jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sirui Liu | Lin Song | Weishu Dai | Mengdie Liu | Huijing Zhang | Xueyan Zhang | Hongyu Li | Xiu Liu | Yan Lv | Ying Hu
Source: Frontiers in Bioengineering and Biotechnology (article, 2023-02-27)
Field: Materials Science — Polymers and Plastics

Worldwide productivity and research trend of publications concerning electroactive materials and spinal cord injury: A bibliometric study <b>Purpose:</b> We investigated the current state and trends in the area during the previous 10 years using bibliometric approaches to evaluate the global scientific output of research on electroactive materials and spinal cord injury. <b>Methods:</b> Studies on spinal cord injury in electroactive materials that were published between 2012 and 2022 were located using the Web of science (WOS) datebase. The software programs bibliometrix R-package and CiteSpace were used to do quantitative analyses of annual publications, nation, author, institution, journal source, co-cited references, and keywords. The studies were categorized by the research's main points using a qualitative analysis, and publications having more than 10 citations each year. <b>Results:</b> In the final analysis, 1,330 relevant papers or reviews were included. There is an increased tendency in both the average annual citation rate and the number of publications in the discipline. The United States and the University of Toronto are the countries and institutions that have contributed the most to this discipline, respectively. The majority of authors are from the China and United States. Zhang Y is the author with the most published articles and holds the top position in the cited author h-index species. The journal with the highest number of published articles is "Disability and rehabilitation"; the journal is divided into four main areas including physics, materials, chemistry, molecular, and biology. The keyword analysis revealed a shift in research hotspots from schwann cell, fracture, and urinary disorders to carbon-based materials, functional recovery, and surgery. Analysis of qualitative data revealed that the role and mechanism of injectable conductive hydrogels in spinal cord healing after damage is a hot topic of current study, with the mechanism primarily focusing on the inhibition of oxidative stress (Nrf2) and apoptosis (Casepase 3). <b>Conclusion:</b> Our bibliometric analysis indicates that research on electroactive materials for spinal cord injury remains an active field of study. Moreover, contemporary research is concentrated on carbon-based materials, functional rehabilitation, and surgery. Productivity ; Spinal cord injury ; Bibliometrics ; Medicine ; Psychology ; Spinal cord ; Computer science ; Economics ; Neuroscience ; Library science ; Economic growth Conducting polymers and applications ; Muscle activation and electromyography studies ; Neuroscience and Neural Engineering
Authors: Ivanna Yu. Danyliuk | Наталія Коваленко | Валентина ТОЛМАЧОВА | Olena M. Kovtun | Lesya Saliyeva | Nataliia Slyvka | Serhii Holota | G. P. Kutrov | M. D. Tsapko | М. В. Вовк
Source: Current Chemistry Letters (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Synthesis and antioxidant activity evaluation of some new 4-thiomethyl functionalised 1,3-thiazoles The 4-bromomethyl-substituted thiazolium salts and corresponding thiazoles obtained through the condensation of 1,3-dibromoacetone with thioamide derivatives were utilised as efficient alkylating reagents for a series of thiophenols and heterylthiols. As a result, a small library of 4-thiomethyl-functionalised 1,3-thiazoles was synthesised in high yields, and their structures were characterised by 1H, 13C NMR, LC-MS and IR spectra. Antioxidant activity of obtained compounds was studied in vitro using the DPPH test. The synthesised compounds showed high absorption level of DPPH radicals in the 70-98% range. For the most active derivatives 7e,m,p,t IC50 values were determined, which were in the range 191-417 µM (for ascorbic acid (reference) IC50 value was 29 µM). Obtained radical scavenging activity screening data suggest in-depth study of the antioxidant potential for these types of heterocyclic compounds. Chemistry ; DPPH ; Thioamide ; Antioxidant ; Ascorbic acid ; Reagent ; Organic chemistry ; Carbon-13 NMR ; Thiazole ; Radical Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Free Radicals and Antioxidants
Authors: Jingjing Wang | Sixue Chen | Yihang Qiu | Xiaoying Chen | Jian Shen | Chaoyang Li
Source: Micromachines (article, 2023-10-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Chiral Metasurface Multifocal Lens in the Terahertz Band Based on Deep Learning Chiral metasurfaces have garnered significant interest as an emerging field of metamaterials, primarily due to their exceptional capability to manipulate phase distributions at interfaces. However, the on-demand design of chiral metasurface structures remains a challenging task. To address this challenge, this paper introduces a deep learning-based network model for rapid calculation of chiral metasurface structure parameters. The network achieves a mean absolute error (MAE) of 0.025 and enables the design of chiral metasurface structures with a circular dichroism (CD) of 0.41 at a frequency of 1.169 THz. By changing the phase of the chiral metasurface, it is possible to produce not only a monofocal lens but also a multifocal lens. Well-designed chiral metasurface lenses allow us to control the number and position of focal points of the light field. This chiral metasurface, designed using deep learning, demonstrates great multifocal focus characteristics and holds great potential for a wide range of applications in sensing and holography. Metamaterial ; Terahertz radiation ; Holography ; Lens (geology) ; Optics ; Phase (matter) ; Focus (optics) ; Physics ; Position (finance) ; Computer science Metamaterials and Metasurfaces Applications ; Terahertz technology and applications ; Antenna Design and Analysis
Authors: Sanmun Kim | Chanhyung Park | Shinho Kim | Hsiao L. Chung | Min Seok Jang
Source: iScience (article, 2023-09-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design parameters of free-form color splitters for subwavelength pixelated image sensors Metasurface-based color splitters are emerging as next-generation optical components for image sensors, replacing classical color filters and microlens arrays. In this work, we report how the design parameters such as the device dimensions and refractive indices of the dielectrics affect the optical efficiency of the color splitters. Also, we report how the design grid resolution parameters affect the optical efficiency and discover that the fabrication of a color splitter is possible even in legacy fabrication facilities with low structure resolutions. Microlens ; Fabrication ; Beam splitter ; Optics ; Optoelectronics ; Color gel ; Materials science ; Computer science ; Refractive index ; Splitter ; Nanotechnology ; Physics ; Lens (geology) ; Laser Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Photonic Crystals and Applications
Authors: Dan Zhang
Source: Fire (article, 2023-06-08)
Field: Materials Science — Polymers and Plastics

