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This article explores the punching shear behavior of GFRP-RC interior slab–column connections. The parameters tested included the column–aspect ratio (1.0, 2.0, 3.0, 4.0, and 5.0), perimeter-to-depth ratio for square column stubs with side lengths of 0.3, 0.4, 0.5, 0.6, and 0.7 meters, and
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This article explores the punching shear behavior of GFRP-RC interior slab–column connections. The parameters tested included the column–aspect ratio (1.0, 2.0, 3.0, 4.0, and 5.0), perimeter-to-depth ratio for square column stubs with side lengths of 0.3, 0.4, 0.5, 0.6, and 0.7 meters, and span-to-depth ratios of 4, 6, 8, 10, and 12. A review of the literature revealed that no previous study has investigated the effect of these parameters or their interactions on this type of connection. Numerically, twenty-five slabs were created using finite element (FE) software (V3), each with square dimensions of 2.5 meters and a constant thickness of 0.2 meters. The central column extended 0.3 meters from the top and bottom of the slab. All four sides of the slabs were supported, and the specimens underwent pure static shear load testing. The test results demonstrated that all slabs failed due to punching shear. Increasing any parameter value reduced the punching shear stresses. Additionally, the results indicated that Canadian (CSA-S806-12) and Japanese (JSCE-97) standards for FRP-RC materials generally provided the closest predictions of punching shear capacity compared to the American guideline, ACI 440.1R-22. However, all standards exhibited shortcomings and require enhancement and modifications, particularly to consider the impact of the span-to-depth ratio. Therefore, three equations were developed to predict the shear strength of the connections, yielding better results than those prescribed by the North American and Japanese standards.
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Titanium alloys have been widely used in aerospace and other fields due to their excellent properties such as light weight and high strength. However, the extremely poor tribological properties of titanium alloys limit their applications in certain special working conditions. In order to
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Titanium alloys have been widely used in aerospace and other fields due to their excellent properties such as light weight and high strength. However, the extremely poor tribological properties of titanium alloys limit their applications in certain special working conditions. In order to improve the tribological properties of titanium alloys, the zirconia coatings were prepared on the surface of a TC4 titanium alloy using the discharge plasma sintering method in this article. The influence of sintering parameters on properties such as density, adhesion, hardness, and phase composition, as well as tribological properties (friction coefficient, wear rate) were investigated, and the influence mechanism of the coating structure on its mechanical and frictional properties was analyzed. The results showed that, with the increase in sintering temperature, the density, bonding strength, and hardness of the zirconia coating were significantly improved. The zirconia coating prepared at a sintering temperature of 1500 °C and a sintering time of 20 min had the lowest friction coefficient and wear rate, which are 0.33 and 6.2 × 10−8 cm3·N−1·m−1, respectively. Numerical analysis showed that the increase in temperature and the extension of time contributed to the extension of the diffusion distance between zirconia and titanium, thereby improving the interfacial adhesion. The influence mechanism of different sintering temperatures and sintering times on the wear performance of zirconia coatings was explained through Hertz contact theory.
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The Dutch housing market comprises three sectors: social-rented, private-rented, and owner-occupied. The contemporary market is marked by a shortage of supply and a large subsidised social sector. Waiting lists for social housing are growing, whereas households with incomes above the limit do not
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The Dutch housing market comprises three sectors: social-rented, private-rented, and owner-occupied. The contemporary market is marked by a shortage of supply and a large subsidised social sector. Waiting lists for social housing are growing, whereas households with incomes above the limit do not or cannot leave the social sector. Government policy and market regulations change frequently, not least for political reasons. In view of commonly recognised problems in the housing market, this article considers the ‘internal demand’ of those households that are dissatisfied with their current residence. We examine the effects of regulatory policy by means of an exploratory agent-based simulation. The results provide perspectives on how internal demand is impacted by regulations in a housing market that is suffering from a shortage, and allow decision makers to weigh the pros and cons of policy measures.
