jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mengyu He | Jin Chen | Li Cheng | Zeyi Cai | Dongdong Peng | Jimmy Xiangji Huang | Jun Wang | Yuanning Zhai | Hengnian Qi | Chu Zhang
Source: Food Chemistry X (article, 2024-05-17)
Field: Chemistry — Analytical Chemistry

Simultaneous determination of pigments of spinach (Spinacia oleracea L.) leaf for quality inspection using hyperspectral imaging and multi-task deep learning regression approaches Rapid and accurate determination of pigment content is important for quality inspection of spinach leaves during storage. This study aimed to use hyperspectral imaging at two spectral ranges (visible/near-infrared, VNIR: 400-1000 nm; NIR: 900-1700 nm) to simultaneously determine the pigment (chlorophyll <i>a</i>, chlorophyll <i>b</i>, total chlorophyll, and carotenoids) content in spinach stored at different durations and conditions (unpackaged and packaged). Partial least squares (PLS), back propagation neural network (BPNN) and convolutional neural network (CNN) were used to establish single-task and multi-task regression models. Single-task CNN (STCNN) models and multi-task CNN (MTCNN) models obtained better performances than the other models. The models using VNIR spectra were superior to those using NIR spectra. The overall results indicated that hyperspectral imaging with multi-task learning could predict the quality attributes of spinach simultaneously for spinach quality inspection under various storage conditions. This research will guide food quality inspection by simultaneously inspecting multiple quality attributes. Spinacia ; Hyperspectral imaging ; Spinach ; Artificial intelligence ; Task (project management) ; Pigment ; Quality (philosophy) ; Carotenoid ; Pattern recognition (psychology) ; Mathematics ; Chemistry ; Computer science ; Food science ; Engineering ; Biochemistry ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Mengyang Wang | Yiyue Hong | Xiaobing Fu | Xiaoyan Sun
Source: Bioactive Materials (article, 2024-05-30)
Field: Materials Science — Biomaterials

Advances and applications of biomimetic biomaterials for endogenous skin regeneration Endogenous regeneration is becoming an increasingly important strategy for wound healing as it facilitates skin's own regenerative potential for self-healing, thereby avoiding the risks of immune rejection and exogenous infection. However, currently applied biomaterials for inducing endogenous skin regeneration are simplistic in their structure and function, lacking the ability to accurately mimic the intricate tissue structure and regulate the disordered microenvironment. Novel biomimetic biomaterials with precise structure, chemical composition, and biophysical properties offer a promising avenue for achieving perfect endogenous skin regeneration. Here, we outline the recent advances in biomimetic materials induced endogenous skin regeneration from the aspects of structural and functional mimicry, physiological process regulation, and biophysical property design. Furthermore, novel techniques including <i>in situ</i> reprograming, flexible electronic skin, artificial intelligence, single-cell sequencing, and spatial transcriptomics, which have potential to contribute to the development of biomimetic biomaterials are highlighted. Finally, the prospects and challenges of further research and application of biomimetic biomaterials are discussed. This review provides reference to address the clinical problems of rapid and high-quality skin regeneration. Regeneration (biology) ; Materials science ; Nanotechnology ; Biomedical engineering ; Engineering ; Cell biology ; Biology Silk-based biomaterials and applications ; Electrospun Nanofibers in Biomedical Applications ; 3D Printing in Biomedical Research
Authors: Rafael O. Moreno‐Tortolero | Yijie Luo | Fabio Parmeggiani | Nick Skaer | Robert Walker | Louise C. Serpell | Chris Holland | Sean A. Davis
Source: Communications Biology (article, 2024-06-29)
Field: Materials Science — Biomaterials

