bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Perioperative Antithrombotics on Postoperative Transfusion and Hematoma in Head and Neck Free Flaps
Authors: Hicks Melanie D. , Vasudev Milind , Bishop Jessica L. , Garcia Natalie , Chowdhury Farshad , Pham Tiffany T. , Heslop Gabriela , Greene Benjamin , Jeyarajan Hari , Grayson Jessica W. , Goddard Julie A. , Tjoa Tjoson , Haidar Yarah , Thomas Carissa M. 
Published: October 2023

AbstractObjectiveTo explore if antiplatelet or anticoagulant therapy increases the risk of transfusion requirement or postoperative hematoma formation in patients undergoing microvascular reconstruction for head and neck defects.Study DesignRetrospective cohort study.SettingDepartments of Otolaryngology–Head and Neck Surgery at the University of Alabama at Birmingham, the University of Colorado, and the University of California Irvine.MethodsA multi‐institutional, retrospective review on microvascular reconstruction of the head and neck between August 2013 to July 2021. Perioperative antithrombotic data were collected to examine predictors of postoperative transfusion and hematoma.ResultsA total of 843 free flaps were performed. Preoperative hemoglobin, hematocrit, operative time, and flap type were positive predictors of postoperative transfusion in both bivariate (P < .0001) and multivariate analyses (P < .0001). However, neither anticoagulation nor antiplatelet therapy were predictive of postoperative transfusion rates and hematoma formation.ConclusionAntithrombotic regimens do not increase the risk of postoperative transfusion or hematoma in head and neck microvascular reconstruction. Based on this limited data, perioperative antithrombotic regimens can be considered in patients who may otherwise be at risk for these postoperative complications.
Statistical analysis of fracture of silica glass using molecular dynamics
Authors: Alshabab Somar Shekh , Markert Bernd , Bamer Franz 
Published: October 2023

AbstractDisordered solids exhibit intermittent avalanches when slowly driven by an external load. These avalanches are associated with plastic rearrangements of the atoms at the nanoscale that manifest as stress and energy drops in the loading curve. The complexity arising from their interactions through long‐range elastic fields and the disorder makes statistical approaches suitable for studying their behavior by considering yielding and fracture as a phase transition. To investigate the avalanche statistics, we perform nanoscale simulations using the athermal quasistatic deformation protocol to induce fracture to silica glass samples, which were simulated using the melting‐quenching technique. We identify and measure the avalanches and voids and investigate their evolution in the process of fracture. Our results confirm that the avalanches exhibit scale‐free power law statistics, indicative of a critical phenomenon.
A large strain thermoplasticity model including recovery, recrystallisation and grain size effects
Authors: Böddecker Merlin , Menzel Andreas 
Published: October 2023

AbstractIn manufacturing, thermomechanical processes such as static annealing and hot working are commonly used to tailor the microstructure of metals to achieve favourable macroscopic material properties that meet specific application requirements. To improve sequential manufacturing processes and to accurately predict the microstructural changes of the material along the process chain, physically motivated constitutive models are required that simultaneously account for the effects of recovery and recrystallisation, as well as grain size dependencies. To this end, Cho et al. [Int. J. Plasticity 112, 123–157 (2019)] proposed a macroscopic hypo‐elasticity based large strain thermoplasticity model that aims at the unification of the effects of static and dynamic recovery and recrystallisation, as well as grain growth and refinement. In the present contribution, the hypo‐elasticity based large strain recrystallisation formulation proposed by Cho et al. is transferred to a hyper‐elasticity based large strain thermoplasticity framework to overcome the limitations typically accompanied with hypo‐elasticity based formulations. For this purpose, an isotropic temperature dependent hyper‐elastic Hencky type formulation defined in logarithmic strains is combined with a temperature dependent von Mises yield criterion. The recrystallisation modelling approach by Cho et al. is adopted, assuming a non‐associated temperature dependent proportional hardening rate in the form of an Armstrong‐Frederick type hardening minus recovery format, wherein the proportional hardening related internal variable is interpreted as a measure of dislocation density. It is shown that the hyper‐elasticity based format results in a thermodynamical consistency condition that effectively constrains the physically motivated evolutions of recrystallised volume fraction and average grain size. To investigate the capability of the model to predict the material response of unified recrystallisation thermodynamically consistently, representative thermomechanical sequential loading conditions including static annealing and hot working are studied.
Mechanical performance of adhesively bonded carbon fiber reinforced boron‐modified phenolic resin plastic‐titanium single‐lap joints at high temperature
Authors: Ma Guoqing , Han Xiao , Ying Liang , Wang Dezhi , Wu Chengwei 
Published: October 2023

