a pronounced sex-dependent metabolic variability (p < 0.05). In vivo, gender significantly affected the Area Under the Moment Curve (AUMC)(0-∞) of the plasma PK parameter (p < 0.05) and the AUMC(0-t) of brain tissue (p < 0.0001), underscoring the necessity of sex-specific PK assessments. The calculated absolute bioavailability of 71.13 ± 12.75% confirmed the favorable oral absorption of kokusaginine. Additionally, our innovative tissue-plasma partition coefficient (Kp) analysis highlighted a rapid and uniform tissue distribution pattern. This study presents a sex-inclusive PK evaluation of kokusaginine, offering novel insights into its metabolic profile and distribution. These findings are instrumental for informing clinical medication practices, dosage optimization, and a nuanced understanding of drug efficacy and safety in a sex-specific context. Full article
(This article belongs to the Section Pharmaceutical Technology)
Show Figures

Figure 1

Figure 1
<p>Specialty chromatogram of kokusaginine in rat plasma (1, kokusaginine; 2, dictamine).</p>
Full article ">Figure 2
<p>Specialty chromatogram of kokusaginine in the heart, liver, spleen, lung, kidney, and brain of rats. ((<b>a</b>), blank sample; (<b>b</b>), a blank sample spiked at the LLOQs; (<b>c</b>), a sample taken from a rat 120 min after oral administration of 28 mg/kg kokusaginine; 1, kokusaginine; 2, dictamine).</p>
Full article ">Figure 3
<p>Residual effects of kokusaginine in rat plasma (1, Kokusaginine; 2, Dictamine).</p>
Full article ">Figure 4
<p>Metabolic elimination curve of kokusaginine in male and female rat liver microsomes (Data are Mean ± SD, <span class="html-italic">n</span> = 3, Equal Sex Ratio, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001, ns—not significant. compared to the male group).</p>
Full article ">Figure 5
<p>Plasma concentration-time curves of kokusaginine in rats after oral administration of kokusaginine 28 mg/kg and i.v. administration 7 mg/kg (Data are Mean ± SD, <span class="html-italic">n</span> = 6, Equal Sex Ratio).</p>
Full article ">Figure 6
<p>Tissue distribution of kokusaginine in rat tissues after oral administration of 28 mg/kg kokusaginine. (Data are Mean ± SD, <span class="html-italic">n</span> = 4, Equal Sex Ratio).</p>
Full article ">Figure 7
<p>Tissue and plasma concentration-time curves of kokusaginine in rats after oral administration of kokusaginine 28 mg/kg (Data are Mean ± SD, <span class="html-italic">n</span> = 4, Equal Sex Ratio).</p>
Full article ">Figure 8
<p>Chemical structures of kokusaginine (<b>a</b>) and dictamine (<b>b</b>).</p>
Full article ">
29 pages, 10214 KiB  
Article
Revisiting the Use of the Gumbel Distribution: A Comprehensive Statistical Analysis Regarding Modeling Extremes and Rare Events
by Cristian Gabriel Anghel
Mathematics 2024, 12(16), 2466; https://doi.org/10.3390/math12162466 - 9 Aug 2024
Viewed by 927
Abstract
The manuscript presents the applicability of the Gumbel distribution in the frequency analysis of extreme events in hydrology. The advantages and disadvantages of using the distribution are highlighted, as well as recommendations regarding its proper use. A literature review was also carried out [...] Read more.
The manuscript presents the applicability of the Gumbel distribution in the frequency analysis of extreme events in hydrology. The advantages and disadvantages of using the distribution are highlighted, as well as recommendations regarding its proper use. A literature review was also carried out regarding the methods for estimating the parameters of the Gumbel distribution in hydrology. Thus, for the verification of the methods, case studies are presented regarding the determination of the maximum annual flows and precipitations using nine methods for estimating the distribution parameters. The influence of the variability of the observed data lengths on the estimation of the statistical indicators, the estimation of the parameters, and the quantiles corresponding to the field of small exceedance probabilities (p < 1%) is also highlighted. In each case, the results are analyzed compared to those obtained with the Generalized Extreme Value distribution, the four-parameter Burr distribution, and the five-parameter Wakeby distribution estimated using the L-moments method. The results of the case studies highlight and reaffirm the statistical, mathematical, and hydrological recommendations regarding the avoidance of applying the Gumbel distribution in flood frequency analysis and its use with reservations in the case of maximum precipitation analysis, especially when the statistical indicators of the analyzed data are not close to the characteristic ones and unique to the distribution. Full article
Show Figures

