bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physiologically based pharmacokinetic modeling and simulation of topiramate in populations with renal and hepatic impairment and considerations for drug–drug interactions
Authors: Chen Shuqing , Shen Chaozhuang , Tian Yuchen , Peng Yuhe , Hu Jing , Xie Haitang , Yin Ping 
Published: December 2024

AbstractTopiramate (TPM) is a broad‐spectrum antiepileptic drug (AED) commonly prescribed for approved and off‐label uses. Routine monitoring is suggested for clinical usage of TPM in special population due to its broad side effect profile. Therefore, it is crucial to further explore its pharmacokinetic characteristics. Physio‐chemical properties of TPM were initially determined from online database and further optimized while establishing the PBPK model for healthy adults using the PK‐Sim software. The model was then extrapolated to patients with renal impairment and patients who were hepatically impaired. A drug–drug interaction (DDI) model was also built to simulate plasma TPM concentrations while concomitantly used with carbamazepine (CBZ). The goodness‐of‐fit method and average fold error (AFE) method were used to compare the differences between predicted and observed values to assess the accuracy of the PBPK model. Almost all of the predicted concentration fell within twofold error range of corresponding observed concentrations. The AFE ratio of predicted to observed values of Cmax and AUC0‐inf was all within 0.5 and 2. It is recommended that the doses be reduced to 70%, 50%, and 40% of the healthy adult dose for the chronic kidney disease (CKD) stage 3, stage 4, and stage 5 patients, respectively, and reduced to ~70%, and 35% for the Child–Pugh‐B, and Child–Pugh C scored patient with hepatic impairment, respectively. If TPM is co‐administered with CBZ, increasing TPM doses to 150%–175% of the monotherapy dose is recommended according to model simulation.
Mapping oil palm plantations and their implications on forest and great ape habitat loss in Central Africa
Authors: Ozigis Mohammed S. , Wich Serge , Descals Adrià , Szantoi Zoltan , Meijaard Erik 
Published: December 2024

AbstractOil palm (Elaeis guineensis) cultivation in Central Africa (CA) has become important because of the increased global demand for vegetable oils. The region is highly suitable for the cultivation of oil palm and this increases pressure on forest biodiversity in the region. Accurate maps are therefore needed to understand trends in oil palm expansion for landscape‐level planning, conservation management of endangered species, such as great apes, biodiversity appraisal and supply of ecosystem services. In this study, we demonstrate the utility of a U‐Net Deep Learning Model and product fusion for mapping the extent of oil palm plantations for six countries within CA, including Cameroon, Central African Republic, Democratic Republic of Congo (DRC), Equatorial Guinea, Gabon and Republic of Congo. Sentinel‐1 and Sentinel‐2 data for the year 2021 were classified using a U‐Net model. Overall classification accuracy for the final oil palm layer was 96.4 ± 1.1%. Producer Accuracy (PA) and User Accuracy (UA) for the industrial and smallholder oil palm classes were 91.6 ± 1.7% and 95.0 ± 1.3%, 67.7 ± 2.8% and 70.0 ± 2.8%. Post classification assessment of the transition from tropical moist forest (TMF) cover to oil palm within the six CA countries suggests that over 1000 Square Kilometer (km2) of forest within great ape ranges had so far been converted to oil palm between 2000 and 2021. Results from this study indicate a more extensive cover of smallholder oil palm than previously reported for the region. Our results also indicate that expansion of other agricultural activities may be an important driver of deforestation as nearly 170 000 km2 of forest loss was recorded within the IUCN ranges of the African great apes between 2000 and 2021. Output from this study represents the first oil palm map for the CA, with specific emphasis on the impact of its expansion on great ape ranges. This presents a dependable baseline through which future actions can be formulated in addressing conservation needs for the African Great Apes within the region.
Nickel (II) and Copper (II) Schiff Base Derivatives: Design, Characterization, Biological Activity
Authors: El‐Lateef Hany M. Abd , Khalaf Mai M. , Gouda Mohamed , Almarri Mohammed N. , Abdelhamid Antar A. , Al‐Ghamdi Saleh , Amer Amer A. , Abdou Aly 
Published: December 2024

