bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting body fat percentage at 36 weeks of postmenstrual age in infants born preterm: A diagnostic accuracy study
Authors: Razzaghy Jacqueline , Zhang Li , Yi Nengjun , Salas Ariel A. 
Published: September 2023

AbstractBackgroundCurrent standards for assessing body composition can be costly and technically challenging. There is a need for a predictive equation that combines multiple clinical and anthropometric factors to predictbody composition outcomes at 36 weeks of postmenstrual age (PMA) or discharge.MethodsTo develop a widely applicable equation that predicts body fat percentage in preterm infants, we analyzed anthropometric data collected prospectively from a cohort of infants born very preterm between 2017 and 2018. We integrated clinical variables significantly associated with adiposity into a predictive equation using Bayesian linear regression models and leave‐one‐out cross‐validation.ResultsWe analyzed data from 86 infants born at 32 weeks of gestation or less (median gestational age, 30 weeks; mean birthweight, 1471 ± 270 g). Weight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and higher enteral fluid intake (>180 ml/kg/day) were the strongest predictors of body fat percentage in the model with the highest predictive value (R2 = 0.65). The correlation between actual and predicted body fat percentage using this Bayesian model was high (r = 0.82).ConclusionsWeight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and enteral fluid intake are significant predictors of body fat percentage at 36 weeks of PMA in very preterm infants.
Gamification's role in fostering user engagement with healthy food‐based digital content
Authors: Charry Karine , Poncin Ingrid , Kullak Avreliane , Hollebeek Linda D. 
Published: September 2023

AbstractThough digital platforms (e.g., social media) are often used to promote unhealthy, calorie‐dense foods, the dynamics characterizing consumers' engagement with healthy nutrition‐based content (e.g., as stimulated trough gamification) on these platforms remains tenuous, warranting further exploration. Addressing this gap, we deploy a qualitative field study and two experiments to show that challenge, a gamification mechanic that relies on rewarding incremental behavioral (e.g., food choice) improvements, shapes consumers' enjoyment of, and engagement with, digital healthy food‐based content. Study 1 (n = 95) shows that challenge induces consumer enjoyment, boosting their engagement with healthy food‐related digital content. Study 2 (n = 94) corroborates these findings by revealing a serial mediation effect of gamification‐based challenge on consumers' enjoyment of, and engagement with, healthy food‐based content. Extending Study 1, we also identify engagement's positive effect on consumers' app reuse intent. Moreover, we identify a moderating role of consumers' stage of change‐based action (i.e., readiness to act on their health), which strengthens the association of gamification‐based challenge/enjoyment. Overall, the findings substantiate gamification's role in boosting consumers' engagement with digital healthy food‐based content. We conclude by deriving pertinent implications from our analyses.
Uncertainty quantification in coastal aquifers using the multilevel Monte Carlo method
Authors: Litvinenko Alexander , Logashenko Dmitry , Tempone Raul , Vasilyeva Ekaterina , Wittum Gabriel 
Published: September 2023

AbstractWe are solving a problem of salinisation of coastal aquifers. As a test case example, we consider the Henry saltwater intrusion problem. Since porosity, permeability and recharge are unknown or only known at a few points, we model them using random fields and random variables. The Henry problem describes a two‐phase flow and is non‐linear and time‐dependent. The solution to be found is the expectation of the salt mass fraction, which is uncertain and time‐dependent. To estimate this expectation, we use the well‐known multilevel Monte Carlo (MLMC) method. The MLMC method takes just a few samples on computationally expensive (fine) meshes and more samples on cheap (coarse) meshes. Then, by building a telescoping sum, the MLMC method estimates the expected value at a much lower computational cost than the classical Monte Carlo method. The deterministic solver used here is the well‐known parallel and scalable ug4 solver.
On the relevance of descriptor fidelity in microstructure reconstruction
Authors: Seibert Paul , Raßloff Alexander , Kalina Karl , Safi Ali , Reck Paul , Peterseim Daniel , Klusemann Benjamin , Kästner Markus 
Published: September 2023