Figure 1

Figure 1
<p>The flowchart of the presented methodology.</p>
Full article ">Figure 2
<p>The variation curves of the inverse function at different series lengths and values of the coefficient of variation—method of ordinary moments.</p>
Full article ">Figure 2 Cont.
<p>The variation curves of the inverse function at different series lengths and values of the coefficient of variation—method of ordinary moments.</p>
Full article ">Figure 2 Cont.
<p>The variation curves of the inverse function at different series lengths and values of the coefficient of variation—method of ordinary moments.</p>
Full article ">Figure 3
<p>The variation curves of the inverse function at different series lengths and values of the coefficient of variation—method of linear moments.</p>
Full article ">Figure 3 Cont.
<p>The variation curves of the inverse function at different series lengths and values of the coefficient of variation—method of linear moments.</p>
Full article ">Figure 4
<p>The location of the studied rivers and hydrometric stations.</p>
Full article ">Figure 5
<p>The chronological series for the analyzed rivers.</p>
Full article ">Figure 6
<p>The boxplot representation of the analyzed series.</p>
Full article ">Figure 7
<p>The locations of the studied stations.</p>
Full article ">Figure 8
<p>The chronological series for the analyzed stations.</p>
Full article ">Figure 9
<p>The boxplot representation for the Dângeni and N. Balcescu series.</p>
Full article ">Figure 10
<p>Normal Q-Q Plot: Siret, Bahna, and Nicolina Rivers.</p>
Full article ">Figure 11
<p>Graphic correlation of data: Siret River.</p>
Full article ">Figure 12
<p>Graphic correlation of data: Nicolina River.</p>
Full article ">Figure 13
<p>Graphic correlation of data: Bahna River.</p>
Full article ">Figure 14
<p>Graphic representation of quantile functions for the Siret, Bahna, and Nicolina Rivers.</p>
Full article ">Figure 15
<p>Graphical verification of data normality: Dângeni and N. Balcescu Stations.</p>
Full article ">Figure 16
<p>The quantile function results for the Dângeni and N. Balcescu Stations.</p>
Full article ">
19 pages, 2974 KiB  
Article
Characterizing Forest Plot Decay Levels Based on Leaf Area Index, Gap Fraction, and L-Moments from Airborne LiDAR
by Abubakar Sani-Mohammed, Wei Yao, Tsz Chung Wong, Reda Fekry and Marco Heurich
Remote Sens. 2024, 16(15), 2824; https://doi.org/10.3390/rs16152824 - 1 Aug 2024
Viewed by 819
Abstract
Effective forest management is essential for mitigating climate change effects. This is why understanding forest growth dynamics is critical for its sustainable management. Thus, characterizing forest plot deadwood levels is vital for understanding forest dynamics, and for assessments of biomass, carbon stock, and [...] Read more.
Effective forest management is essential for mitigating climate change effects. This is why understanding forest growth dynamics is critical for its sustainable management. Thus, characterizing forest plot deadwood levels is vital for understanding forest dynamics, and for assessments of biomass, carbon stock, and biodiversity. For the first time, this study used the leaf area index (LAI) and L-moments to characterize and model forest plot deadwood levels in the Bavarian Forest National Park from airborne laser scanning (ALS) data. This study proposes methods that can be tested for forests, especially those in temperate climates with frequent cloud coverage and limited access. The proposed method is practically significant for effective planning and management of forest resources. First, plot decay levels were characterized based on their canopy leaf area density (LAD). Then, the deadwood levels were modeled to assess the relationships between the vegetation area index (VAI), gap fraction (GF), and the third L-moment ratio (T3). Finally, we tested the rule-based methods for classifying plot decay levels based on their biophysical structures. Our results per the LAD vertical profiles clearly showed the declining levels of decay from Level 1 to 5. Our findings from the models indicate that at a 95% confidence interval, 96% of the variation in GF was explained by the VAI with a significant negative association (VAIslope = −0.047; R2 = 0.96; (p < 0.001)), while the VAI explained 92% of the variation in T3 with a significant negative association (VAIslope = −0.50; R2 = 0.92; (p < 0.001)). Testing the rule-based methods, we found that the first rule (Lcv = 0.5) classified Levels 1 and 2 at (Lcv < 0.5) against Levels 3 to 5 at (Lcv > 0.5). However, the second rule (Lskew = 0) classified Level 1 (healthy plots) as closed canopy areas (Lskew < 0) against Levels 2 to 5 (deadwood) as open canopy areas (Lskew > 0). This approach is simple and more convenient for forest managers to exploit for mapping large forest gap areas for planning and managing forest resources for improved and effective forest management. Full article
Show Figures