AbstractThis article characterized the mechanical performance and failure mode of single‐lap joints (SLJs) of carbon fiber reinforced boron‐modified phenolic resin plastic (CF/BPR) and TC4 titanium alloy by quasi‐static tensile tests at four temperatures (25, 100, 175, and 250°C). The experimental results indicated that the shear strength of SLJs is 10.8 MPa at 25°C, which experiences monotonic drop to 80%, 42.6%, and 18.5% with temperature increase from 100 to 175°C, and to 250°C, respectively. Additionally, there was a transformation in the failure mode from composite material failure to cohesive failure in the adhesive along with the temperature increase. The intralaminar elasticities of CF/BPR were predicted using representative volume element (RVE), and the mechanical properties of three types of bondlines (i.e., the interlamination, interface of CF/BPR and the epoxy adhesive layer) were determined by both experiment and predictive methods. A finite element model taking into account the intralaminar damage of CF/BPR and the cohesive behavior of three bondlines was established. The simulated results showed good consistency with the experimental data for failure prediction, and the mechanical performance and damage propagation of SLJs at different temperatures were discussed. This research provides reference for the design and manufacture of high‐temperature bonded structures.Highlights
RVE and degradation factor methods evaluate the elasticity of composite material.
Four types of damage behaviors are considered in the established FE model.
The SLJs exhibit single or multiple failure modes at different temperatures.
The mechanical properties of SLJs severely degraded with increasing temperature.
An investigation of the mechanical characteristics of natural particle‐reinforced glass and epoxy composites after immersion in acidic and basic aging solutions
Authors: Kandas Halis , Ozdemir Okan 
Published: October 2023

AbstractThis study aimed to ascertain the alterations in aging responses of fiber‐reinforced composites, as well as the effects of their natural particle reinforcement, through exposure to acidic and alkaline solutions. Specimens were produced with 0 wt. % (neat), 1 wt. %, 2 wt. % and 3 wt. % particle ratios from acorn and pinecone particles. A particle content of 2 wt. % was determined to yield the best mechanical properties in all mechanical tests conducted for pinecone reinforcement. The highest improvement in strength, observed in 3 wt. % pinecone‐reinforced composites, reached 22.5% at flexural strength. HCl and NaOH diluted in water were chosen as aging solutions. Mechanical tests were repeated at different stages of aging. According to the findings, 1 wt. % particle‐reinforced composites showed better resilience to the mechanical property reduction effect of aging compared to the 2 wt. % and 3 wt. % particle‐reinforced composites. At a particle ratio of 2 wt. %, the acorn‐reinforced specimens exhibit their highest maximum penetration force, which is 5% higher than that of the 0 wt. % composite, consistent with the results of tensile and compressive tests.Highlights
Composite material was manufactured by hand lay‐up and vacuum bagging method.
Specimens were aged using acid and base solutions.
Tensile, compressive, and bending results were obtained depending on particle type and ratio.
Tensile, compressive, and bending strengths of composites were compared according to various aging times.
Effects of long‐range dispersive interaction on the electron transport in short single strands of guanine bases
Authors: Bao Xuan‐Xuan , Wang Xue‐Feng 
Published: October 2023