AbstractThis work presents the designing and characterization of two novel metal complexes derived from a Schiff base, N,N’‐ethane‐1,2‐diylbis[1‐(2‐chloroquinolin‐3‐yl)methanimine] (EBCQ), coordinated with Ni (II) (NiEBCQ), and Cu (II) (CuEBCQ). Structures of the metal complex derivatives were proposed utilizing a variety of analytical methods having elemental analysis, ultraviolet‐visible spectroscopy, mass spectroscopy, infrared spectroscopy, magnetic properties, conductivity measurement, and thermal analysis. The obtained data revealed octahedral geometries for both NiEBCQ and CuEBCQ complexes, denoted as [Ni(EBCQ)(H2O)2(Cl)2] and [Cu(EBCQ)(H2O)2(Cl)2], respectively. Density functional theory computations were employed for confirming the molecular structures and exploring quantum chemical parameters of both EBCQ and its metal complex derivatives. The anti‐inflammatory results reveal that the EBCQ ligand and its metal complexes, NiEBCQ, and CuEBCQ, exhibit varying degrees of inhibition, with CuEBCQ showing the highest potency. CuEBCQ achieved 89.80% inhibition at 300 µM, with an IC50 value of 86.38 µM, indicating its superior anti‐inflammatory activity compared to NiEBCQ (IC50 of 92.33 µM) and the ligand EBCQ (IC50 of 169.07 µM). In the antioxidant assays, the CuEBCQ complex again showed the most pronounced activity, achieving an IC50 of 74.16 µM, outperforming both NiEBCQ (IC50 of 89.06 µM) and the EBCQ ligand (IC50 of 101.58 µM). The antibacterial tests confirmed the metal complexes' superiority, particularly CuEBCQ, which displayed excellent inhibition against Bacillus cereus compared to the ligand. Molecular docking studies targeting specific proteins (5IKT for human cyclo‐oxygenase‐2, and 5IJT for human peroxiredoxin 2) were performed to assess the binding affinities and interactions of EBCQ and its metal complex derivatives. The results propose promising potential for the application of EBCQ and its metal complexes as novel therapeutic agents with diverse biological activities. Finally, antibacterial effectiveness of the ligand and its complexes were monitored opposed to several Gram‐positive and Gram‐negative bacteria.
A Sustainable Nanoporous Adsorbent for Reducing Amoxicillin in Pharmaceutical Wastewater: Magnetic Tea Waste Hydrochar
Authors: Shahavi Mohammad Hassan , Akbari Mohammad , Ayrilmis Nadir , Dorieh Ali 
Published: December 2024

AbstractIn this research, a sustainable approach to augmenting nanoporous and high‐capacity adsorbents widely employed in amoxicillin (AMX) removal from pharmaceutical wastewater was introduced in this study. Iron oxide particles were incorporated into tea factory waste material under microwave hydrothermal carbonization, aiming to produce a green and enhanced magnetic adsorbent material. The chemical structure, morphology, and surface charge of the magnetic tea waste hydrochar (MTWHC) were characterized. The results show that the synthesized nanoporous magnetic tea waste hydrochar has an average pore diameter of 1.90 nm. The value of the SBET was measured at about 30.22 cm2/g for the MTWHC. Furthermore, the adsorbent showed a remarkable maximum removal efficiency of 93.8%, highlighting its significant potential for implementation in wastewater treatment. The Freundlich isotherm was a good fit to the experimental data, indicating that the multilayer adsorption mechanism is responsible for its compatibility and an adsorption capacity of 3.2047 mg/g was measured using this method. This approach not only introduces an environmentally friendly modification to a widely used material but also highlights the potential of magnetic tea waste hydrochar as an innovative additive in composite matrices. This research is an important contribution to the ongoing development of advanced, sustainable composites with a lower environmental impact.
A Constant Filgotinib Delivery Adhesive Platform Based on Polyethylene Glycol (PEG) Hydrogel for Accelerating Wound Healing via Restoring Macrophage Mitochondrial Homeostasis
Authors: Xie Jian , Huang Yiqian , Hu Xiaofeng , Wu Xiaowei , Luo Xi , Wei Pengfei , Jing Wei , Zhao Bo , Su Jiansheng 
Published: December 2024