Figure 1

Figure 1
<p>Map of the BFNP (light green) illustrating regions of the three ALS transects (blue) and the selected plots (red).</p>
Full article ">Figure 2
<p>The five selected plots (at 30 m radius) decay levels resulting from a fusion of the ALS point clouds and CIR imagery viewing from above the canopies. The healthy trees are reddish to brown while the dead trees are gray/dark gray to green in color.</p>
Full article ">Figure 3
<p>Schematic illustration of the sub-plot (concentric circles in short dashes) creation for each decay level (not drawn to scale).</p>
Full article ">Figure 4
<p>The general methodological flowchart.</p>
Full article ">Figure 5
<p>LAD vertical profiles of plot decay levels at varied radii (5, 10, 15, 20, 25, and 30 m).</p>
Full article ">Figure 6
<p>The relationship between VAI and GF in modeling plot decay levels (black line) at a 95% confidence interval (light gray around the line of best fit).</p>
Full article ">Figure 7
<p>The relationship between VAI and T3 in modeling plot decay levels (black line) at a 95% confidence interval (light gray around the line of best fit).</p>
Full article ">Figure 8
<p>Classification of plot decay levels based on the rule-based methods in the BFNP, (<b>a</b>) graph of the first rule-based method (short dashes represent the threshold, <span class="html-italic">Lcv</span> = 0.5); (<b>b</b>) graph of the second rule-based method (short dashes represent the threshold, <span class="html-italic">Lskew</span> = 0); the numbers indicated in the graph by the plots are the radii for respective plots.</p>
Full article ">
9 pages, 1268 KiB  
Article
High-Efficiency In Vitro Root Induction in Pear Microshoots (Pyrus spp.)
by Jae-Young Song, Jinjoo Bae, Young-Yi Lee, Ji-Won Han, Ye-ji Lee, Sung Hee Nam, Ho-sun Lee, Seok Cheol Kim, Se Hee Kim and Byeong Hyeon Yun
Plants 2024, 13(14), 1904; https://doi.org/10.3390/plants13141904 - 10 Jul 2024
Viewed by 612
Abstract
Extensive research has been conducted on the in vitro mass propagation of pear (Pyrus spp.) trees through vegetative propagation, demonstrating high efficiency in shoot multiplication across various pear species. However, the low in vitro rooting rates remain a significant barrier to the [...] Read more.
Extensive research has been conducted on the in vitro mass propagation of pear (Pyrus spp.) trees through vegetative propagation, demonstrating high efficiency in shoot multiplication across various pear species. However, the low in vitro rooting rates remain a significant barrier to the practical application and commercialization of mass propagation. This study aims to determine the favorable conditions for inducing root formation in the in vitro microshoots of Pyrus genotypes. The base of the microshoots was exposed to a high concentration (2 mg L−1) of auxins (a combination of IBA and NAA) for initial root induction at the moment when callus formation begins. The microshoots were then transferred to an R1 medium (1/2 MS with 30 g L−1 sucrose without PGRs) to promote root development. This method successfully induced rooting in three European pear varieties, one Asian pear variety, and a European–Asian hybrid, resulting in rooting rates of 66.7%, 87.2%, and 100% for the European pear (P. communis), 60% for the Asian pear (P. pyrifolia), and 83.3% for the hybrid pear (P. pyrifolia × P. communis) with an average of 25 days. In contrast, the control group (MS medium) exhibited rooting rates of 0–13.3% after 60 days of culture. These findings will enhance in vitro root induction for various pear varieties and support the mass propagation and acclimatization of pear. The in vitro root induction method developed in this study has the potential for global commercial application in pear cultivation. Full article
(This article belongs to the Special Issue Plant Tissue Culture and Plant Regeneration)
Show Figures