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Maryam Pourhassan, Bjoern Buehring, Ulrik Stervbo, Sven Rahmann, Felix Mölder, Sebastian Rütten, Nina Rosa Neuendorff, Timm Henning Westhoff, Nina Babel and Rainer Wirth
Osteosarcopenia, the concurrent presence of sarcopenia and osteopenia/osteoporosis, poses a significant health risk to older adults, yet its impact on clinical outcomes is not fully understood. The aim of this prospective, longitudinal multicentre study was to examine the impact of osteosarcopenia on 3-year
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Osteosarcopenia, the concurrent presence of sarcopenia and osteopenia/osteoporosis, poses a significant health risk to older adults, yet its impact on clinical outcomes is not fully understood. The aim of this prospective, longitudinal multicentre study was to examine the impact of osteosarcopenia on 3-year mortality and unplanned hospitalizations among 572 older hospitalized patients (mean age 75.1 ± 10.8 years, 78% female). Sarcopenia and low bone mineral density (BMD) were evaluated using Dual Energy X-ray Absorptiometry and the European Working Group on Sarcopenia in Older People (EWGSOP2) and WHO criteria, respectively. Among participants, 76% had low BMD, 9% were sarcopenic, and 8% had osteosarcopenia. Individuals with osteosarcopenia experienced a significantly higher rate of mortality (46%, p < 001) and unplanned hospitalization (86%, p < 001) compared to those without this condition. Moreover, “healthy” subjects—those without sarcopenia or low BMD—showed markedly lower 3-year mortality (9%, p < 001) and less unplanned hospitalization (53%, p < 001). The presence of osteosarcopenia (p = 0.009) increased the 3-year mortality risk by 30% over sarcopenia alone and by 8% over low BMD alone, underscoring the severe health implications of concurrent muscle and bone deterioration. This study highlights the substantial impact of osteosarcopenia on mortality among older adults, emphasizing the need for targeted diagnostic and therapeutic strategies.
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Microscopic traffic simulations have become increasingly important for research targeting connected vehicles. They are especially appreciated for enabling investigations targeting large areas, which would be practically impossible or too expensive in the real world. However, such large-scale simulation scenarios often lack validation with
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Microscopic traffic simulations have become increasingly important for research targeting connected vehicles. They are especially appreciated for enabling investigations targeting large areas, which would be practically impossible or too expensive in the real world. However, such large-scale simulation scenarios often lack validation with real-world measurements since these data are often not available. To overcome this issue, this work integrates probe counts from floating car data as reference counts to model a large-scale microscopic traffic scenario with high-resolution detector data. To integrate the frequent probe counts, a road network matching is required. Thus, a novel road network matching method based on a decision tree classifier is proposed. The classifier automatically adjusts its cosine similarity and Hausdorff distance-based similarity metrics to match the network’s requirements. The approach performs well with an F1-score of 95.6%. However, post-processing steps are required to produce a sufficiently consistent detector dataset for the subsequent traffic simulation. The finally modeled traffic shows a good agreement of 95.1%. with upscaled probe counts and no unrealistic traffic jams, teleports, or collisions in the simulation. We conclude that probe counts can lead to consistent traffic simulations and, especially with increasing and consistent penetration rates in the future, help to accurately model large-scale microscopic traffic simulations.
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Exploring the Moon and Mars are crucial steps in advancing space exploration. Numerous missions aim to land and research in various lunar locations, some of which possess challenging surfaces with unchanging features. Some of these areas are cataloged as lunar light plains. Their
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Exploring the Moon and Mars are crucial steps in advancing space exploration. Numerous missions aim to land and research in various lunar locations, some of which possess challenging surfaces with unchanging features. Some of these areas are cataloged as lunar light plains. Their main characteristics are that they are almost featureless and reflect more light than other lunar surfaces. This poses a challenge during navigation and landing. This paper compares traditional feature matching techniques, specifically scale-invariant feature transform and the oriented FAST and rotated BRIEF, and novel machine learning approaches for dense feature matching in challenging, unstructured scenarios, focusing on lunar light plains. Traditional feature detection methods often need help in environments characterized by uniform terrain and unique lighting conditions, where unique, distinguishable features are rare. Our study addresses these challenges and underscores the robustness of machine learning. The methodology involves an experimental analysis using images that mimic lunar-like landscapes, representing these light plains, to generate and compare feature maps derived from traditional and learning-based methods. These maps are evaluated based on their density and accuracy, which are critical for effective structure-from-motion reconstruction commonly utilized in navigation for landing. The results demonstrate that machine learning techniques enhance feature detection and matching, providing more intricate representations of environments with sparse features. This improvement indicates a significant potential for machine learning to boost hazard detection and avoidance in space exploration and other complex applications.