Fire-Safe Biobased Composites: Enhancing the Applicability of Biocomposites with Improved Fire Performance Research has recently transitioned from the study of fossil-based materials to bio-sourced ones, following the quest to achieve sustainability. However, fire presents a unique hazard to bio-composite materials, which limits their applicability in various sectors. This necessitates an in-depth assessment of the fire behaviour of biobased composites used for specific applications. Improving the fire properties of bio-composites with flame retardants tends to reduce mechanical strength. Therefore, this review focused on biobased composite materials for packaging, structural, automotive, and aeronautical applications that are both mechanically strong and fire safe. It was noticed that the interfacial bonding between the matrix and the reinforcement should be optimized. In addition, optimum amounts of flame retardants are required for better fire performance. This article covers flame retardants for biobased composites, the optimum amount required, and the extent of improvement to the thermal stability and flammability of the materials. This research will help material scientists and the like in their selection of biomass feedstock, flame retardants, and general materials for different types of applications. Flammability ; Materials science ; Fire retardant ; Fire performance ; Composite material ; Raw material ; Fire safety ; Durability ; Composite number ; Fire resistance ; Engineering ; Civil engineering Natural Fiber Reinforced Composites ; Flame retardant materials and properties ; biodegradable polymer synthesis and properties
Authors: Péter Kovács | Peter Blaha | Georg K. H. Madsen
Source: The Journal of Chemical Physics (article, 2023-12-28)
Field: Materials Science — Materials Chemistry