Figure 1

Figure 1
<p>In vitro microshoots for initial root induction. (<b>A</b>) In vitro proliferation of microshoot cultures of pear grown on MS medium supplemented with 2 mg L<sup>−1</sup> BA and 0.2 mg L<sup>−1</sup> IBA. (<b>B</b>) Microshoots on MS medium before transfer to R0-IN medium with auxin. (<b>C</b>) Swollen base of microshoots on R0-IN medium. (<b>D</b>) Microshoot base before PGR treatment. (<b>E</b>) Swollen base of ‘Bartlett’ after 1–2 days on R0-IN medium. (<b>F</b>) Swollen base of ‘BaeYun No. 3’ after 10 days on R0-IN medium. (<b>G</b>) Swollen base of ‘Oharabeni’ after 3 days on R0-IN medium.</p>
Full article ">Figure 2
<p>Effect of IBA, NAA, and their combination on the in vitro root formation of ‘Bartlett’ microshoots using a two-step treatment method. MS refers to the rooting rate of microshoots on the MS medium after 30 days of culture. R0-I, R0-N, and R0-IN indicate the rooting rates of microshoots after 1 day of exposure to R0-I (2 mg L<sup>−1</sup> IBA), R0-N (2 mg L<sup>−1</sup> NAA), and R0-IN (1 mg L<sup>−1</sup> each of IBA and NAA), respectively, followed by transfer to the R1 (PGR-free) medium for 14 days. Different letters on bars indicate significant differences at <span class="html-italic">p</span> &lt; 0.05 according to Duncan’s multiple range test. Twelve plants per treatment were used, with three replications.</p>
Full article ">Figure 3
<p>In vitro rooting of five different pear genotypes. The microshoots cultured on the initial root induction medium (R0-IN) in the dark for specified days were moved to the medium (R1).</p>
Full article ">
21 pages, 3024 KiB  
Article
Preliminary Investigation of Fruit Mash Inoculation with Pure Yeast Cultures: A Case of Volatile Profile of Industrial-Scale Plum Distillates
by Josef Balák, Lucie Drábová, Vojtěch Ilko, Dominik Maršík and Irena Jarošová Kolouchová
Foods 2024, 13(12), 1955; https://doi.org/10.3390/foods13121955 - 20 Jun 2024
Viewed by 924
Abstract
This study investigates the effect of pure yeast culture fermentation versus spontaneous fermentation on the volatile compound profile of industrially produced plum brandy. Using traditional distillation methods, the evolution of key volatile compounds is monitored at seven different moments during the distillation process. [...] Read more.
This study investigates the effect of pure yeast culture fermentation versus spontaneous fermentation on the volatile compound profile of industrially produced plum brandy. Using traditional distillation methods, the evolution of key volatile compounds is monitored at seven different moments during the distillation process. By integrating advanced analytical techniques such as GC-MS and sensory evaluation, significant differences in the composition of the distillates are highlighted, particularly in terms of ethyl esters and higher alcohols which are key to the sensory properties of the final product. Distillates produced with the addition of pure cultures gave higher concentrations of esters than those obtained by wild fermentation. The results of our industrial research show that the most critical step is to limit the storage of the input raw material, thereby reducing the subsequent risk of producing higher concentrations of 1-propanol. Furthermore, our results indicate that the heart of the distillate can only be removed up to an ethanol content of approximately 450 g/L and that the removal of additional ethanol results in only a 10% increase in the total volume of the distillate, which in turn results in an increase in boiler heating costs of approximately 30%. Full article
(This article belongs to the Section Food Biotechnology)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>)—Raw material (plums) was disintegrated and split into three tanks. (<b>B</b>)—Fermentation provided by wild microflora. (<b>C</b>)—Fermentation with the addition of a pure yeast culture of strain SP7. (<b>D</b>)—Fermentation with the addition of a pure yeast culture of strain DV10. (<b>E</b>)—Distillation in a single pot still with column. (<b>F</b>)—Chemical analysis (GC-FID).</p>
Full article ">Figure 2
<p>Mean relative contribution (%) of major compounds in plum brandies produced from wild, SP7, and DV10 yeasts fermentation.</p>
Full article ">Figure 3
<p>Mean relative contribution (%) of carbonyl compounds in plum brandies produced from wild, SP7, and DV10 yeasts fermentation.</p>
Full article ">Figure 4
<p>Mean relative contribution (%) of minor alcohols in plum brandies produced from wild, SP7, and DV10 yeasts fermentation.</p>
Full article ">Figure 5
<p>Mean relative contribution (%) of minor esters in plum brandies produced from wild, SP7, and DV10 yeasts fermentation.</p>
Full article ">Figure 6
<p>Evolution of the concentration of selected substances during the distillation of the heart fraction of plum distillates—decreasing concentration over time. (<b>A</b>)—2-butanol, (<b>B</b>)—1-propanol, (<b>C</b>)—methylacetate, (<b>D</b>)—ethyl acetate, (<b>E</b>)—nonanal, (<b>F</b>)—isobutyl acetate, (<b>G</b>)—hexyl acetate.</p>
Full article ">Figure 7
<p>Evolution of the concentration of selected substances during the distillation of the heart fraction of plum distillates—increasing concentration over time. (<b>A</b>)—methanol, (<b>B</b>)—furfural, (<b>C</b>)—linalool, (<b>D</b>)—α-terpineol, (<b>E</b>)—dekanol, (<b>F</b>)—benzyl alcohol, (<b>G</b>)—eugenol, (<b>H</b>)—acetic acid.</p>
Full article ">Figure 8
<p>Evolution of ethanol concentration during the distillation of plum brandies.</p>
Full article ">Figure 9
<p>Comparison of taste profiles of samples fermented with the addition of pure yeast cultures. * Significant difference: <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 10
<p>Comparison of odour profiles of samples fermented with the addition of pure yeast cultures. * Significant difference: <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 11
<p>Comparison of additional sensory descriptors of samples fermented with the addition of pure yeast cultures. * Significant difference: <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">
21 pages, 12993 KiB  
Article
Effective Flange Width Based on Equivalence of Slab Crack Width at Hogging Moment Region of Composite Frame Beam
by Mu-Xuan Tao, Ze-Bin Zou and Ji-Zhi Zhao
Buildings 2024, 14(6), 1708; https://doi.org/10.3390/buildings14061708 - 7 Jun 2024
Viewed by 533
Abstract
Steel–concrete composite structures have advantages in terms of strong bearing capacity and full utilisation of performance, and thus, composite frame beams are widely used in building construction. However, in the design and use of existing composite frame beams, the composite effect of a [...] Read more.
Steel–concrete composite structures have advantages in terms of strong bearing capacity and full utilisation of performance, and thus, composite frame beams are widely used in building construction. However, in the design and use of existing composite frame beams, the composite effect of a slab and steel beam cannot be completely taken into account. In this study, the effective flange width method is utilised to calculate the contribution of the slab reinforcement to the section moment of inertia to check the beam-end crack width via simulations using the general finite-element software MSC.MARC 2020. A parameter sensitivity analysis of the reinforcement tensile stress is conducted to determine critical influential geometric parameters for the side-column and centre-column hogging moment regions. Finally, design formulae for calculating the effective flange widths of the side- and centre-column hogging moment regions are proposed. In the formula for the side-column hogging moment region, the half column width (R) and steel-beam height (hs) are critical variables, whereas, in the formula for the centre-column hogging moment region, the steel-beam height (hs), slab width (bc), and half clear-span length (l) are critical variables. Both formulas are verified via a multiparameter simulation, which enables more accurate crack-checking calculations for the hogging moment region in the serviceability limit state. This study provides an important reference for fine finite-element simulations of serviceability limit states and shows the factors affecting the effective flange width that differ from those in the ultimate limit state. Full article
(This article belongs to the Special Issue High-Performance Steel–Concrete Composite/Hybrid Structures)
Show Figures