Molecular organization of fibroin heavy chain and mechanism of fibre formation in Bombyx mori Fibroins' transition from liquid to solid is fundamental to spinning and underpins the impressive native properties of silk. Herein, we establish a fibroin heavy chain fold for the Silk-I polymorph, which could be relevant for other similar proteins, and explains mechanistically the liquid-to-solid transition of this silk, driven by pH reduction and flow stress. Combining spectroscopy and modelling we propose that the liquid Silk-I fibroin heavy chain (FibH) from the silkworm, Bombyx mori, adopts a newly reported β-solenoid structure. Similarly, using rheology we propose that FibH N-terminal domain (NTD) templates reversible higher-order oligomerization driven by pH reduction. Our integrated approach bridges the gap in understanding FibH structure and provides insight into the spatial and temporal hierarchical self-assembly across length scales. Our findings elucidate the complex rheological behaviour of Silk-I, solutions and gels, and the observed liquid crystalline textures within the silk gland. We also find that the NTD undergoes hydrolysis during standard regeneration, explaining key differences between native and regenerated silk feedstocks. In general, in this study we emphasize the unique characteristics of native and native-like silks, offering a fresh perspective on our fundamental understanding of silk-fibre production and applications. Fibroin ; Bombyx mori ; SILK ; Rheology ; Polymer science ; Materials science ; Chemistry ; Chemical engineering ; Nanotechnology ; Composite material ; Biochemistry Silk-based biomaterials and applications ; Adhesion, Friction, and Surface Interactions ; Invertebrate Immune Response Mechanisms
Authors: Georgi Georgiev | Stanislav Baluschev | Petar Eftimov | Mihaela Bacheva | Katharina Landfester
Source: Colloids and Interfaces (review, 2024-11-18)
Field: Materials Science — Surfaces, Coatings and Films

Addressing the Apparent Controversies Between the Contact Angle-Based Models for Estimation of Surface Free Energy: A Critical Review The most popular contact angle (CA)-based approaches for determination of solid surface free energy (SFE) are considered: (i) single liquid methods, mainly of Neumann and Chibowski, (ii) the multiple liquids approach of Owens–Wendt–Rabel–Kaelble (OWRK), and (iii) van Oss-Chaudhury–Good (vOCG) acid–base model. Evaluations based on Neumann and Chibowski models agree between each other. Under the assumption of equilibrium “wet wetting” (i.e., presence of saturated precursor film ahead of the drop), the model of Chibowski transforms in Lipatov’s interfacial equilibrium rule, i.e., the Antonow rule derived for the ternary point solid–liquid–gas. Very good agreement is observed between single and multiple liquids models where OWRK/vOCG values can be viewed as a mean of the individual SFE adopted by the solid with each of the wetting probes. Both approaches (single and multiple liquids) can be used in conjunction to evaluate SFE dispersion and polar components and to elucidate hydrophobicity and hydrophilicity. The implementation of apparently fully non-polar liquids (diiodomethane, bromonaphthalene) in OWRK and vOCG is practically and theoretically suspect. CA-based estimates represent apparent SFE determined by the interactions of both the solid surface and the probing liquid, which are very useful to elucidate the energy, chemistry and dynamics of the solid surface. Contact angle ; Estimation ; Surface (topology) ; Energy (signal processing) ; Econometrics ; Mathematics ; Physics ; Engineering ; Statistics ; Thermodynamics ; Geometry Surface Modification and Superhydrophobicity ; High voltage insulation and dielectric phenomena ; Adhesion, Friction, and Surface Interactions
Authors: Hui Jiang | Ziyu Wang | Jihong Deng | Zhidong Ding | Quansheng Chen
Source: Journal of Food Science (article, 2024-10-04)
Field: Chemistry — Analytical Chemistry