AbstractA common strategy for reducing the computational effort of descriptor‐based microstructure reconstruction in the Yeong–Torquato algorithm lies in restricting the choice of descriptors to an efficiently computable subset. As an alternative, the number of iterations can be reduced by gradient‐based optimization as in differentiable microstructure characterization and reconstruction (DMCR). This allows for, but does not require, the use of a set of informative, high‐dimensional and computationally expensive descriptors that would be unfeasible for a high number of iterations. For this reason, the present work investigates the role of descriptor fidelity on microstructure reconstruction results. More precisely, spatial two‐ and three‐point correlations as well as the lineal path function are computed on 2D planes as well as on 1D lines. These descriptors are used for reconstruction with the Yeong–Torquato and DMCR algorithm and the results are compared throughout various microstructures, respectively.
Extraction solvent selection for Cannabis sativa L. by efficient exploration of cannabinoid selectivity and phytochemical diversity
Authors: Tzimas Petros S. , Petrakis Eleftherios A. , Halabalaki Maria , Skaltsounis Leandros A. 
Published: September 2023

AbstractIntroductionCannabis sativa L. is attracting worldwide attention due to various health‐promoting effects. Extraction solvent type is critical for the recovery of bioactive compounds from the plant, especially cannabinoids. However, the choice of solvent is varied and not adequately warranted elsewhere, causing confusion in involved fields.ObjectiveThe present work aimed to investigate the effect of extraction solvent on C. sativa (hemp) with regard to cannabinoid recovery and phytochemical profile of the extracts, considering most of the related solvents.MethodologyThe majority of solvents reported for C. sativa (n = 14) were compared using a representative hemp pool. Quantitative results for major and minor cannabinoids were rapidly and reliably obtained using ultrahigh‐performance liquid chromatography coupled with photodiode array detection (UPLC‐PDA). In parallel, high‐performance thin‐layer chromatographic (HPTLC) fingerprinting was employed, involving less toxic mobile phase than in relevant reports. Various derivatisation schemes were applied for more comprehensive comparison of extracts.ResultsDifferential selectivity towards cannabinoids was observed among solvents. MeOH was found particularly efficient for most cannabinoids, in addition to solvent systems such as n‐Hex/EtOH 70:30 and ACN/EtOH 80:20, while EtOH was generally inferior. For tetrahydrocannabinol (THC)‐type compounds, EtOAc and n‐Hex/EtOAc 60:40 outperformed n‐Hex, despite its use in the official EU method. Solvents that tend to extract more lipids or more polar compounds were revealed based on HPTLC results.ConclusionCombining the observations from UPLC quantitation and HPTLC fingerprinting, this work allowed comprehensive evaluation of extraction solvents, in view of robust quality assessment and maximised utilisation of C. sativa.
Co/CoS2 Heterojunction Embedded in N, S‐Doped Hollow Nanocage for Enhanced Polysulfides Conversion in High‐Performance Lithium–Sulfur Batteries
Authors: Zheng Ming , Zhao Junzhe , Wu Wei , Chen Runzhe , Chen Suhao , Cheng Niancai 
Published: September 2023

AbstractModulating the electronic configuration of the substrate to achieve the optimal chemisorption toward polysulfides (LiPSs) for boosting polysulfide conversion is a promising way to the efficient Li–S batteries but filled with challenges. Herein, a Co/CoS2 heterostructure is elaborately built to tuning d‐orbital electronic structure of CoS2 for a high‐performance electrocatalyst. Theoretical simulations first evidence that Co metal as the electron donator can form a built‐in electric field with CoS2 and downshift the d‐band center, leading to the well‐optimized adsorption strength for lithium polysulfides on CoS2, thus contributing a favorable way for expediting the redox reaction kinetics of LiPSs. As verification of prediction, a Co/CoS2 heterostructure implanted in porous hollow N, S co‐doped carbon nanocage (Co/CoS2@NSC) is designed to realize the electronic configuration regulation and promote the electrochemical performance. Consequently, the batteries assembled with Co/CoS2@NSC cathode display an outstanding specific capacity and an admirable cycling property as well as a salient property of 8.25 mAh cm−2 under 8.18 mg cm−2. The DFT calculation also reveals the synergistic effect of N, S co‐doping for enhancing polysulfide adsorption as well as the detriment of excessive sulfur doping.
Large‐Area Soluble Covalent Organic Framework Oligomer Coating for Organic Solution Nanofiltration Membranes
Authors: Yu Huiting , Guan Jiayu , Chen Yaohan , Sun Yuxuan , Zhou Shengyang , Zheng Jifu , Zhang Qifeng , Li Shenghai , Zhang Suobo 
Published: September 2023