Figure 1

Figure 1
<p>Layered shell elements of the slab.</p>
Full article ">Figure 2
<p>Connection between slabs and steel beams.</p>
Full article ">Figure 3
<p>Simulation of the composite frames tested and analysed. (Reprinted with permission from Ref. [<a href="#B12-buildings-14-01708" class="html-bibr">12</a>] 2012, Nie et al.). (<b>a</b>) Elaborate FE model. (<b>b</b>) Shear stress at the positive displacement of 150 mm. (<b>c</b>) Comparison of test and numerical results. (<b>d</b>) Comparison of numerical results and with different parameters.</p>
Full article ">Figure 4
<p>Composite frame beam models.</p>
Full article ">Figure 5
<p>Boundary constraints in Marc models.</p>
Full article ">Figure 6
<p>Influential parameters for side-column EFW. (<b>a</b>) EFWs for different steel-beam heights in the single-span model. (<b>b</b>) EFWs for different column widths in the single-span model. (<b>c</b>) EFWs for different steel-beam heights in the double-span model. (<b>d</b>) EFWs for different column widths in the single-span model.</p>
Full article ">Figure 7
<p>Stress distribution along slab width (<math display="inline"><semantics> <mi>R</mi> </semantics></math> &lt; 300 mm).</p>
Full article ">Figure 8
<p>Stress distribution along slab width (<math display="inline"><semantics> <mi>R</mi> </semantics></math> ≥ 300 mm).</p>
Full article ">Figure 9
<p>Irrelevant column parameters for side-column EFW. (<b>a</b>) EFWs for different column heights in the double-span model. (<b>b</b>) EFWs for different steel-tube thicknesses in the double-span model.</p>
Full article ">Figure 10
<p>Irrelevant steel-beam parameters for side-column EFW. (<b>a</b>) EFWs for different steel-beam top-flange widths in the double-span model. (<b>b</b>) EFWs for different steel-beam bottom-flange widths in the double-span model. (<b>c</b>) EFWs for different steel-beam flange thicknesses in the double-span model. (<b>d</b>) EFWs for different steel-beam web thicknesses in the double-span model.</p>
Full article ">Figure 11
<p>Irrelevant transom parameters for side-column EFW. (<b>a</b>) EFWs for different transom top-flange widths in the double-span model. (<b>b</b>) EFWs for different transom bottom-flange widths in the double-span model. (<b>c</b>) EFWs for different transom flange thicknesses in the double-span model. (<b>d</b>) EFWs for different transom web thicknesses in the double-span model. (<b>e</b>) EFW for different transom heights in the double-span model.</p>
Full article ">Figure 12
<p>Irrelevant slab parameters for side-column EFW. (<b>a</b>) EFWs for different slab widths in the double-span model. (<b>b</b>) EFWs for different clear-span lengths in the double-span model.</p>
Full article ">Figure 13
<p>Influential parameters for centre-column EFW. (<b>a</b>) EFWs for different slab widths in the double-span model. (<b>b</b>) EFWs for different clear-span lengths in the double-span model. (<b>c</b>) EFWs for different steel-beam heights in the double-span model.</p>
Full article ">Figure 14
<p>Stress distribution along slab width.</p>
Full article ">Figure 15
<p>Irrelevant column parameters for centre-column EFW. (<b>a</b>) EFWs for different column heights in the double-span model. (<b>b</b>) EFWs for different steel-tube thicknesses in the double-span model. (<b>c</b>) EFWs for different column widths in the double-span model.</p>
Full article ">Figure 16
<p>Irrelevant steel-beam parameters for centre-column EFW. (<b>a</b>) EFWs for different steel-beam top-flange widths in the double-span model. (<b>b</b>) EFWs for different steel-beam bottom-flange widths in the double-span model. (<b>c</b>) EFWs for different steel-beam flange thicknesses in the double-span model. (<b>d</b>) EFWs for different steel-beam web thicknesses in the double-span model.</p>
Full article ">Figure 17
<p>Irrelevant transom parameters for centre-column EFW. (<b>a</b>) EFWs for different transom top-flange widths in the double-span model. (<b>b</b>) EFWs for different transom bottom-flange widths in the double-span model. (<b>c</b>) EFWs for different transom flange thicknesses in the double-span model. (<b>d</b>) EFWs for different transom web thicknesses in the double-span model. (<b>e</b>) EFWs for different transom heights in the double-span model.</p>