AbstractWe study the effects of the long‐range dispersive interaction on the electron transport in short single strands of guanine bases (G)s employing the density functional theory combined with non‐equilibrium Green's function method. Effects of contacting position are considered by connecting atomic gold chain electrodes on different positions to adapt to possible realistic measurements. The dispersive interaction can modify the stacking structure and enhance the helicity of the molecules. The corresponding change in the electronic structure may result in much‐increased conductance and the rectification effect. The dispersive interaction may also be the key to the realization of first‐principles simulation of some systems.
Strain‐Free GaSb Quantum Dots as Single‐Photon Sources in the Telecom S‐Band
Authors: Michl Johannes , Peniakov Giora , Pfenning Andreas , Hilska Joonas , Chellu Abhiroop , Bader Andreas , Guina Mircea , Höfling Sven , Hakkarainen Teemu , Huber‐Loyola Tobias 
Published: October 2023

AbstractGenerating single photons in the telecommunication wavelength range from semiconductor quantum dots (QDs) and interfacing them with spins of electrons or holes is of high interest in recent years, with research mainly focusing on indium‐based QDs. However, there is not much data on the optical and spin properties of gallium antimonide (GaSb) QDs, despite it being a physically rich system with an indirect to direct bandgap crossover in the telecom wavelength range. This work investigates the (quantum‐) optical properties of GaSb QDs, which are fabricated by filling droplet‐etched nanoholes in an aluminum gallium antimonide (AlGaSb) matrix. Photoluminescence (PL) features from isolated and highly symmetric QDs are observed that exhibit narrow linewidth in the telecom S‐band and show an excitonic fine structure splitting of up to µeV. Moreover, time‐resolved measurements of the decay characteristics of an exciton are performed and the second‐order photon autocorrelation function of the charge complex is measured to , revealing clear antibunching and thus proving the capability of this material platform to generate non‐classical light.
Pregnancy‐specific dietary guidelines for Americans are not met: Findings from a pilot study
Authors: El Habbal Noura , Filatava Evgenia J. , Overton Nicolette E. , Gregas Matt , Gregory Katherine E. 
Published: October 2023

AbstractObjectiveTo assess maternal dietary intake during pregnancy and adherence to the 2020–2025 pregnancy‐specific Dietary Guidelines for Americans (DGA).MethodsThis was a retrospective observational study. The study population consisted of women who gave birth to term infants (>37 weeks of gestation). Participants were given the Dietary Screener Questionnaire (DSQ) after birth and asked to recall their dietary intake in the last month of pregnancy. Participants' estimated dietary intakes were then compared to the 2020–2025 DGA which includes specific recommendations for pregnant women.ResultsOut of 51 women who completed the DSQ, none consumed the recommended amounts of all surveyed dietary factors. Specifically, only one woman (2%) met the recommended intake of fruits, 11 women (22%) met the recommended intake of calcium, 25 women (49%) exceeded the recommended upper limit for added sugar intake, and none of the women (0%) met the intake of vegetables, whole grains, dairy and fiber.ConclusionWomen in our study did not adhere to the pregnancy‐specific DGA recommendations in the last month of pregnancy. Our findings underscore the need to increase maternal nutritional awareness and education to improve adherence to the DGA.
Chasing the rainbow: Exploiting photosensitizers to drive photoisomerization reactions
Authors: Wang Zhihang , Fernandez Lorette , Aslam Adil S. , Shamsabadi Monika , Muhammad Lidiya M. , Moth‐Poulsen Kasper 
Published: October 2023

AbstractPhotoswitchable molecules have garnered considerable attention for their versatility and diverse applications, spanning from solar energy harvesting and storage to drug delivery and molecular motors. The chemical conversions that make photoswitches a desirable system are driven by specific wavelengths of light, which often demand intricate molecular modifications. An alternative approach to achieve the photoisomerization reaction is through energy transfer with photosensitizers. Photosensitizers play a pivotal role in various light‐induced processes and have demonstrated successful applications in photodynamic therapy, dye‐sensitized solar cells, and activating photochemical reactions. Therefore, combining photoswitching systems with sensitizers presents an attractive alternative for advancing light‐responsive material design and enabling innovative light‐controlled technologies. This review summarizes the energy transfer mechanisms and strategies involved in sensitized molecular photoswitchable systems, emphasizing the performance of various combined systems, and potential applications. Furthermore, recent advances and emerging trends in this field are also discussed, offering insights into prospective future directions for the development of light‐responsive materials.
The impact of clean energy consumption, green innovation, and technological diffusion on environmental sustainability: New evidence from load capacity curve hypothesis for 10 European Union countries
Authors: Aydin Mucahit , Degirmenci Tunahan 
Published: October 2023