AbstractCovalent organic frameworks (COFs) are a family of engaging membrane materials for molecular separation, which remain challenging to fabricate in the form of thin‐film composite membranes due to slow crystal growth and insoluble powder. Here, an additive approach is presented to construct COF‐based thin‐film composite membranes in 10 min via COF oligomer coating onto poly(ether ether ketone) (PEEK）ultrafiltration membranes. By the virtue of ultra‐thin liquid phase and liquid‐solid interface‐confined assembly, the COF oligomers are fast stacked up and grow along the interface with the solvent evaporation. Benefiting from the low out‐plane resistance of COFs, COF@PEEK composite membranes exhibit high solvent permeances in a negative correlation with solvent viscosity. The well‐defined pore structures enable high molecular sieving ability (Mw = 300 g mol−1). Besides, the COF@PEEK composite membranes possess excellent mechanical integrities and steadily operate for over 150 h in the condition of high‐pressure cross flow. This work not only exemplifies the high‐efficiency and scale‐up preparation of COF‐based thin‐film composite membranes but also provides a new strategy for COF membrane processing.
Entropy‐Tuned Layered Oxide Cathodes for Potassium‐Ion Batteries
Authors: Li Shu , Wu Lichen , Fu Hongwei , Rao Apparao M. , Cha Limei , Zhou Jiang , Lu Bingan 
Published: September 2023

AbstractThe manganese‐based layered oxides as a promising cathode material for potassium ion batteries (PIBs) have attracted considerable interest owing to their simple synthesis, high specific capacity, and low cost. However, due to the irreversible phase transition and the Jahn–Teller distortion of the Mn3+, its application in potassium ion batteries is limited, leading to slow potassium ion kinetics and severe capacity attenuation. Here, entropy‐tuning by changing the content of cathode material composition is proposed to address the above challenges. Compared to low and high entropy variants of K0.45MnxCo(1‐x)/4Mg(1‐x)/4Cu(1‐x)/4Ti(1‐x)/4O2, where x = 0.8, 0.6, and 0.4, the medium entropy K0.45Mn0.6Co0.1Mg0.1Cu0.1Ti0.1O2 shows more balanced electrochemical properties in the PIBs. Benefiting from entropy‐tuned suppression of the Jahn–Teller distortion of the Mn3+, the K0.45Mn0.6Co0.1Mg0.1Cu0.1Ti0.1O2 can achieve a high K+ ion transport rate and alleviated volume variation while retaining high specific capacity. Accordingly, the medium entropy K0.45Mn0.6Co0.1Mg0.1Cu0.1Ti0.1O2 cathode in the full cell exhibits a high capacity of 100 mAh g−1 at 50 mA g−1, delivers superior rate capability (65.8 mAh g−1 at 500 mA g−1) and cycling stability (67.8 mAh g−1 after 350 cycles at 100 mA g−1). The entropy‐tuning strategy is expected to open new avenues in designing PIB cathode materials and beyond.
A probabilistic modeling and evolutionary optimization approach for serverless workflow configuration
Authors: Wang Weiguo , Wu Quanwang , Zhang Zhiyong , Zeng Jie , Zhang Xiang , Zhou Mingqiang 
Published: September 2023

AbstractServerless computing has nowadays become a mainstream paradigm to develop cloud‐native applications owing to its high scalability, ease of usage and cost‐effectiveness. Nevertheless, because of its poor infrastructure transparency, two main challenges emerge when users migrate their applications to a serverless platform: the lack of an effective analytical model for performance and billing, and the trade‐off problem between them. In this paper, we formally define a serverless workflow and introduce the concept of execution instances. Based on them, a probabilistic performance and cost evaluation model is built to obtain their expected values for an input serverless workflow. Then, we design a tailored evolutionary optimization algorithm called EASW to tackle budget‐constrained performance optimization and performance‐constrained cost optimization problems. Extensive experiments were carried out to test the proposed model and optimization algorithm on AWS Lambda. Results reveal that our model can achieve an accuracy over 98% and EASW can yield a better memory configuration solution than existing methods for constrained optimization.
Whitney stratifications are conically smooth
Authors: Nocera Guglielmo , Volpe Marco 
Published: September 2023