Full article ">Figure 18
<p>Numerical and proposed-formula results for half column width (<math display="inline"><semantics> <mi>R</mi> </semantics></math>) in side columns.</p>
Full article ">Figure 19
<p>Numerical and proposed-formula results for steel-beam height (<math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi mathvariant="normal">s</mi> </msub> </mrow> </semantics></math>) in side columns.</p>
Full article ">Figure 20
<p>Ratio of EFWD to EFWM for side column.</p>
Full article ">Figure 21
<p>Numerical and proposed-formula results for half clear-span length (<math display="inline"><semantics> <mi>l</mi> </semantics></math>) in center columns.</p>
Full article ">Figure 22
<p>Numerical and proposed-formula results of slab breadth (<math display="inline"><semantics> <mrow> <msub> <mi>b</mi> <mi>c</mi> </msub> </mrow> </semantics></math>) in center columns.</p>
Full article ">Figure 23
<p>Numerical and proposed-formula results for steel-beam height (<math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>s</mi> </msub> </mrow> </semantics></math>) in center columns.</p>
Full article ">Figure 24
<p>Ratio of EFWD to EFWM for centre column.</p>
Full article ">Figure 25
<p>Comparison between EC4 and proposed formulae for centre columns.</p>
Full article ">Figure 26
<p>Comparison between AISC and proposed formulae for centre columns.</p>
Full article ">
9 pages, 1405 KiB  
Article
Sperm Incubation in Biggers–Whitten–Whittingham Medium Induces Capacitation-Related Changes in the Lizard Sceloporus torquatus
by Uriel Ángel Sánchez-Rivera, Norma Berenice Cruz-Cano, Alfredo Medrano, Carmen Álvarez-Rodríguez and Martín Martínez-Torres
Animals 2024, 14(9), 1388; https://doi.org/10.3390/ani14091388 - 6 May 2024
Viewed by 1264
Abstract
Sperm capacitation involves biochemical and physiological changes that enable sperm to fertilize the oocyte. It can be induced in vitro under controlled conditions that simulate the environment of the oviduct. While extensively studied in mammals, its approach in lizards remains absent. Understanding the [...] Read more.
Sperm capacitation involves biochemical and physiological changes that enable sperm to fertilize the oocyte. It can be induced in vitro under controlled conditions that simulate the environment of the oviduct. While extensively studied in mammals, its approach in lizards remains absent. Understanding the mechanisms that ensure reproduction is essential for advancing the implementation of assisted reproductive technologies in this group. We aimed to perform a sperm analysis to determine if capacitation-related changes were induced after incubation with capacitating media. Fifteen males of Sceloporus torquatus were collected during the early stage of the reproductive season. The sperm were isolated from the seminal plasma and then diluted up to a volume of 150 μL using BWW medium to incubate with 5% CO2 at 30 °C for a maximum duration of 3 h. A fraction was retrieved hourly for ongoing sperm assessment. The sperm analysis included assessments of its motility, viability, the capacitation status using the chlortetracycline (CTC) assay, and the acrosome integrity with the lectin binding assay to detect changes during incubation. We found that total motility was maintained up to 2 h post incubation, after which it decreased. However, sperm viability remained constant. From that moment on, we observed a transition to a deeper and less symmetrical flagellar bending in many spermatozoa. The CTC assay indicated a reduction in the percentage of sperm showing the full (F) pattern and an increase in those exhibiting the capacitated (B) and reactive (RA) patterns, accompanied by an elevation in the percentage of damaged acrosomes as revealed by the lectin binding assay. In mammals, these changes are often associated with sperm capacitation. Our observations support the notion that this process may also occur in saurian. While sperm analysis is a valuable method for assessing certain functional changes, additional approaches are required to validate this process. Full article
(This article belongs to the Special Issue Animal Reproduction: Semen Quality Assessment, Volume II)
Show Figures