AbstractSkin wound healing is often hindered by disrupted mitochondrial homeostasis and imbalanced macrophage glucose metabolism, posing a critical challenge to improve patient outcomes. Developing new wound healing dressings capable of effectively regulating macrophage immune‐metabolic functions remains a pressing issue. Herein, a highly adhesive polyethylene glycol (PEG) hydrogel loaded with the Janus kinase 1 (JAK1) inhibitor Filgotinib (Fil@GEL) is prepared to modulate macrophage metabolic reprogramming and restore normal mitochondrial function. Fil@GEL exhibits superior shear adhesion strength compared to commercially available tissue binder products, providing adequate adhesion for skin wound closure. Additionally, Fil@GEL exhibits the capacity to inhibit M1‐type macrophage polarization by suppressing the JAK‐STAT signaling pathway, and induces a metabolic shift in macrophages from aerobic glycolysis to oxidative phosphorylation, which results in decreased lactate production, reduced reactive oxygen species (ROS) levels, and the restoration of mitochondrial homeostasis. The Fil@GEL hydrogel significantly accelerates skin wound healing compared to the control group, reduces intra‐wound inflammation, and promotes collagen regeneration. In summary, this highly adhesive hydrogel demonstrates exceptional performance as a drug carrier, exerting immunometabolic modulation through firm wound adhesion and sustained filgotinib release, underscoring its substantial potential as an effective wound dressing.
Rational Design of Atomically Immobilized Fe‐N4 Sites via Acid‐Amine Chemistry: Leveraging Metal Ionic Assistance for Precise Morphology Control
Authors: Sathyaseelan Arunprasath , Elumalai Vijayakumar , Perumalsamy Muthukumar , Nardekar Swapnil Shital , Raaju Sundhar Arul Saravanan , Karthikeyan S. C. , Yoo Dong Jin , Kim Sang‐Jae 
Published: December 2024

ABSTRACTTailoring atomically dispersed single‐atom catalyst (Fe‐SAC) holding well‐defined coordination structure (Fe‐N4) along with precise control over morphology is a critical challenge. Herein, we propose a novel acid‐amine coupling reaction between metal‐chelated ionic liquid ([1‐(3‐aminopropyl) 3‐methylimidazolium tetrachloroferrate(III)] [APIM]+[FeCl4]−) and carboxylic groups of carbon allotropes (C = GO, CNT, CNF, and vX‐72) to precisely immobilize Fe‐Nx sites. Out of designed single‐atom catalyst (IL‐Fe‐SAC‐C), Fe‐N4 on graphene (IL‐Fe‐SAC‐Gr) delivered superior oxygen reduction reaction (ORR) activity by holding higher halfwave potential of 0.882 V versus RHE in 1.0 M KOH akin to Pt/C (0.878 V vs. RHE) and surpassing recently reported M–N–C catalysts with superior ethanol tolerance. Thanks to higher graphitization degree, enhanced surface characteristics, and richness in high‐density Fe‐N4 sites of IL‐Fe‐SAC‐Gr confirmed by XPS, X‐ray absorption spectroscopy (XAS), and HAADF analysis. The IL‐Fe‐SAC‐Gr catalyst‐coated cathode on testing in flexible direct ethanol fuel cells (f‐DEFC) delivered higher peak power density of 18 mW cm−2 by outperforming Pt/C‐based cathode by 3.5 times as a result of excellent ethanol tolerance. Further, the developed f‐DEFC successfully powered the Internet of Things (IoT)‐based health monitoring system. This method demonstrates novel strategy to tailor high‐performance single‐atom (Fe‐SAC‐C) sites on desired morphologies to meet specific application requirements with feasibility and versatility.
Storage Availability Prediction in Unmanned Aerial Vehicle Swarms Using Agent‐Based Simulation
Authors: Tang Hui , Wang Lizhi , Sun Yaning , Wang Xiaohong , Ma Tielin 
Published: December 2024

ABSTRACTIn practice, when an unmanned aerial vehicle (UAV) swarm is not executing a mission, its UAVs will be stored as inventory. To ensure that the UAV swarm can be quickly deployed when needed, it is necessary to assess and predict its storage state. Due to the flexible configuration of UAV swarms and the complex factors that affect them during storage, existing storage state indicators and prediction methods cannot meet the requirements of UAV swarm storage. In order to address these issues, a UAV swarm storage availability prediction method based on agent‐based simulation (ABS) is proposed. Considering the degradation of health status, maintenance, support, and other factors during the storage period of UAVs, a UAV swarm storage state measurement metric that covers the storage cycle is proposed. Based on this metric, a UAV swarm storage availability model is established. Then, considering the dynamic adaptability and internal complex interactions of UAV swarms, the ABS is used to realize the modeling and prediction of UAV swarm storage availability. Finally, a UAV swarm rescue case is used to illustrate its scientific validity and accuracy. Therefore, this study offers a scientific and efficient method for measuring the availability of UAV swarms, providing valuable insights for rapid response and decision‐making during the transition from storage to deployment. It also presents a viable approach for availability modeling and prediction in complex, emergent swarm systems.
Sensemaking as a goal of science education, abduction as a process of scientific sensemaking
Authors: Oh Phil Seok , Ha Heesoo 
Published: December 2024