Origin of the success of mGGAs for bandgaps One of the well-known limitations of Kohn-Sham density functional theory is the tendency to strongly underestimate bandgaps. Meta-generalized gradient approximations (mGGAs), which include the kinetic energy density in the functional form, have been shown to significantly alleviate this deficiency. In this study, we explore the mechanisms responsible for this improvement from the angle of the underlying local densities. We find that the highest occupied and lowest unoccupied states are distinct in the space of the underlying descriptors. The gap opening is compared to a simple scaling of the local density approximation, and two mechanisms responsible for opening the mGGA gaps are identified. First of all, the relatively large negative derivative of the functional form with respect to reduced kinetic energy tends to elevate the lowest unoccupied state. Second, the curvature of functional, which ensures that it is bounded, tends to lower the highest occupied state. Remarkably, these two mechanisms are found to be transferable over a large and diverse database of compounds. Density functional theory ; Kinetic energy ; Scaling ; Curvature ; Bounded function ; Orbital-free density functional theory ; Space (punctuation) ; Band gap ; Local-density approximation ; Physics ; Mathematics ; Chemistry ; Computational chemistry ; Classical mechanics ; Mathematical analysis ; Quantum mechanics ; Geometry ; Computer science Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Catalysis and Oxidation Reactions
Authors: Yue Zhang | Yang Li | Xiang Han | Ang Gao | Shuaijie Jing | Yuepeng Song
Source: Agriculture (article, 2023-03-31)
Field: Chemistry — Analytical Chemistry

A Study on Hyperspectral Apple Bruise Area Prediction Based on Spectral Imaging Achieving fast and accurate prediction of the fruit mechanical damage area is important to improve the accuracy and efficiency of apple quality grading. In this paper, the spectral data of all samples in the wavelength range from 376 to 1011 nm were collected, the sample set was divided by the physicochemical coeval distance method, and the spectral preprocessing methods were evaluated by establishing a full-wavelength artificial neural network model. The wavelength selection of spectral data was performed by competitive adaptive reweighted sampling, L1 parameter method, and the Pearson correlation coefficient method, and the partial least squares, artificial neural network, and support vector machine (Gaussian kernel) prediction models were established to predict the fruit bruise area size. The surface fitting was performed using the actual apple bruise area, and the regression surface equation of the damage time and damage height of the fruit was established. The results showed that (1) the preprocessing method of first-order difference + SG smoothing can make the prediction model more accurate; (2) the CARS-ANN prediction model has better prediction performance and higher operation efficiency, with the prediction set root mean square error of prediction and R-value of 0.1150 and 0.8675, respectively; (3) the sparrow search algorithm was used to optimize the model, which improved the accuracy of the prediction model. The root mean square error of prediction reached 0.0743 and The R-value reached 0.9739. (4) The relationship between spectral information, bruise area, damage time, and damage degree was obtained by combining the establishment of the fitted surface of the apple bruise area with the prediction model. This study is of application and extension value for the rapid nondestructive prediction of fruit bruise area. Bruise ; Mean squared error ; Hyperspectral imaging ; Mathematics ; Statistics ; Artificial neural network ; Pattern recognition (psychology) ; Support vector machine ; Correlation coefficient ; Computer science ; Artificial intelligence ; Algorithm Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Psidium guajava Extracts and Applications
Authors: Hamideh Hamedi | Nima Rezaei | Sohrab Zendehboudi
Source: Energies (article, 2023-12-15)
Field: Materials Science — Materials Chemistry

Investigation of Emulsified Oil Adsorption onto Functionalized Magnetic Nanoparticles—Kinetic and Isotherm Models Recently, considerable attention has been given to using magnetic nanoparticles (MNPs) for capturing oil from oil-in-water (O/W) emulsions, despite MNPs’ inherent instability and agglomeration. Their stabilization through changing surface chemistry is required to increase dispersivity. In this research, we use cetyltrimethylammonium bromide (CTAB) as a cationic surfactant to increase the positive surface charge of the particles, resulting in a better stability in the aqueous solution because of increased repulsive forces. The functionalized MNPs are characterized using transmission electron microscopy (TEM), zeta potential, and contact angle (CA) measurements. The aim of this study is to investigate the oil separation efficiency (SE) and equilibrium oil adsorption capacity of the synthesized particles, which are determined using gas chromatography analysis. We also study the adsorption behavior using isotherm and kinetic models. The SE values indicate the superior performance of MNP@CTAB for oil adsorption from dodecane-in-water nanoemulsion (SE = 99.80%) compared to the bare MNPs with SE of approximately 57.46%. These findings are attributed to the stronger electrostatic attraction between the MNP@CTAB having high positive charge and negatively charged oil droplets. The adsorption isotherm results using both linear and non-linear regression methods show that the Freundlich isotherm is the best fit to the experimental equilibrium data (with calculated R2 &gt; 0.97), verifying a multilayer heterogeneous adsorption. Moreover, the pseudo-first-order kinetic model describes the experimental equilibrium data in a greater congruence (R2 = 0.99), suggesting physical adsorption of oil onto MNPs through van der Waals and physical bonding, which is also confirmed through zeta potential measurements. Adsorption ; Freundlich equation ; Zeta potential ; Chemical engineering ; van der Waals force ; Aqueous solution ; Nanoparticle ; Chemistry ; Surface charge ; Pulmonary surfactant ; Contact angle ; Bromide ; Magnetic nanoparticles ; Materials science ; Chromatography ; Organic chemistry ; Physical chemistry ; Molecule Pickering emulsions and particle stabilization ; Characterization and Applications of Magnetic Nanoparticles ; Minerals Flotation and Separation Techniques
Authors: Théophile Gaudin | Adrien Benazzouz | Jean‐Marie Aubry
Source: Computational and Theoretical Chemistry (article, 2023-01-07)
Field: Chemistry — Spectroscopy