AbstractThe notion of conically smooth structure on a stratified space was introduced by Ayala, Francis and Tanaka. This is a very well behaved analogue of a differential structure in the context of stratified topological spaces, satisfying good properties such as the existence of resolutions of singularities and handlebody decompositions. In this paper we prove Ayala, Francis and Tanaka’s conjecture that any Whitney stratified space admits a canonical conically smooth structure. We thus establish a connection between the theory of conically smooth spaces and the classical examples of stratified spaces from differential topology.
Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports
Authors: Nakaura Takeshi , Yoshida Naofumi , Kobayashi Naoki , Shiraishi Kaori , Nagayama Yasunori , Uetani Hiroyuki , Kidoh Masafumi , Hokamura Masamichi , Funama Yoshinori , Hirai Toshinori 
Published: September 2023

Abstract
Purpose
In this preliminary study, we aimed to evaluate the potential of the generative pre-trained transformer (GPT) series for generating radiology reports from concise imaging findings and compare its performance with radiologist-generated reports.

Methods
This retrospective study involved 28 patients who underwent computed tomography (CT) scans and had a diagnosed disease with typical imaging findings. Radiology reports were generated using GPT-2, GPT-3.5, and GPT-4 based on the patient’s age, gender, disease site, and imaging findings. We calculated the top-1, top-5 accuracy, and mean average precision (MAP) of differential diagnoses for GPT-2, GPT-3.5, GPT-4, and radiologists. Two board-certified radiologists evaluated the grammar and readability, image findings, impression, differential diagnosis, and overall quality of all reports using a 4-point scale.

Results
Top-1 and Top-5 accuracies for the different diagnoses were highest for radiologists, followed by GPT-4, GPT-3.5, and GPT-2, in that order (Top-1: 1.00, 0.54, 0.54, and 0.21, respectively; Top-5: 1.00, 0.96, 0.89, and 0.54, respectively). There were no significant differences in qualitative scores about grammar and readability, image findings, and overall quality between radiologists and GPT-3.5 or GPT-4 (p > 0.05). However, qualitative scores of the GPT series in impression and differential diagnosis scores were significantly lower than those of radiologists (p < 0.05).

Conclusions
Our preliminary study suggests that GPT-3.5 and GPT-4 have the possibility to generate radiology reports with high readability and reasonable image findings from very short keywords; however, concerns persist regarding the accuracy of impressions and differential diagnoses, thereby requiring verification by radiologists.
Removal of metronidazole antibiotic by modified red mud from aqueous solutions: process modeling, kinetic, and isotherm studies
Authors: Lotfi Golsefidi Fatemeh , Zahmatkesh Anbarani Mohaddeseh , Bonyadi Ziaeddin 
Published: September 2023

AbstractMetronidazole is a type of antibiotic that is commonly used to treat bacterial infections in both humans and animals. The objective of this study was to eliminate MDZ from aqueous solutions using MRM. To gain a better understanding of the adsorption mechanism, we utilized kinetic and isotherm models to investigate the factors that affect the removal of MDZ. The Box–Behnken model was utilized to design experimental factors, which included the initial concentration of MDZ (ranging from 5 to 80 mg/L), MRM dose (ranging from 0.1 to 0.7 g/L), reaction time (ranging from 10 to 60 min), and pH (ranging from 4 to 10). Analysis of the adsorbent using FESEM, FTIR, EDX, DLS, and zeta potential provided valuable insights into its morphology, surface properties, functional groups, size, and electrical charge. Acid modification of red mud increased the porosity and number of pores on the adsorbent surface, thereby enhancing its ability to adsorb the MDZ antibiotic. The FTIR spectrum displays various bands corresponding to different functional groups, such as O–H, Si(Al)–O, Fe–O, and carbonate groups. EDX analysis revealed that the composition of MRM includes carbon, oxygen, and nitrogen elements. The DLS and zeta potential data demonstrate the impact of particle size and electric charge of the adsorbent on the removal of MDZ. The maximum removal of MDZ, which was 69.87%, was achieved at an MDZ concentration of 42.5 mg/L, a pH of 7, a contact time of 35 min, and an adsorbent dose of 0.4 g/L. The removal of MDZ follows both the pseudo-second-order model and the Langmuir model. The maximum adsorption capacity was found to be 6.04 mg/g. The findings of this study indicate that MRM successfully removes MDZ from aqueous solutions.
Revolutionizing shale drilling with potassium chloride-based natural deep eutectic solvent as an additive
Authors: Rasool Muhammad Hammad , Ahmad Maqsood 
Published: September 2023