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This study addresses the challenge of recycling adhesive bonds, as their disassembly is irreversible and damages the substrates. It explores the use of thermally expandable particles (TEPs), which, when heated, expand and weaken the bond. The magnetization of TEPs allows us to control
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This study addresses the challenge of recycling adhesive bonds, as their disassembly is irreversible and damages the substrates. It explores the use of thermally expandable particles (TEPs), which, when heated, expand and weaken the bond. The magnetization of TEPs allows us to control their distribution using a magnetic field. The work aims to obtain magnetized TEPs, study their influence on resin curing, mechanical performance, and durability, test their mobility in graded bonds, and analyze the temperature-induced debonding process. TEPs are characterized using various techniques, including differential scanning calorimetry, nuclear magnetic resonance, and scanning electron microscopy. Additionally, the impact of 25 wt.% TEPs on epoxy resin curing is examined using the Kamal model. Adhesion and disassembly assessments were conducted through tensile shear tests using single-lap-joint specimens, while the bond durability was determined via wedge testing. It was found that magnetization reduces the debonding time, though it decreases shear strength while increasing bond durability. The crack formation energy is higher with magnetic TEPs, and total crack length is lower in long-term wedge tests. Once debonded, the substrates are sanded and reused as raw material.
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MBRs (Membrane bioreactors) have been increasingly employed for municipal and industrial wastewater treatment in the last decades for their small footprint and excellent effluent quality. However, microorganisms are often detected in the permeates of microfiltration (MF) membranes even with small pore sizes. Coliform
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MBRs (Membrane bioreactors) have been increasingly employed for municipal and industrial wastewater treatment in the last decades for their small footprint and excellent effluent quality. However, microorganisms are often detected in the permeates of microfiltration (MF) membranes even with small pore sizes. Coliform bacteria are known for indicating the potential presence of pathogenic bacteria that cause infectious disease such as bacteremia, respiratory tract infections, and urinary tract infections. Thus, the retention of coliform bacteria by membrane processes is important when the membrane process is utilized in water reclamation. In this study, a microbial community of coliform bacteria in the permeates of MF membranes with different pore sizes (0.2, 0.4, and 0.8 µm) was identified. The results showed that the dominant coliform bacteria changed from Enterobacter spp. and Citrobacter spp. in the activated sludge to Enterobacter spp. and Klebsiella spp. in the permeate of MF membranes, while some pieces of membranes showed complete retention. The bacterial regrowth on the surface of the piping system on the permeate side could be a significant factor contributing to the frequent and exclusive detection of Enterobacter spp. and Klebsiella spp. in the case of membranes with small pore size (0.2 and 0.4 µm) after a long continuous filtration time. To indicate the public health-related risk of treated wastewater by MF, Escherichia coli may not be a suitable indicator species because E. coli is relatively retentive in MF compared to other coliforms.
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The charge carrier formation and transport in the pristine polymers as well as in the polymer–fullerene blend is still a hot topic of discussion for the scientific community. In the present work, the carrier generation in some prominent organic molecules has been studied
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The charge carrier formation and transport in the pristine polymers as well as in the polymer–fullerene blend is still a hot topic of discussion for the scientific community. In the present work, the carrier generation in some prominent organic molecules has been studied through ultrafast transient absorption spectroscopy. The identification of the exciton and polaron lifetimes of these polymers has led to device performance-related understanding. In the Energy Gap Law, the slope of the linear fit gradient (γ) of lifetimes vs. bandgap are subjected to the geometrical rearrangements experienced by the polymers during the non-radiative decay from the excited state to the ground state. The value of gradient (γ) for excitons and polarons is found to be −1.1 eV−1 and 1.14 eV−1, respectively. It suggests that the exciton decay to the ground state is likely to involve a high distortion in polymer equilibrium geometry. This observation supports the basis of Stokes shift found in the conjugated polymers due to the high disorder. It provides the possible reasons for the substantial variation in the exciton lifetime. As the bandgap becomes larger, exciton decay rate tends to reduce due to the weak attraction between the holes in the HUMO and electron in the LUMO. The precise inverse action is observed for the polymer–fullerene blend, as the decay of polaron tends to increase as the bandgap of polymer increases.