Quantitative detection of heavy metal Cd in vegetable oils: A nondestructive method based on Raman spectroscopy combined with chemometrics Heavy metal contaminants in vegetable oils can cause irreversible damage to human health. In this study, the quantitative detection of Cd in vegetable oils was investigated based on Raman spectroscopy combined with chemometric methods. The necessary preprocessing of the Raman signal was performed using baseline calibration and the Savitzky-Golay method. Three variable optimization methods were applied to the preprocessed Raman spectra. Namely, bootstrap soft shrinkage, multiple feature spaces ensemble strategy with least absolute shrinkage and selection operator, and competitive adaptive reweighted sampling (CARS), respectively. Partial least squares regression (PLSR) modeling for the determination of Cd in vegetable oils. The results show that three variable optimization algorithms improved the predictive performance of the model. Among them, the CARS-PLSR model has strong generalization performance and robustness. Its prediction coefficient of determination ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:msubsup><mml:mi>R</mml:mi> <mml:mi>P</mml:mi> <mml:mn>2</mml:mn></mml:msubsup> <mml:annotation>$R_{\mathrm{P}}^2$</mml:annotation></mml:semantics> </mml:math> ) was 0.9995, the root mean square error of prediction was 0.3533 mg/kg, and the relative prediction deviation was 44.3748, respectively. In summary, rapid quantitative analysis of Cd contamination in vegetable oils can be realized based on Raman spectroscopy combined with chemometrics. Chemometrics ; Partial least squares regression ; Raman spectroscopy ; Biological system ; Analytical Chemistry (journal) ; Calibration ; Chemistry ; Feature selection ; Mean squared error ; Mathematics ; Chromatography ; Statistics ; Computer science ; Artificial intelligence ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Electrochemical Analysis and Applications
Authors: Thinesh Sharma Balakrishnan | Mohamed Thariq Hameed Sultan | Farah Syazwani Shahar | Suhas Yeshwant Nayak | Ain Umaira Md Shah | Tamer A. Sebaey | Adi Azriff Basri
Source: Journal of Natural Fibers (review, 2024-01-17)
Field: Materials Science — Polymers and Plastics

Plant Fiber Reinforcements as Alternatives in Pultruded FRP Composites Manufacturing: A Review Recent developments of green technology promote the rising attraction toward developing high-performance and environmentally friendly pultruded products from naturally derived resources. Some factors that attract attention to developing pultruded biocomposites are their lightweight properties, recyclability, and economical and environmentally superior alternatives to synthetic fibers in commercial applications. Researchers have studied that the environmental crisis caused by conventional synthetic materials can be reduced significantly by using sustainable materials instead. This paper aims to review the potential of plant fibers to be used in pultruded composite manufacturing to reduce and replace the use of synthetic materials in pultruded structures. It was found that kenaf and jute fibers have been extensively studied in pultruded plant fiber reinforced composites and pultruded glass/plant fiber reinforced hybrid composites for their mechanical and physical properties under various test parameters. Overall, pultruded PFCs have recorded good mechanical properties but have limitations in water absorption properties for outdoor applications. An overview of the optimum process parameters, limitations, and potential applications of pultruded PFCs are also outlined. Finally, this review summarizes the future scopes and expectations, providing researchers and industrialists with a vision for deeper investigation in developing pultruded PFCs. Pultrusion ; Kenaf ; Materials science ; Fibre-reinforced plastic ; Composite material ; Environmentally friendly ; Fiber ; Biocomposite ; Synthetic fiber ; Composite number Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; Nanocomposite Films for Food Packaging
Authors: So Yul Kim | In Young Kim | Seong‐Hoon Park | Minsung Hwangbo | Soon Hwangbo
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Novel ultrasonic technology for advanced oxidation processes of water treatment Textile wastewater accounts for a significant proportion of industrial wastewater worldwide. In particular, dye wastewater accounts for a large proportion and consists of non-degradable dyes, which are substances resistant to biodegradation. Methylene blue is a representative example of such non-degradable dyes. It is not biologically degraded and exhibits toxicity. Various methods for their decomposition are currently being studied. Advanced oxidation processes (AOPs), which generate highly reactive hydroxyl radicals that oxidize and degrade pollutants, have been actively studied. Particularly, the photocatalytic degradation method using TiO<sub>2</sub> nanoparticles is one of the most actively studied fields; however, there are still concerns regarding the toxicity of nanoparticles. Research is currently being conducted on AOPs using the cavitation phenomenon of ultrasonic waves. However, achieving high efficiency using existing ultrasonic equipment is difficult. Therefore, in this study, we evaluated a new water treatment technology through AOPs using a focused ultrasonic system with a cylindrical piezoelectric ceramic structure. After determining the optimal conditions for degradation, the degradation process was evaluated as a useful tool for mitigating the toxicity of methylene blue. We found that, under the optimal conditions of 100 W intensity at a frequency of 400 kHz, this system is a helpful instrument for degradation and a new water treatment technology suitable for removing ecotoxicity and genotoxicity. Wastewater ; Ultrasonic sensor ; Textile ; Industrial wastewater treatment ; Pulp and paper industry ; Textile industry ; Process engineering ; Environmental science ; Sewage treatment ; Waste management ; Materials science ; Environmental engineering ; Engineering ; Acoustics ; Composite material ; Geography Ultrasound and Cavitation Phenomena ; Advanced oxidation water treatment ; Dye analysis and toxicity
Authors: Wenzhi Huang | Shuai Huang | Yanpeng Fang | Tianyu Zhu | Feiyi Chu | Qianhui Liu | Kunqian Yu | Fei Chen | Jie Dong | Wenbin Zeng
Source: Advanced Science (article, 2024-07-17)
Field: Chemistry — Physical and Theoretical Chemistry