AbstractShale instability is a significant problem, accounting for approximately 70% of wellbore challenges during drilling operations. To address this issue, shale inhibitors are commonly added to drilling mud to stabilize the encountered shale formations. Ionic liquids and deep eutectic solvents have been recognized as effective shale inhibitors due to their environmental friendliness and effectiveness. However, despite their advantages, these solutions still lack full environmental sustainability, leading researchers to explore more natural alternatives like Natural Deep Eutectic Solvents (NADES). This study focuses on the synthesis and application of a NADES composed of Potassium Chloride (KCl) and glycerine, aiming to enhance the environmental profile and efficacy of shale inhibitors. The NADES was prepared with a 1:8 molar ratio at a temperature of 60 °C. Characterization analyses, including Fourier Transform Infrared and Thermogravimetric Analysis, confirmed the formation of bonds between –(OH) and Cl− and demonstrated the NADES's thermal stability up to 200 °C. Incorporating 3% NADES into water-based mud, prepared following API 13B-1 standards, resulted in significant improvements in mud rheology. Specifically, the addition of 3% NADES reduced filtrate volume by 14.2% and mud cake thickness by 19.2%. Furthermore, the 3% NADES exhibited remarkable inhibition of clay swelling by 69.23% and demonstrated a shale recovery rate of 58%. When compared with 3% KCl and 3% 1-ethyl-3-methylimidazolium chloride (EMIM-Cl), the NADES-based mud outperformed both in terms of efficacy. These findings were further supported by additional analyses, including d-spacing measurements (XRD), Zeta Potential, Surface tension, and Field Emission Scanning Electron Microscopy. Additionally, the rheological behavior of the NADES-based mud aligned with the Yield Power Law at both 25 °C and 100 °C. The study's findings contribute to the advancement of greener drilling practices and highlight the applicability of KCl-based NADES as a potential drilling fluid additive.
Facile and green synthesis of CuS-activated carbon nanocomposite from Sargassum siliquastrum biomass for fast and efficient removal of eosin yellow dye
Authors: Hasan Ibrahem M. A. , Assaf Fawzy H. , Tawfik Ahmed R. 
Published: September 2023

AbstractSargassum spp. comprise significant amounts of biomass which can be risky for environmental and economic activities; thus, taking the advantage of this underutilized raw material could make a significant contribution to long-term sustainability. In this study, Sargassum siliquastrum (SS) brown alga was successfully transformed into CuS nanoparticles–activated carbon (CuS NPs–AC) composite for adsorption of the hazardous dye eosin yellow (EY) from aqueous solutions. The CuS NPs–AC sorbent was characterized through FTIR, XRD, SEM-EDX, and SBET analyses. Characterization results revealed the successful formation of CuS NPs–AC nanocomposite. Results of the adsorption process indicated that EY was efficiently removed with a percentage of 99.6% at the optimum conditions; pH 7, 120 min contact time, 2 g/L CuS NPs–AC dose, and 300 mg/L initial EY concentration. Adsorption data fitted well with pseudo-second-order kinetics and Langmuir isotherm model with a monolayer adsorption capacity of 303.03 mg/g at 328 K. Thermodynamic analyses revealed that the adsorption process was spontaneous and endothermic. The adsorbent showed high selectivity towards EY and followed a three-stage intraparticle diffusion mechanism. The potent adsorption of EY by CuS NPs–AC nanocomposite was attributed to electrostatic attraction, π-π stacking, halogen bonding, and hydrogen bonding. This study developed a reliable and cost-effective adsorbent for removing EY dye from water.
Graphical Abstract