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Agnieszka Budka-Chrzęszczyk, Agnieszka Szlagatys-Sidorkiewicz, Ewa Bień, Ninela Irga-Jaworska, Anna Borkowska, Małgorzata Anna Krawczyk, Katarzyna Popińska, Hanna Romanowska, Ewa Toporowska-Kowalska, Magdalena Świder, Jan Styczyński, Tomasz Szczepański and Janusz Książyk
“Managing Undernutrition in Pediatric Oncology” is a collaborative consensus statement of the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology. The early identification and accurate management of malnutrition in children receiving anticancer treatment are crucial
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“Managing Undernutrition in Pediatric Oncology” is a collaborative consensus statement of the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology. The early identification and accurate management of malnutrition in children receiving anticancer treatment are crucial components to integrate into comprehensive medical care. Given the scarcity of high-quality literature on this topic, a consensus statement process was chosen over other approaches, such as guidelines, to provide comprehensive recommendations. Nevertheless, an extensive literature review using the PubMed database was conducted. The following terms, namely pediatric, childhood, cancer, pediatric oncology, malnutrition, undernutrition, refeeding syndrome, nutritional support, and nutrition, were used. The consensus was reached through the Delphi method. Comprehensive recommendations aim to identify malnutrition early in children with cancer and optimize nutritional interventions in this group. The statement underscores the importance of baseline and ongoing assessments of nutritional status and the identification of the risk factors for malnutrition development, and it presents tools that can be used to achieve these goals. This consensus statement establishes a standardized approach to nutritional support, aiming to optimize outcomes in pediatric cancer patients.
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KR (Kanbara Reaction) desulfurization slag is a solid waste that is not sufficiently utilized. This is because the KR desulfurization slag contains 1–2.5% sulfur, which is directly used in steel smelting to increase the sulfur content in molten steel. Therefore, the possibility of
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KR (Kanbara Reaction) desulfurization slag is a solid waste that is not sufficiently utilized. This is because the KR desulfurization slag contains 1–2.5% sulfur, which is directly used in steel smelting to increase the sulfur content in molten steel. Therefore, the possibility of oxidation desulfurization of KR desulfurization slag was studied in this study. Experiments were conducted to investigate the possibility of removing sulfur from used KR (Kambara Reaction) slag with oxidation. The KR slag samples were treated with oxidative desulfurization in the oxygen partial pressure range of 0.05 bar–1.00 bar, with a gas flow rate ranging from 2 L min−1 to 6 L min−1, and at a temperature of 1420 °C. X-ray diffraction (XRD), an infrared carbon sulfur analyzer, and scanning electron microscopy–energy dispersive X-ray spectrometry (SEM–EDS) analysis were used to reveal the oxidative desulfurization mechanism of KR desulfurization slag. At low oxygen pressure ( < 0.20 bar), the desulfurization rate of slag oxidized for 120 min increased with the increase in oxygen partial pressure. At high oxygen pressure ( ≥ 0.20 bar), the desulfurization rate of slag samples did not change with the change in oxygen partial pressure, and the desulfurization rate was higher than 93.5%. At low oxygen pressure ( < 0.20 bar), the residual sulfur in the slag after oxidation still existed in the slag as the CaS phase. At high oxygen pressure ( ≥ 0.20 bar), the residual sulfur in the slag oxidized from the CaS phase to the 11CaO·7Al2O3·CaS phase in the slag. The sulfur removal rate was directly correlated with the slag surface area and the flow rate of the reaction gas, and it increased with an increase in both surface area and gas flow rate.