Robust definition and prediction of dispersive Hansen solubility parameter δD with COSMO-RS Chemistry ; COSMO-RS ; Hildebrand solubility parameter ; Thermodynamics ; Dielectric ; Solvation ; Solubility ; Conductor ; Simple (philosophy) ; Statistical physics ; Physical chemistry ; Quantum mechanics ; Physics ; Organic chemistry ; Molecule Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Haorui Zhang | Ping Luo | Xiaojun Huang
Source: Frontiers in Pharmacology (review, 2023-08-21)
Field: Materials Science — Biomaterials

Engineered nanomaterials enhance drug delivery strategies for the treatment of osteosarcoma Osteosarcoma (OS) is the most common malignant bone tumor in adolescents, and the clinical treatment of OS mainly includes surgery, radiotherapy, and chemotherapy. However, the side effects of chemotherapy drugs are an issue that clinicians cannot ignore. Nanomedicine and drug delivery technologies play an important role in modern medicine. The development of nanomedicine has ushered in a new turning point in tumor treatment. With the emergence and development of nanoparticles, nanoparticle energy surfaces can be designed with different targeting effects. Not only that, nanoparticles have unique advantages in drug delivery. Nanoparticle delivery drugs can not only reduce the toxic side effects of chemotherapy drugs, but due to the enhanced permeability retention (EPR) properties of tumor cells, nanoparticles can survive longer in the tumor microenvironment and continuously release carriers to tumor cells. Preclinical studies have confirmed that nanoparticles can effectively delay tumor growth and improve the survival rate of OS patients. In this manuscript, we present the role of nanoparticles with different functions in the treatment of OS and look forward to the future treatment of improved nanoparticles in OS. Nanomedicine ; Drug delivery ; Osteosarcoma ; Medicine ; Chemotherapy ; Radiation therapy ; Drug ; Nanoparticle ; Cancer research ; Nanotechnology ; Pharmacology ; Internal medicine ; Materials science Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Nanoplatforms for cancer theranostics
Authors: Rongcai Wang | Xisheng Jia | Zichang Liu | Enzhi Dong | Siyu Li | Zhonghua Cheng
Source: Eksploatacja i Niezawodnosc - Maintenance and Reliability (article, 2023-11-16)
Field: Chemistry — Analytical Chemistry