AbstractCurrent science education reform efforts have identified sensemaking as an important goal of science education, and science education researchers have studied what constitutes the sensemaking process in the science classroom. Because the studies of sensemaking are loosely linked to those of scientific reasoning, however, they have provided little practical insight into how students can make scientific sense, rather than any sense, of natural phenomena. Therefore, in this position paper, we discuss the close relationship between sensemaking and abduction. Sensemaking refers to a prolonged process of resolving a gap or inconsistency in current knowledge and understanding by constructing an explanation of a phenomenon. Abduction is a form of scientific reasoning to generate explanatory hypotheses about the evidence embedded in a phenomenon based on available resources. Abduction can play a crucial role in sensemaking by providing a mechanism for generating a plausible explanation of a target phenomenon and should be adapted for science teaching and learning for students' sensemaking through engagement in science practices. In particular, to develop scientific sensemaking in students, the teacher should help students identify critical evidence, provide students with critical resources, and encourage students to use the method of multiple working hypotheses, so that the students can construct scientifically sound and valid explanations of natural phenomena. It is suggested that further research explore and collect exemplary cases of science teachers effectively supporting students to achieve scientific sensemaking through abduction.
Detection and Classification of Surface Cracks Using Deep Learning Based Autoencoders in Eddy Current Testing
Authors: Fatima Barrarat , Bachir Helifa , Samir Bensaid , Karim Rayane , IbnKhaldoun Lefkaier 
Published: December 2024

AbstractIndustrial equipment subjected to rigorous conditions of high speed and pressure leads to the development of cracks on metal surfaces. These cracks reduce the service life and threaten the safety of parts, and the deeper the crack, the greater the resulting damage. Crack detection and crack depth evaluation continue to take center stage in quantitative non‐destructive testing and evaluation (NDT&E 4.0). The accuracy of the rotating uniform eddy current (RUEC) probe in achieving fast and efficient detection of surface cracks is corroborated by a comparison with previous experimental results. Next, accurate crack depth classification is achieved by building deep learning model based on a sparse autoencoder (SAE) and a multi‐layer perceptron (MLP) model. These classifiers are combined with eddy current testing (ECT) data, including the normal magnetic component Bz. As a result, evaluation metrics such as accuracy increased by up to 100% with both precision and recall scores of 1 for the deep sparse autoencoder classifier compared to MLP performance. The originality of our approach is evident in the application of deep SAE, which achieves high classification accuracy. Furthermore, the integration of our high‐resolution NDT&E RUEC probe with advanced machine learning models for depth classification is both novel and impactful. This unique combination offers a comprehensive framework for crack analysis, from precise detection to detailed characterization. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Urban farming system and food security in sub‐Saharan Africa: Analysis of the current status and challenges
Authors: Kiribou Razak , Bedadi Bobe , Dimobe Kangbéni , Ndemere Julius , Neya Tiga , Ouedraogo Valentin , Dejene Sintayehu W. 
Published: December 2024

AbstractBy 2022, 42.39% of the sub‐Saharan Africa (SSA) population was living in urban areas. This urbanization correlates with increasing poverty, unemployment, food insecurity, environmental pollution, and the prevalence of informal settlements. These challenges worsened urban food insecurity during the COVID‐19 pandemic in SSA cities. This review analyzed the role of urban farming system as a pivotal means to enhance urban food security, incorporating socioeconomic integration and environmental sustainability. The analysis is grounded in a systematic review using specific keywords, evaluating 46 articles and institutional reports related to the subject. The results revealed that 3.62% of SSA countries have implemented national urban governance and policies with minimal focus on urban farming. Rapid urbanization, urban population growth, and climate change are key factors contributing to cities' vulnerabilities to food insecurity in SSA. Predominantly characterized by horticultural practice, urban farming enhances the food supply system, nutritious security, jobs and income generation, reduces transportation costs, promotes the consumption of fresh food, and mitigates food loss in cities. Despite its importance, urban farming in SSA encounters several challenges: (i) urbanization governance and policy, (ii) knowledge and technology in urban farming, (iii) access to land and water, (iv) financing and capacity building for urban farming, and (v) environmental pollution. SSA countries need a coordinated mix of urbanization policies and technological advancements to integrate innovative urban farming methods, bolstering cities’ resilience to food insecurity. Implementing these measures could advance the achievement of sustainable development goals 2 and 11 in SSA cities.
Quantum Navier–Stokes equations for electrons in graphene
Authors: Barletti Luigi , Demeio Lucio , Nicoletti Sara 
Published: December 2024