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Cyanobacteria, photoautotrophic Gram-negative bacteria, play a crucial role in aquatic and terrestrial environments, contributing significantly to fundamental ecological processes and displaying potential for various biotechnological applications. It is, therefore, critical to identify viable strains for aquaculture and establish accurate culture parameters to ensure
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Cyanobacteria, photoautotrophic Gram-negative bacteria, play a crucial role in aquatic and terrestrial environments, contributing significantly to fundamental ecological processes and displaying potential for various biotechnological applications. It is, therefore, critical to identify viable strains for aquaculture and establish accurate culture parameters to ensure an extensive biomass supply for biotechnology purposes. This study aims to establish optimal laboratory batch culture conditions for Nostoc 136, sourced from Alga2O, Coimbra, Portugal. Preliminary investigations were conducted to identify the optimal culture parameters and to perform biomass analysis, including protein and pigment content. The highest growth was achieved with an initial inoculum concentration of 1 g.L−1, using modified BG11 supplemented with nitrogen, resulting in a Specific Growth Rate (SGR) of 0.232 ± 0.017 μ.day−1. When exposed to white, red, and blue LED light, the most favourable growth occurred under a combination of white and red LED light exhibiting an SGR of 0.142 ± 0.020 μ.day−1. The protein content was determined to be 10.80 ± 2.09%. Regarding the pigments, phycocyanin reached a concentration of 200.29 ± 30.07 µg.mL−1, phycoerythrin 148.29 ± 26.74 µg.mL−1, and allophycocyanin 10.69 ± 6.07 µg.mL−1. This study underscores the influence of light and nutrient supplementation on the growth of the Nostoc biomass.
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Currently, Mediterranean forests are experiencing the deleterious effects of global warming, which mainly include increased temperatures and decreased precipitation in the region. Relict Abies pinsapo fir forests, endemic in the southern Iberian Peninsula, are especially sensitive to these recent environmental disturbances, and identifying
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Currently, Mediterranean forests are experiencing the deleterious effects of global warming, which mainly include increased temperatures and decreased precipitation in the region. Relict Abies pinsapo fir forests, endemic in the southern Iberian Peninsula, are especially sensitive to these recent environmental disturbances, and identifying the genes involved in the response of this endangered tree species to climate-driven stresses is of paramount importance for mitigating their effects. Genomic resources for A. pinsapo allow for the analysis of candidate genes reacting to warming and aridity in their natural habitats. Several members of the complex gene families encoding late embryogenesis abundant proteins (LEAs) and heat shock proteins (HSPs) have been found to exhibit differential expression patterns between wet and dry seasons when samples from distinct geographical locations and dissimilar exposures to the effects of climate change were analyzed. The observed changes were more perceptible in the roots of trees, particularly in declining forests distributed at lower altitudes in the more vulnerable mountains. These findings align with previous studies and lay the groundwork for further research on the molecular level. Molecular and genomic approaches offer valuable insights for mitigating climate stress and safeguarding this endangered conifer.
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This article addresses the challenges of measuring the 3D architecture traits, such as height and volume, of fruit tree canopies, constituting information that is essential for assessing tree growth and informing orchard management. The traditional methods are time-consuming, prompting the need for efficient
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This article addresses the challenges of measuring the 3D architecture traits, such as height and volume, of fruit tree canopies, constituting information that is essential for assessing tree growth and informing orchard management. The traditional methods are time-consuming, prompting the need for efficient alternatives. Recent advancements in unmanned aerial vehicle (UAV) technology, particularly using Light Detection and Ranging (LiDAR) and RGB cameras, have emerged as promising solutions. LiDAR offers precise 3D data but is costly and computationally intensive. RGB and photogrammetry techniques like Structure from Motion and Multi-View Stereo (SfM-MVS) can be a cost-effective alternative to LiDAR, but the computational demands still exist. This paper introduces an innovative approach using UAV-based single-lens stereoscopic photography to overcome these limitations. This method utilizes color variations in canopies and a dual-image-input network to generate a detailed canopy height map (CHM). Additionally, a block structure similarity method is presented to enhance height estimation accuracy in single-lens UAV photography. As a result, the average rates of growth in canopy height (CH), canopy volume (CV), canopy width (CW), and canopy project area (CPA) were 3.296%, 9.067%, 2.772%, and 5.541%, respectively. The r2 values of CH, CV, CW, and CPA were 0.9039, 0.9081, 0.9228, and 0.9303, respectively. In addition, compared to the commonly used SFM-MVS approach, the proposed method reduces the time cost of canopy reconstruction by 95.2% and of the cost of images needed for canopy reconstruction by 88.2%. This approach allows growers and researchers to utilize UAV-based approaches in actual orchard environments without incurring high computation costs.