Figure 1

Figure 1
<p>Representative images of <span class="html-italic">Sceloporus torquatus</span> sperm evaluation. (<b>A</b>) shows live (L) and dead (D) spermatozoa stained with eosin nigrosin, (<b>B</b>) shows full (F), band (B), and acrosome-reacted (RA) patterns indicative of capacitance state, as revealed by the CTC assay, and (<b>C</b>) shows sperm with intact (IA) and damaged acrosome (DA) spermatozoa, as revealed by the lectin binding assay. Linear bars correspond to 10 µm.</p>
Full article ">Figure 2
<p>(<b>a</b>) Sperm motility and (<b>b</b>) viability of <span class="html-italic">Sceloporus torquatus</span> incubated in BWW medium. The lines represent the standard error of the mean. Different letters indicate significant differences between incubation times (Dunn, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>The clorthetracyclin (CTC) sperm patterns of <span class="html-italic">Sceloporus torquatus</span> incubated in BWW medium. The lines represent the standard error of the mean. Different letters and asterisks indicate significant differences between incubation times in each pattern (Dunn, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Sperm acrosome integrity of <span class="html-italic">Sceloporus torquatus</span> incubated in BWW medium. The lines represent the standard error of the mean. Different letters and asterisks indicate significant differences between incubation times (Dunn, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
11 pages, 606 KiB  
Article
The Day After: The Longitudinal Effect of COVID-19 Lockdown on Quality of Life of University Students and the Moderator Role of Mindfulness
by Pamela Barone, Carmen Borrás-Sansaloni, Marina Ricco-Pérez, Emilio López-Navarro and Capilla Navarro-Guzmán
J. Clin. Med. 2024, 13(8), 2340; https://doi.org/10.3390/jcm13082340 - 18 Apr 2024
Viewed by 730
Abstract
Background: The COVID-19 lockdown has been a major stressor for the general population, posing a considerable threat to quality of life (QoL), particularly among university students. Existing research highlights the protective role of dispositional mindfulness (DM) in mitigating stressors; however, its influence on [...] Read more.
Background: The COVID-19 lockdown has been a major stressor for the general population, posing a considerable threat to quality of life (QoL), particularly among university students. Existing research highlights the protective role of dispositional mindfulness (DM) in mitigating stressors; however, its influence on moderating the impact of COVID-19 on QoL remains unknown. We used a longitudinal design to assess the QoL of undergraduate students before and after the COVID-19 lockdown, while also examining the potential moderating effect of DM on this impact. Methods: One hundred eleven Spanish undergraduate students were recruited in 2019, and 103 were followed-up in 2020. Instruments comprised a demographic questionnaire, the World Health Organization Quality of Life BREF (WHOQOL-BREF) inventory to assess QoL, and the Five Facets Mindfulness Questionnaire (FFMQ) to assess DM. Results: Analyses revealed statistically significant differences between the two time points in WHOQOL-BREF: Psychological, Social Relationships, and Environmental. Moderation analyses revealed that the impact of COVID-19 on WHOQOL-BREF Psychological scores was moderated by FFMQ-Observe and FFMQ-Non-judging. Conclusions: The COVID-19 lockdown resulted in a reduction of QoL among undergraduate students, yet this impact was moderated by DM. Specifically, present moment attention to experience (observe) and non-judgmental awareness attenuated the impact of COVID-19 on psychological well-being. Future research should focus on evaluating the protective role of preventive interventions designed to increase DM among undergraduate students. Full article
Show Figures

Figure 1

Figure 1
<p>Moderation effect of the FFMQ-Observe (<b>a</b>) and of the FFMQ-Non-judging (<b>b</b>) scores on the impact of year on WHOQOL-BREF Psychological scores.</p>
Full article ">
21 pages, 2167 KiB  
Article
PID Control Assessment Using L-Moment Ratio Diagrams
by Paweł D. Domański, Krzysztof Dziuba and Radosław Góra
Appl. Sci. 2024, 14(8), 3331; https://doi.org/10.3390/app14083331 - 15 Apr 2024
Viewed by 747
Abstract
This paper presents an application of L-moments and respective L-moment ratio diagrams (LMRD) to the task of control performance assessment (CPA). An L-moment ratio diagram is a graphical approach to the visualization of statistical properties for a given time series. Moreover, it enables [...] Read more.
This paper presents an application of L-moments and respective L-moment ratio diagrams (LMRD) to the task of control performance assessment (CPA). An L-moment ratio diagram is a graphical approach to the visualization of statistical properties for a given time series. Moreover, it enables comparing various data, showing their similarities and homogeneity. Simultaneously, CPA aims at measuring the control loop quality, supporting decision-making about their tuning and maintenance. This paper shows that control system quality can be efficiently visualized using LMRDs. The method was analyzed using simulations and further validated at a real chemical engineering industrial ammonia synthesis plant. Full article
(This article belongs to the Special Issue Robotics and Industrial Automation: From Methods to Applications)
Show Figures