AI‐Powered Mining of Highly Customized and Superior ESIPT‐Based Fluorescent Probes Excited-state intramolecular proton transfer (ESIPT) has attracted great attention in fluorescent sensors and luminescent materials due to its unique photobiological and photochemical features. However, the current structures are far from meeting the specific demands for ESIPT molecules in different scenarios; the try-and-error development method is labor-intensive and costly. Therefore, it is imperative to devise novel approaches for the exploration of promising ESIPT fluorophores. This research proposes an artificial intelligence approach aiming at exploring ESIPT molecules efficiently. The first high-quality ESIPT dataset and a multi-level prediction system are constructed that realized accurate identification of ESIPT molecules from a large number of compounds under a stepwise distinguishing from conventional molecules to fluorescent molecules and then to ESIPT molecules. Furthermore, key structural features that contributed to ESIPT are revealed by using the SHapley Additive exPlanations (SHAP) method. Then three strategies are proposed to ensure the ESIPT process while keeping good safety, pharmacokinetic properties, and novel structures. With these strategies, >700 previously unreported ESIPT molecules are screened from a large pool of 570 000 compounds. The ESIPT process and biosafety of optimal molecules are successfully validated by quantitative calculation and experiment. This novel approach is expected to bring a new paradigm for exploring ideal ESIPT molecules. Computer science ; Intramolecular force ; Molecule ; Process (computing) ; Fluorescence ; Chemistry Photochemistry and Electron Transfer Studies ; Luminescence and Fluorescent Materials ; Photochromic and Fluorescence Chemistry
Authors: George-Alexandru Croitoru | Adelina-Gabriela Niculescu | Dragoș Epistatu | Dan Eduard Mihăiescu | Alexandru Mihai Antohi | Alexandru Mihai Grumezescu | Carmen-Larisa Nicolae
Source: Applied Sciences (article, 2024-10-04)
Field: Materials Science — Biomaterials