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Small-pore zeolites catalyze the methanol-to-olefins (MTO) reaction via a dual-cycle mechanism, encompassing both olefin- and aromatic-based cycles. Zeolite topology is crucial in determining both the catalytic pathway and the product selectivity of the MTO reaction. Herein, we investigate the mechanistic influence of MCM-35
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Small-pore zeolites catalyze the methanol-to-olefins (MTO) reaction via a dual-cycle mechanism, encompassing both olefin- and aromatic-based cycles. Zeolite topology is crucial in determining both the catalytic pathway and the product selectivity of the MTO reaction. Herein, we investigate the mechanistic influence of MCM-35 zeolite on the MTO process. The structural properties of the as-synthesized MCM-35 catalyst, including its confined cages (6.19 Å), were characterized, confirming them as the catalytic centers. Then, the MTO reactions were systematically performed and investigated over a MCM-35 catalyst. Feeding pure methanol to the reactor yielded minimal MTO activity despite the formation of some aromatic species within the zeolite. The results suggest that the aromatic-based cycle is entirely suppressed in MCM-35, preventing the simultaneous occurrence of the olefin-based cycle. However, cofeeding a small amount of propene in methanol can obviously enhance the methanol conversion under the same studied reaction conditions. Thus, the exclusive operation of the olefin-based cycle in the MTO reaction, independent of the aromatic-based cycle, was demonstrated in MCM-35 zeolite.
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Regeneration agents play a critical role in modifying the mechanical properties and durability of RAP asphalt mixtures. This paper aimed to develop a castor oil-based asphalt regeneration agent. The effects of this regeneration agent on the pavement performance of laboratory-aged asphalt and an
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Regeneration agents play a critical role in modifying the mechanical properties and durability of RAP asphalt mixtures. This paper aimed to develop a castor oil-based asphalt regeneration agent. The effects of this regeneration agent on the pavement performance of laboratory-aged asphalt and an RAP asphalt mixture were comparatively studied by a series of laboratory tests. For the developed castor oil-based asphalt regeneration agent, the weight ratio of the castor oil to dibutyl phthalate was determined as 1:4. Moreover, the regeneration effectiveness of the castor oil-based regeneration agent was tested on three laboratory-aged asphalt binders and an RAP asphalt binder; the penetration, softening point and ductility of the RAP asphalt binder recovered to 83 dmm, 50.3 °C, and more than 100 cm, respectively. The optimum content of the regeneration agent was 5% by the weight of the aged asphalt binder. Furthermore, the castor oil-based regeneration agent could effectively restore the pavement performance of an RAP asphalt mixture. In this study, the RAP percentage can reach up to 60% by the weight of the HMA mixture using the castor oil-based asphalt regeneration agent according to the Chinese specification.