Figure 1

Figure 1
<p>The simulation close-loop system diagram.</p>
Full article ">Figure 2
<p>Time series for the loop <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, which was run using the so-called well-tuned PID algorithm (blue line—process variable, green—setpoint, magenta—manipulated variable).</p>
Full article ">Figure 3
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot <math display="inline"><semantics> <mi>κ</mi> </semantics></math>.</p>
Full article ">Figure 4
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to settling time.</p>
Full article ">Figure 5
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to ISE.</p>
Full article ">Figure 6
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to IAE.</p>
Full article ">Figure 7
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 8
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to settling time.</p>
Full article ">Figure 9
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 10
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to settling time.</p>
Full article ">Figure 11
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 12
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to settling time.</p>
Full article ">Figure 13
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>4</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to IAE.</p>
Full article ">Figure 14
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>4</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 15
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>4</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 16
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>5</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to IAE.</p>
Full article ">Figure 17
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>5</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 18
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>5</mn> </msub> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> related to overshoot.</p>
Full article ">Figure 19
<p>Schematic diagram of the ammonia production plant.</p>
Full article ">Figure 20
<p>The LMRD(<math display="inline"><semantics> <mrow> <mi>L</mi> <mi>c</mi> <mi>V</mi> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for July 2020.</p>
Full article ">Figure 21
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for July 2020.</p>
Full article ">Figure 22
<p>The LMRD(<math display="inline"><semantics> <mrow> <mi>L</mi> <mi>c</mi> <mi>V</mi> <mo>,</mo> <msub> <mi>τ</mi> <mn>3</mn> </msub> </mrow> </semantics></math>) for loop #15.</p>
Full article ">Figure 23
<p>The LMRD(<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>τ</mi> <mn>4</mn> </msub> </mrow> </semantics></math>) for loop #15.</p>
Full article ">
11 pages, 677 KiB  
Article
Measuring Cardiorespiratory Fitness without Exercise Testing: The Development and Validation of a New Tool for Spanish Adults
by Helmut Schröder, Isaac Subirana, Roberto Elosua, Anna Camps-Vilaró, Helena Tizón-Marcos, Montserrat Fitó, Santiago F. Gómez, Irene R. Dégano and Jaume Marrugat
J. Clin. Med. 2024, 13(8), 2210; https://doi.org/10.3390/jcm13082210 - 11 Apr 2024
Viewed by 1079
Abstract
Background: Cardiorespiratory fitness (CRF) is an important component of overall physical fitness and is associated with numerous health benefits, including a reduced risk of heart disease, diabetes, and obesity. However, direct measurement of CRF is time-consuming and therefore not feasible for screening purposes. [...] Read more.
Background: Cardiorespiratory fitness (CRF) is an important component of overall physical fitness and is associated with numerous health benefits, including a reduced risk of heart disease, diabetes, and obesity. However, direct measurement of CRF is time-consuming and therefore not feasible for screening purposes. Methods: A maximal treadmill exercise test with the Bruce protocol was performed to estimate VO2max in 1047 Spanish men and women aged 17 to 62 years. Weight, height, and heart rate were measured. Leisure-time physical activity (LTPA) was recorded using the Minnesota Leisure Time Physical Activity Questionnaire. A multiple linear regression model was developed to predict exercise-based VO2max. The validity of the model was examined by correlation, concordance, Bland–Altman analysis, cross-validation, and construct validity analysis. Results: There was no significant difference between VO2max obtained by the Bruce protocol (43.56 mL/kg/min) or predicted by the equation (43.59 mL/kg/min), with R2 of 0.57, and a standard error of the estimate of 7.59 mL/kg/min. Pearson’s product–moment correlation and Lin’s concordance correlation between measured and predicted CRF values were 0.75 and 0.72, respectively. Bland–Altman analysis revealed a significant proportional bias of non-exercise eCRF, overestimating unfit and underestimating highly fit individuals. However, 64.3% of participants were correctly classified into CRF tertile categories, with an important 69.9% in the unfit category. Conclusions: The eCRF equation was associated with several cardiovascular risk factors in the anticipated directions, indicating good construct validity. In conclusion, the non-exercise eCRF showed a reasonable validity to estimate true VO2max, and it may be a useful tool for screening CRF. Full article
(This article belongs to the Section Sports Medicine)
Show Figures

Figure 1

Figure 1
<p>Agreement between measured and estimated VO<sub>2max</sub> by Bland–Altman method. Red dashed lines: 95% confidence interval. Black line: difference between measured and estimated VO<sub>2max</sub>. Blue line: regression line (regression coefficient: −0.319, 95%CI −0.316–0.257, <span class="html-italic">p</span> &lt; 0.001) of the association between measured and estimated VO<sub>2max</sub>.</p>
Full article ">
Back to TopTop