AbstractThe Chapman–Enskog method, in combination with the quantum maximum entropy principle (QMEP), is applied to the Wigner equation in order to obtain quantum Navier–Stokes equations for electrons in graphene in the isothermal case. The derivation is based on the quantum version of the maximum entropy principle and follows the lines of Ringhofer–Degond–Méhats' theory (J. Stat. Phys. 112, 2003 and Z. Angew. Math. Mech. 90, 2010). The model obtained in this way is then semiclassically expanded up to .
Connecting the Temporal Evolution of the Turbulence Interface to the Entrainment and Detrainment in a Turbulent Plane Jet
Authors: Xie Yuanliang , Nagata Koji , Zhou Yi 
Published: December 2024

AbstractDirect numerical simulation is performed to investigate the connection between the evolution of the turbulent/non-turbulent interface (TNTI) and the entrainment and detrainment process in a temporally evolving turbulent plane jet with Taylor Reynolds number of about $$Re_\lambda \approx 72$$

R

e
λ

≈
72

. For an accurate calculation of the surface area of the turbulent interface, a novel algorithm is used. On average, the stretching term and the curvature/propagation term counterbalance each other, maintaining a constant surface area of the TNTI. We show that regardless of the entrainment or detrainment process, the stretching term always contributes to the production of surface area. The curvature/propagation term contributes to the destruction of surface area in the entrainment process. In contrast, the curvature/propagation term is related to the production of surface area in the detrainment process.
Interfacial Morphology of a Bubble Moving in Confined Channel Filled with Viscoelastic Fluid
Authors: Zhang Yidi , Cao Xubo , Li Zhenzhen 
Published: December 2024

AbstractBubble motion in confined channels find applications ranging from carbon oxide sequestration to cardio-vascular embolism, and is ubiquitous in nature and industry. The confinement of bubbles in the channel causes the formation of a thin liquid film between gas and solid wall, whose flow field has been studied theoretically and especially for Newtonian fluids. Steadily moving bubbles in Newtonian fluids exhibits saddle shape. However, since a large amount of industrial and biological fluids are complex fluids, the motion of morphology of moving bubbles can be affected by non-Newtonian effect such as viscoelasticity. The purpose of this work is to explore the thickness distribution of liquid film between gas and solid wall during the motion of bubbles in a confined channel filled with viscoelastic fluid. In this study, bubbles are formed with flow focusing method of droplet microfluidics, bubbles move steadily through a long channel, and the film thickness is measured by an experimental method based on light interference. The relative optical interference intensity (ROII) method was used to obtain the thickness distribution of liquid film by analyzing the fringes. The thickness distribution of the liquid film within the bubble’s reference frame exhibits a different pattern compared to that in Newtonian fluids, and the symmetry of the spherical bubble is violated. This study provides experimental data for theoretical and computational research on bubble dynamics in confined channels.
Effect of Fractal Orifice on Characteristics of Turbulent/Non-turbulent Interface in Synthetic Jet Flow
Authors: Xu Congyi , Wang Jinjun 
Published: December 2024

AbstractSynthetic jets with circular and fractal orifices are experimentally investigated using time-resolved stereoscopic particle image velocimetry. The synthetic jet with circular orifice exhibit more rapid centreline velocity decay and half-width growth, indicating superior entrainment over the continuous jet. The synthetic jets with fractal orifices show intermediate entrainment performance between the round synthetic jet and continuous jet. The analysis on turbulent/non-turbulent interface (TNTI) properties reveals that the fractal orifice reduces the mean value and fluctuation of the radial position of the TNTI, as well as the tortuosity of the TNTI. This reduction in TNTI properties leads to a decrease in the area where nibbling occur. Consequently, synthetic jets with fractal orifices exhibit inferior entrainment performance compared to those with circular orifices.