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Md Abu Sufian, Wahiba Hamzi, Boumediene Hamzi, A. S. M. Sharifuzzaman Sagar, Mustafizur Rahman, Jayasree Varadarajan, Mahesh Hanumanthu and Md Abul Kalam Azad
Early pregnancy loss (EPL) is a prevalent health concern with significant implications globally for gestational health. This research leverages machine learning to enhance the prediction of EPL and to differentiate between typical pregnancies and those at elevated risk during the initial trimester. We
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Early pregnancy loss (EPL) is a prevalent health concern with significant implications globally for gestational health. This research leverages machine learning to enhance the prediction of EPL and to differentiate between typical pregnancies and those at elevated risk during the initial trimester. We employed different machine learning methodologies, from conventional models to more advanced ones such as deep learning and multilayer perceptron models. Results from both classical and advanced machine learning models were evaluated using confusion matrices, cross-validation techniques, and analysis of feature significance to obtain correct decisions among algorithmic strategies on early pregnancy loss and the vitamin D serum connection in gestational health. The results demonstrated that machine learning is a powerful tool for accurately predicting EPL, with advanced models such as deep learning and multilayer perceptron outperforming classical ones. Linear discriminant analysis and quadratic discriminant analysis algorithms were shown to have 98 % accuracy in predicting pregnancy loss outcomes. Key determinants of EPL were identified, including levels of maternal serum vitamin D. In addition, prior pregnancy outcomes and maternal age are crucial factors in gestational health. This study’s findings highlight the potential of machine learning in enhancing predictions related to EPL that can contribute to improved gestational health outcomes for mothers and infants.
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Background and Objectives: Faricimab is a vascular endothelial growth factor A and angiopoietin-2 bispecific antibody. It is a novel therapeutic approach distinct from previous anti-vascular endothelial growth factor agents. This study aimed to evaluate the efficacy of switching from aflibercept to faricimab
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Background and Objectives: Faricimab is a vascular endothelial growth factor A and angiopoietin-2 bispecific antibody. It is a novel therapeutic approach distinct from previous anti-vascular endothelial growth factor agents. This study aimed to evaluate the efficacy of switching from aflibercept to faricimab in the treatment of diabetic macular edema (DME) refractory to aflibercept, with a specific focus on the resolution of macular edema. Materials and Methods: The medical records of 29 eyes of 21 patients with DME that were refractory to intravitreal injections of aflibercept (IVAs) and who had completed the clinical follow-up of at least four intravitreal injections of faricimab (IVFs) were reviewed. The central retinal thickness (CRT), best-corrected visual acuity (BCVA), and the mean period (weeks) until the next injection were measured after the second-to-last IVA, first-to-last IVA, last IVA, and first to fourth IVFs following the transition to IVF. Results: The mean time from the first IVF to the assessment of effectiveness was significantly shorter than the time to the last IVA; however, no significant difference was found in the time from the second, third, and fourth IVFs to the assessment. The mean CRTs after the first and second IVFs were not significantly different from the CRT after the last IVA, but the mean CRT after the third and fourth IVFs was significantly thinner than that after the last IVA (p = 0.0025 and p = 0.0076, respectively). The mean BCVAs after the third and fourth IVFs significantly improved compared with that after the last IVA (p = 0.0050 and p = 0.0052, respectively). Conclusions: When switching the treatment to IVF for eyes with IVA-resistant DME, better treatment outcomes are achieved if IVF is performed three or more times.
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Giovanni Messina, Antonietta Monda, Antonietta Messina, Girolamo Di Maio, Vincenzo Monda, Pierpaolo Limone, Anna Dipace, Marcellino Monda, Rita Polito and Fiorenzo Moscatelli
Non-invasive brain stimulation (NIBS) approaches have seen a rise in utilization in both clinical and basic neuroscience in recent years. Here, we concentrate on the two methods that have received the greatest research: transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation
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Non-invasive brain stimulation (NIBS) approaches have seen a rise in utilization in both clinical and basic neuroscience in recent years. Here, we concentrate on the two methods that have received the greatest research: transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS). Both approaches have yielded pertinent data regarding the cortical excitability in subjects in good health as well as pertinent advancements in the management of various clinical disorders. NIBS is a helpful method for comprehending the cortical control of the ANS. Previous research has shown that there are notable changes in muscular sympathetic nerve activity when the motor cortex is modulated. Furthermore, in NIBS investigations, the ANS has been employed more frequently as an outcome measure to comprehend the overall impacts of these methods, including their safety profile. Though there is ample proof that brain stimulation has autonomic effects on animals, new research on the connection between NIBS and the ANS has produced contradictory findings. In order to better understand NIBS processes and ANS function, it is crucial to take into account the reciprocal relationship that exists between central modulation and ANS function.