Conditional generative adversarial network based data augmentation for fault diagnosis of diesel engines applied with infrared thermography and deep convolutional neural network This paper tries to introduce a new intelligent method for the early fault diagnosis of diesel engines. Firstly, infrared thermography (IRT) is introduced into diesel engine condition monitoring, then infrared images of diesel engines in four health states, such as normal condition, single-cylinder misfire, multi-cylinder misfire and air filter blockage, are collected and the region of interest (ROI) of infrared images are extracted. Next, conditional generative adversarial network (CGAN) is deployed to perform data augmentation on infrared image datasets. Then, deep convolutional neural network (DCNN) and Softmax regression (SR) classifier are used for automatically extracting infrared image fault features and pattern recognition, respectively. Finally, a comparison with three deep learning (DL) models is performed. The validation results show that the data augmentation method proposed in the paper can significantly improve the early fault diagnosis accuracy, and DCNN has the best fault diagnosis effect and resistance to temperature fluctuation interference among the four DL models. Softmax function ; Convolutional neural network ; Thermography ; Artificial intelligence ; Deep learning ; Computer science ; Classifier (UML) ; Pattern recognition (psychology) ; Diesel fuel ; Artificial neural network ; Fault (geology) ; Infrared ; Computer vision ; Engineering ; Automotive engineering ; Geology Spectroscopy and Chemometric Analyses ; Thermography and Photoacoustic Techniques
Authors: Ihssen Abdelmomen | Marin Vincent | Frédéric Thiebaud | Julia Budzinski | Thierry Bastogne | Tarak Ben Zineb | Marc Engels‐Deutsch
Source: Materials (article, 2023-04-28)
Field: Materials Science — Materials Chemistry

Experimental Analysis of the Influence of Heat Treatments on the Flexibility of NiTi Alloy for Endodontic Instruments Manufacturing The flexibility of NiTi based endodontic files is improved by heat treatment, leading to lower risk of failure, ledges, and canal transportation during the preparation of curved root canals. The aim of this study is to investigate and clearly highlight the influence of every parameter of heat treatment on the flexibility of NiTi wires and thus of endodontic instruments. A full factorial Design of Experiment (DoE) and a designed bending-torsion bench following the ISO 3630-1 standard were used for this investigation. Temperature, holding time, and cooling method were selected as contributing factors, while maximum bending moment, hysteresis size, and stiffness during martensitic transformation were selected as outputs. Regression analysis was performed to estimate the relationship between contributing and output variables to assess how the experimentation fits with the model. The experimental results showed that wires heated at 425 °C for 30 min are more flexible. Moreover, heat treatment temperature is the most critical factor influencing the flexibility and hysteresis size of the NiTi wire followed by the holding time, while the cooling method has a negligible effect. The regression analysis showed that the model is effective at predicting the relationship between contributing factors, bending moment response, and hysteresis size. Materials science ; Nickel titanium ; Torsion (gastropod) ; Factorial experiment ; Flexibility (engineering) ; Hysteresis ; Composite material ; Structural engineering ; Mathematics ; Shape-memory alloy ; Statistics ; Engineering Shape Memory Alloy Transformations ; Endodontics and Root Canal Treatments
Authors: Qingying Hu | Wei Lu | Yuxin Guo | Wei He | Hui Luo | Yiming Deng
Source: Agriculture (article, 2023-07-27)
Field: Chemistry — Analytical Chemistry

Vigor Detection for Naturally Aged Soybean Seeds Based on Polarized Hyperspectral Imaging Combined with Ensemble Learning Algorithm To satisfy the increasing demand for soybeans, identifying and sorting high-vigor seeds before sowing is an effective way to improve the yield. Polarized hyperspectral imaging (PHI) technology is here proposed as a rapid, non-destructive method for detecting the vigor of naturally aged soybean seeds. First, the spectrum of 396.1–1044.1 nm was collected to automatically extract the region of interest (ROI). Then, first derivative (FD), Savitzky–Golay (SG), multiplicative scatter correction (MSC), and standard normal variate (SNV) preprocessed hyperspectral and polarized hyperspectral data (0°, 45°, 90°, and 135°) for the soybean seeds was obtained. Finally, the seed vigor prediction model based on polarized hyperspectral components such as I, Q, and U was constructed, and partial least squares regression (PLSR), back-propagation neural network (BPNN), generalized regression neural network (GRNN), support vector regression (SVR), random forest (RF), and blending ensemble learning were applied for modeling analysis. The results showed that the prediction accuracy when using PHI was improved to 93.36%, higher than that for the hyperspectral technique, with a prediction accuracy up to 97.17%, 98.25%, and 97.55% when using the polarization component of I, Q, and U, respectively. Hyperspectral imaging ; Random forest ; Support vector machine ; Artificial intelligence ; Pattern recognition (psychology) ; Partial least squares regression ; Mathematics ; Regression ; Artificial neural network ; Algorithm ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Soybean genetics and cultivation ; Leaf Properties and Growth Measurement