Nanostructured Drug Delivery Systems in Immunotherapy: An Updated Overview of Nanotechnology-Based Therapeutic Innovations Using nanostructured drug delivery systems has attracted increasing interest in immunotherapeutic approaches. The intrinsic immunomodulatory properties and versatility of nanoparticles used as carriers were consistently reported to augment treatment efficiency as nanoscaled materials increase drug accumulation at the desired site, enhance cell internalization, and improve therapeutic outcomes. Thus, numerous studies have exploited the potential use of nanostructured drug delivery vehicles in delivering different cargo as a promising alternative for treating conditions like cancer, autoimmune diseases, infectious diseases, and allergic and immune disorders. In this context, this paper presents nanostructured drug delivery systems as a solid basis for immunotherapeutic innovations, highlighting their advantages for improving treatment strategies, reviewing their clinical applications, and discussing existing challenges and ways to overcome them. Drug delivery ; Nanotechnology ; Materials science ; Medicine Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; RNA Interference and Gene Delivery
Authors: Gaurav Arya | William F. Li | Charles Roques‐Carmes | Marin Soljačić | Steven G. Johnson | Zin Lin
Source: ACS Photonics (article, 2024-04-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing We present a framework for the end-to-end optimization of metasurface imaging systems that reconstruct targets using compressed sensing, a technique for solving underdetermined imaging problems when the target object exhibits sparsity (e.g., the object can be described by a small number of nonzero values, but the positions of these values are unknown). We nest an iterative, unapproximated compressed sensing reconstruction algorithm into our end-to-end optimization pipeline, resulting in an interpretable, data-efficient method for maximally leveraging metaoptics to exploit object sparsity. We apply our framework to super-resolution imaging and high-resolution depth imaging with a phase-change material. In both situations, our end-to-end framework effectively optimizes metasurface structures for compressed sensing recovery, automatically balancing a number of complicated design considerations to select an imaging measurement matrix from a complex, physically constrained manifold with millions of dimensions. The optimized metasurface imaging systems are robust to noise, significantly improving over random scattering surfaces and approaching the ideal compressed sensing performance of a Gaussian matrix, showing how a physical metasurface system can demonstrably approach the mathematical limits of compressed sensing. Compressed sensing ; Underdetermined system ; Computer science ; Pipeline (software) ; Iterative reconstruction ; Gaussian ; Optimization problem ; Algorithm ; Artificial intelligence ; Computer vision ; Physics Metamaterials and Metasurfaces Applications ; Random lasers and scattering media ; Underwater Acoustics Research
Authors: Yinsheng Zhang | Xudong Yang | Yongbo Cheng | Xiao‐Jun Wu | Xiulan Sun | Ruiqi Hou | Haiyan Wang
Source: Current Research in Food Science (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Fruit freshness detection based on multi-task convolutional neural network This study proves that MTL exploits the mutual correlation between two or more relevant tasks and can maximally share their underlying feature extraction process. we envision this approach to be extended to other domains that involve multiple interconnected tasks. Convolutional neural network ; Computer science ; Task (project management) ; Artificial intelligence ; Deep learning ; Machine learning ; Artificial neural network ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Currency Recognition and Detection
Authors: Gary C. Jensen | Makena K. Janis | Hazel N. Nguyen | O. David | Melissa L. Zastrow
Source: ACS Sensors (review, 2024-04-08)
Field: Chemistry — Electrochemistry

Fluorescent Protein-Based Sensors for Detecting Essential Metal Ions across the Tree of Life Genetically encoded fluorescent metal ion sensors are powerful tools for elucidating metal dynamics in living systems. Over the last 25 years since the first examples of genetically encoded fluorescent protein-based calcium indicators, this toolbox of probes has expanded to include other essential and non-essential metal ions. Collectively, these tools have illuminated fundamental aspects of metal homeostasis and trafficking that are crucial to fields ranging from neurobiology to human nutrition. Despite these advances, much of the application of metal ion sensors remains limited to mammalian cells and tissues and a limited number of essential metals. Applications beyond mammalian systems and in vivo applications in living organisms have primarily used genetically encoded calcium ion sensors. The aim of this Perspective is to provide, with the support of historical and recent literature, an updated and critical view of the design and use of fluorescent protein-based sensors for detecting essential metal ions in various organisms. We highlight the historical progress and achievements with calcium sensors and discuss more recent advances and opportunities for the detection of other essential metal ions. We also discuss outstanding challenges in the field and directions for future studies, including detecting a wider variety of metal ions, developing and implementing a broader spectral range of sensors for multiplexing experiments, and applying sensors to a wider range of single- and multi-species biological systems. Nanotechnology ; Fluorescent protein ; Metal ions in aqueous solution ; Toolbox ; Fluorescence ; Living systems ; Computer science ; Biochemical engineering ; Chemistry ; Ion ; Materials science ; Green fluorescent protein ; Biochemistry ; Physics ; Engineering ; Artificial intelligence Electrochemical Analysis and Applications ; Trace Elements in Health ; Molecular Sensors and Ion Detection