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Hesperidin is a highly bioactive natural flavonoid whose role in ecological interactions is poorly known. In particular, the effects of hesperidin on herbivores are rarely reported. Flavonoids have been considered as prospective biopesticides; therefore, the aim of the present study was to examine
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Hesperidin is a highly bioactive natural flavonoid whose role in ecological interactions is poorly known. In particular, the effects of hesperidin on herbivores are rarely reported. Flavonoids have been considered as prospective biopesticides; therefore, the aim of the present study was to examine the influence of hesperidin on the host plant selection behavior of three aphid (Hemiptera: Aphididae) species: Acyrthosiphon pisum Harrris, Rhopalosiphum padi (L.), and Myzus persicae (Sulz.). The aphid host plants were treated with 0.1% and 0.5% ethanolic solutions of hesperidin. Aphid probing behavior in the no-choice experiment was monitored using electropenetrography and aphid settling on plants in the choice experiment was recorded. The results demonstrated that hesperidin can be applied as a pre-ingestive, ingestive, and post-ingestive deterrent against A. pisum, as an ingestive deterrent against R. padi, and as a post-ingestive deterrent against M. persicae using the relatively low 0.1% concentration. While in A. pisum the deterrent effects of hesperidin were manifested as early as during aphid probing in peripheral plant tissues, in M. persicae, the avoidance of plants was probably the consequence of consuming the hesperidin-containing phloem sap.
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The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper,
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The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper, a novel golden jackal optimization algorithm (SCMGJO) combining sine–cosine and Cauchy mutation is proposed. On one hand, tent mapping reverse learning is introduced in population initialization, and sine and cosine strategies are introduced in the update of prey positions, which enhances the global exploration ability of the algorithm. On the other hand, the introduction of Cauchy mutation for perturbation and update of the optimal solution effectively improves the algorithm’s ability to obtain the optimal solution. Through the optimization experiment of 23 benchmark test functions, the results show that the SCMGJO algorithm performs well in convergence speed and accuracy. In addition, the stretching/compression spring design problem, three-bar truss design problem, and unmanned aerial vehicle path planning problem are introduced for verification. The experimental results prove that the SCMGJO algorithm has superior performance compared with other intelligent optimization algorithms and verify its application ability in engineering applications.
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Isaac Kwesi Nooni, Faustin Katchele Ogou, Daniel Fiifi Tawiah Hagan, Abdoul Aziz Saidou Chaibou, Nana Agyemang Prempeh, Francis Mawuli Nakoty, Zhongfang Jin and Jiao Lu
Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production.
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Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions.
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While ex vivo confocal laser scanning microscopy has previously demonstrated its utility in most common skin diseases, its use in the assessment of dermatological entities with lower incidence remains unexplored in most cases. We therefore aimed to evaluate the diagnostic efficacy of some
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While ex vivo confocal laser scanning microscopy has previously demonstrated its utility in most common skin diseases, its use in the assessment of dermatological entities with lower incidence remains unexplored in most cases. We therefore aimed to evaluate the diagnostic efficacy of some rare skin tumors as well as a few inflammatory skin diseases, that have not yet been studied in ex vivo confocal laser scanning microscopy. A total of 50 tissue samples comprising 10 healthy controls, 10 basal cell carcinoma, 10 squamous cell carcinoma, and 20 rare skin conditions were imaged using the newest generation ex vivo confocal microscopy (Vivascope 2500 M-G4, Vivascope GmbH, Munich, Germany). Three blinded investigators were asked to identify characteristic features of rare skin disorders and distinguish them from more common skin diseases in the ex vivo confocal microscopy images. Our findings present the capability of ex vivo confocal microscopy to display distinctive morphologic patterns in common and rare skin diseases. As might be expected, we found a strong correlation between imaging experience and diagnostic accuracy. While the imaging inexperienced dermatohistopathologist reached 60% concordance, the imaging-trained dermatologist obtained 88% agreement with dermatohistopathology. The imaging-trained dermatohistopathologist achieved concordance up to 92% with gold-standard dermatohistopathology. This study highlights the potential of ex vivo confocal laser scanning microscopy as a promising adjunct to conventional dermatohistopathology for the early and precise identification of rare dermatological disorders.
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