AbstractToday, when climate change and environmental degradation are experienced, environmental sustainability comes to the fore. The most important component of environmental sustainability is undoubtedly technology and innovation. This study examines the effects of clean energy consumption, green innovation, and technological diffusion on environmental sustainability from 1990 to 2018 in selected European Union countries. This relationship has been frequently examined in the literature within the framework of the environmental Kuznets curve (EKC) hypothesis. The number of studies examining it within the load capacity curve (LCC) hypothesis framework is negligible. This study aims to fill the gap in the literature in the context of examining the relationship within the framework of the LCC hypothesis. For this purpose, Westerlund's (2008) panel cointegration test was applied, and cointegration was determined in the LCC model. Three different long‐term estimators, namely rCCE, DCCE, and AMG, were used to test the validity of the hypothesis. Although the results obtained for the entire panel say that the LCC hypothesis is not valid, evidence for the existence of the hypothesis has been identified in the country‐based results. Accordingly, the LCC hypothesis is valid for Denmark, France, Portugal, and Spain. Overall, green innovation and technological diffusion are essential to encourage the spread of environmentally friendly practices and to leave a more livable world for future generations.
Modulating Electronic Structure by Etching Strategy to Construct NiSe2/Ni0.85Se Heterostructure for Urea‐Assisted Hydrogen Evolution Reaction
Authors: Wu Kaili , Lyu Chaojie , Cheng Jiarun , Guo Zhonglu , Li Hongyu , Zhu Xixi , Lau Woon‐Ming , Zheng Jinlong 
Published: October 2023

AbstractExploring and developing novel strategies for constructing heterostructure electrocatalysts is still challenging for water electrolysis. Herein, a creative etching treatment strategy is adopted to construct NiSe2/Ni0.85Se heterostructure. The rich heterointerfaces between NiSe2 and Ni0.85Se emerge strong electronic interaction, which easily induces the electron transfer from NiSe2 to Ni0.85Se, and tunes the charge‐state of NiSe2 and Ni0.85Se. In the NiSe2/Ni0.85Se heterojunction nanomaterial, the higher charge‐state Ni0.85Se is capable of affording partial electrons to combine with hydrogen protons, inducing the rapid formation of H2 molecule. Accordingly, the lower charge‐state NiSe2 in the NiSe2/Ni0.85Se heterojunction nanomaterial is more easily oxidized into high valence state Ni3+ during the oxygen evolution reaction (OER) process, which is beneficial to accelerate the mass/charge transfer and enhance the electrocatalytic activities towards OER. Theoretical calculations indicate that the heterointerfaces are conducive to modulating the electronic structure and optimizing the adsorption energy toward intermediate H* during the hydrogen evolution reaction (HER) process, leading to superior electrocatalytic activities. To expand the application of the NiSe2/Ni0.85Se‐2h electrocatalyst, urea is served as the adjuvant to proceed with the energy‐saving hydrogen production and pollutant degradation, and it is proven to be a brilliant strategy.
Surface Glass Transition Temperature Region of Diarylethene Films Determined by Nano‐Marangoni Effect
Authors: Tsujioka Tsuyoshi , Yamabayashi Keishi , Kotani Kazuma 
Published: October 2023

AbstractFor the last two decades, research has addressed whether the glass transition temperature and the molecular motions on the surface of organic films are significantly different from those inside the bulk glasses. It is reported that the surface of the photochromic diarylethene film prepared by vacuum deposition has fluidity and the vacuum deposition of small amount of rubrene molecules induces surface tension fluctuations, generating dents due to the Marangoni flow in nanoscale. The depth of the dents increases in proportion to these radii for the colorless diarylethene film with a bulk glass transition temperature (Tg) close to room temperature. On the other hand, in the colored diarylethene obtained by UV irradiation to the colorless film, the depth becomes constant at a certain level. The Tg distribution in the depth direction is clarified based on an analysis of the dent depth. By approximating the obtained Tg depth distribution with an exponential function, the outermost surface Tg is about 100 K lower than the bulk Tg in the case of photoisomerized diarylethene.
DeepMDFC: A deep learning based android malware detection and family classification method
Authors: Sharma Sandeep , Ahlawat Prachi , Khanna Kavita 
Published: October 2023

AbstractUnprecedented growth and prevalent adoption of the Android Operating System (OS) have triggered a substantial transformation, not only within the smartphone industry but across various categories of intelligent devices. These intelligent devices store a wealth of sensitive data, making them enticing targets for malicious individuals who create harmful Android applications to steal this data for malicious purposes. While numerous Android malware detection methods have been proposed, the exponential growth in sophisticated and malicious Android apps presents an unprecedented challenge to existing detection techniques. Some of the researchers have attempted to classify malicious Android applications into families through static analysis of applications but most of them are evaluated on applications of previous API levels. This paper introduces a novel dataset compromising of 2019 to 2021 applications and proposes a Deep Learning based Malware Detection and Family Classification method (DeepMDFC) to detect and classify emerging malicious Android applications through static analysis and deep Artificial Neural Networks. Experimental findings indicate that DeepMDFC surpasses standard machine learning algorithms, achieving accuracy rates of 99.3% and 96.7% for Android malware detection and classification, respectively, with a limited size feature set. The performance of DeepMDFC is also assessed using the benchmark dataset (DREBIN) and results showed that DeepMDFC surpasses these methods in terms of performance. Furthermore, it leverages the proposed dataset to construct a prediction model that adeptly identifies malicious Android applications from both the years 2022 and 2023. This process the potency and resilience of DeepMDFC against emerging Android applications.
On the use of ordered factors as explanatory variables
Authors: Azzalini Adelchi 
Published: October 2023

SummaryConsider a regression or some regression‐type model for a certain response variable where the linear predictor includes an ordered factor among the explanatory variables. The inclusion of a factor of this type can take place in a few different ways, discussed in the pertaining literature. The present contribution proposes a different way of tackling this problem, by constructing a numeric variable in an alternative way with respect to the current methodology. The proposed technique appears to retain the data fitting capability of the existing methodology but with a simpler interpretation of the model components.
Toward presenting an ensemble meta‐model for evaluation of pozzolanic mixtures incorporating industrial by‐products
Authors: Ashrafian Ali , Behnood Ali , Golafshani Emadaldin Mohammadi , Panahi Elahe , Berenjian Javad 
Published: October 2023

AbstractUnsustainable development in the industry has increased the challenge of proper disposal of industrial by‐products and has caused environmental pollution on a large scale. Furthermore, minimizing the carbon dioxide emissions due to industrial and environmental activities is a crucial challenge to controlling the global warming crisis and climate change. The use of industrial by‐product‐based supplementary cementitious materials (SCMs) can reduce fossil fuel consumption through the reduction in cement production and contribute to suitable waste management. In this research, a meta‐model was developed using integration of the decision tree‐based method named reduced error pruning tree (REPtree) and ensemble approaches (boosting and bagging) to improve the pruning phase for strength simulation of concrete mixtures incorporating industrial by‐products. Then, ensemble multiple learning algorithms were applied to develop a meta‐model using the artificial neural network and Gaussian process regression. A comprehensive experimental‐based database incorporating 3836 records from short‐term to long‐term compressive strength (CS) was collected from the literature. Performance measures present that the proposed ensemble boosting‐REPtree model outperforms other benchmark and ensemble models with a correlation coefficient of 0.960 and root mean square error of 7.884 MPa. Also, uncertainty evaluation was done based on the Monte Carlo simulation algorithm in the modeling process. The FAST and SOBOL methods, as global sensitivity analysis, presented water‐to‐binder (W/B) ratio, curing time, and SCMs to binder ratio (SCM/B) as critical components to estimate the CS of concrete mixtures. The computational simulation of the influential parameters on concrete mixtures incorporating industrial by‐products revealed that the experimental factors yielding the highest CS of the mixtures were calculated as follows: cement content of 584 kg/m3, W/B ratio of 0.17, superplasticizer‐to‐cement ratio of 1.88%, and SCM/B ratio of 0.15.