jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yan Duan | Lorena E. Rosaleny | Joana T. Coutinho | Silvia Giménez‐Santamarina | Allen Scheie | José J. Baldoví | Salvador Cardona‐Serra | Alejandro Gaita‐Ariño
Source: Nature Communications (article, 2022-12-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Data-driven design of molecular nanomagnets Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations. Nanomagnet ; Intuition ; Materials science ; Serendipity ; Inductive coupling ; Chemical physics ; Nanotechnology ; Computer science ; Chemistry ; Physics ; Magnetization Magnetism in coordination complexes ; Advanced NMR Techniques and Applications ; Lanthanide and Transition Metal Complexes
Authors: Giovana Signori-Iamin | Alexandre F. Santos | Marcos L. Corazza | Roberto Aguado | Quim Tarrés | Marc Delgado‐Aguilar
Source: Cellulose (article, 2022-09-17)
Field: Materials Science — Biomaterials

Prediction of cellulose micro/nanofiber aspect ratio and yield of nanofibrillation using machine learning techniques Abstract Predictive monitoring of two key properties of nanocellulose, aspect ratio and yield of nanofibrillation, would help manufacturers control and optimize production processes, given the uncertainty that still surrounds their influential factors. For that, 20 different types of cellulosic and lignocellulosic micro/nanofibers produced from spruce and pine softwoods, and by different pre-treatment and fibrillation techniques, were used as training and testing datasets aiming at the development and evaluation of three machine learning models. The models used were Random Forests (RF), Linear Regression (LR) and Artificial Neural Networks (ANN), broadening the scope of our previous work (Santos et al. in Cellulose 29:5609–5622, 2022. https://doi.org/10.1007/s10570-022-04631-5 ). Performance of these models were evaluated by comparing statistical parameters such as Mean Absolute Percentage Error (MAPE) and R². For the aspect ratio and the yield of nanofibrillation, inputs were chosen among these easily controlled or measured variables: Total lignin (wt%), Cellulose (wt%), Hemicellulose (wt%), Extractives (wt%), HPH Energy Consumption (kWh/kg), Cationic Demand (µeq/g), Transmittance at 600 nm and Consistency index (Ostwald-De Waele’s k ). In both cases, the ANN models trained here provided satisfactory estimates of aspect ratio (MAPE = 4.54% and R 2 = 0.96) and the yield of nanofibrillation (MAPE = 6.74% and R 2 = 0.98), being able to capture the effect of the applied energy along the fibrillation process. RF and LR models resulted in correlation coefficients of 0.93 and 0.95, respectively, for aspect ratio, while for yield of nanofibrillation the correlation coefficients were 0.87 and 0.92. Mean absolute percentage error ; Cellulose ; Nanofiber ; Yield (engineering) ; Hemicellulose ; Lignin ; Nanocellulose ; Pulp and paper industry ; Materials science ; Dewatering ; Machine learning ; Mathematics ; Biological system ; Statistics ; Composite material ; Artificial neural network ; Chemical engineering ; Computer science ; Chemistry ; Engineering ; Organic chemistry Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Nanocomposite Films for Food Packaging
Authors: Junming Han | Tong Li | Yun He | Quan Gao
Source: Mathematical Problems in Engineering (article, 2022-12-31)
Field: Chemistry — Analytical Chemistry

Using Machine Learning Approaches for Food Quality Detection Food quality detection is an important method for ensuring food safety. Efficient quality detection methods can improve the efficiency of food circulation and reduce storage and labor costs. Traditional methods use instrumentation, testing reagents, or manual labor. These methods take a long time to detect, are time-consuming and labor-intensive, and require professionals to operate. Fruit, as a high-value food that provides essential nutrition for human beings, is susceptible to spoilage during packaging, transportation, and sales, so the freshness and safety assurance of fruit are a hot and difficult area of current research. Therefore, for the detection of fruit freshness, this paper proposes an efficient and nondestructive way to detect fruit freshness by using the machine learning algorithm convolutional neural network (CNN). This paper shows that convolutional neural networks have good performance in identifying the freshness of fruits through extensive experimental results and discusses the overfitting of machine learning based on the experimental results. Overfitting ; Convolutional neural network ; Computer science ; Food safety ; Quality (philosophy) ; Food spoilage ; Machine learning ; Artificial intelligence ; Artificial neural network ; Food science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Alena Stsiapanava | Chenrui Xu | Shunsuke Nishio | Ling Han | Nao Yamakawa | Marta Carroni | Kathryn Tunyasuvunakool | John Jumper | Daniele de Sanctis | Bin Wu | Luca Jovine
Source: Nature Structural & Molecular Biology (article, 2022-03-01)
Field: Materials Science — Materials Chemistry

Structure of the decoy module of human glycoprotein 2 and uromodulin and its interaction with bacterial adhesin FimH Glycoprotein 2 (GP2) and uromodulin (UMOD) filaments protect against gastrointestinal and urinary tract infections by acting as decoys for bacterial fimbrial lectin FimH. By combining AlphaFold2 predictions with X-ray crystallography and cryo-EM, we show that these proteins contain a bipartite decoy module whose new fold presents the high-mannose glycan recognized by FimH. The structure rationalizes UMOD mutations associated with kidney diseases and visualizes a key epitope implicated in cast nephropathy. Tamm–Horsfall protein ; Glycoprotein ; Decoy ; Glycan ; Lectin ; Shigella dysenteriae ; Biology ; Bacterial adhesin ; Cell biology ; Escherichia coli ; Microbiology ; Computational biology ; Genetics ; Biochemistry ; Kidney ; Gene Enzyme Structure and Function ; Escherichia coli research studies ; Pediatric Urology and Nephrology Studies
Authors: Dominique Albert-Weiss | Ahmad Osman
Source: Sensors (article, 2022-01-06)
Field: Chemistry — Analytical Chemistry

Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach A pivotal topic in agriculture and food monitoring is the assessment of the quality and ripeness of agricultural products by using non-destructive testing techniques. Acoustic testing offers a rapid in situ analysis of the state of the agricultural good, obtaining global information of its interior. While deep learning (DL) methods have outperformed state-of-the-art benchmarks in various applications, the reason for lacking adaptation of DL algorithms such as convolutional neural networks (CNNs) can be traced back to its high data inefficiency and the absence of annotated data. Active learning is a framework that has been heavily used in machine learning when the labelled instances are scarce or cumbersome to obtain. This is specifically of interest when the DL algorithm is highly uncertain about the label of an instance. By allowing the human-in-the-loop for guidance, a continuous improvement of the DL algorithm based on a sample efficient manner can be obtained. This paper seeks to study the applicability of active learning when grading 'Galia' muskmelons based on its shelf life. We propose <i>k</i>-Determinantal Point Processes (<i>k</i>-DPP), which is a purely diversity-based method that allows to take influence on the exploration within the feature space based on the chosen subset <i>k</i>. While getting coequal results to uncertainty-based approaches when <i>k</i> is large, we simultaneously obtain a better exploration of the data distribution. While the implementation based on eigendecomposition takes up a runtime of O(n3), this can further be reduced to O(n·poly(k)) based on rejection sampling. We suggest the use of diversity-based acquisition when only a few labelled samples are available, allowing for better exploration while counteracting the disadvantage of missing the training objective in uncertainty-based methods following a greedy fashion. Artificial intelligence ; Computer science ; Machine learning ; Convolutional neural network ; Deep learning ; Algorithm Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Smart Agriculture and AI
Authors: Igor D. Zlotnikov | Alexander A. Ezhov | Rostislav A. Petrov | Maksim A. Vigovskiy | Olga Grigorieva | Natalya G. Belogurova | Еlena V. Kudryashova
Source: Pharmaceuticals (article, 2022-09-21)
Field: Materials Science — Biomaterials

Mannosylated Polymeric Ligands for Targeted Delivery of Antibacterials and Their Adjuvants to Macrophages for the Enhancement of the Drug Efficiency Bacterial infections and especially resistant strains of pathogens localized in macrophages and granulomas are intractable diseases that pose a threat to millions of people. In this paper, the theoretical and experimental foundations for solving this problem are proposed due to two key aspects. The first is the use of a three-component polymer system for delivering fluoroquinolones to macrophages due to high-affinity interaction with mannose receptors (CD206). Cytometry assay determined that 95.5% macrophage-like cells were FITC-positive after adding high-affine to CD206 trimannoside conjugate HPCD-PEI1.8-triMan, and 61.7% were FITC-positive after adding medium-affine ligand with linear mannose label HPCD-PEI1.8-Man. The second aspect is the use of adjuvants, which are synergists for antibiotics. Using FTIR and NMR spectroscopy, it was shown that molecular containers, namely mannosylated polyethyleneimines (PEIs) and cyclodextrins (CDs), load moxifloxacin (MF) with dissociation constants of the order of 10<sup>-4</sup>-10<sup>-6</sup> M; moreover, due to prolonged release and adsorption on the cell membrane, they enhance the effect of MF. Using CLSM, it was shown that eugenol (EG) increases the penetration of doxorubicin (Dox) into cells by an order of magnitude due to the creation of defects in the bacterial wall and the inhibition of efflux proteins. Fluorescence spectroscopy showed that 0.5% EG penetrates into bacteria and inhibits efflux proteins, which makes it possible to increase the maximum concentration of the antibiotic by 60% and maintain it for several hours until the pathogens are completely neutralized. Regulation of efflux is a possible way to overcome multiple drug resistance of both pathogens and cancer cells. Drug ; Pharmacology ; Drug delivery ; Antibiotics ; Targeted drug delivery ; Medicine ; Chemistry ; Biochemistry Nanoparticle-Based Drug Delivery ; Multicomponent Synthesis of Heterocycles ; Synthesis and biological activity
Authors: Weihua Gong | Jie Hu | Zhaowei Wang | Yubin Wei | Yanfang Li | Tingting Zhang | Qinduan Zhang | Tongyu Liu | Yanong N. Ning | Wei Zhang | K. T. V. Grattan
Source: Frontiers in Physics (article, 2022-11-14)
Field: Chemistry — Spectroscopy

Recent advances in laser gas sensors for applications to safety monitoring in intelligent coal mines Due to the extremely complex working conditions, various health and safety hazards are present in underground coal mines, which cause economic losses and heavy casualties. Among these hazards, methane gas explosion and coal combustion are recognized as the two major hazards to miners. Traditional electronic sensors in mine safety monitoring systems have problems such as low precision, a large amount of maintenance, and monitoring dead zones. In the past decade, gas sensors based on tunable diode laser absorption spectroscopy (TDLAS) have been extensively studied and tailored for use in the coal mine industry because of their advantages of high sensitivity, high stability, fast response, intrinsic safety, and remote monitoring. This invited paper introduces the recent progress and typical applications of TDLAS-based methane sensors, carbon monoxide sensors, and multi-gas monitoring systems in coal mine gas monitoring, fire prevention, and early warning in intelligent coal mines. Coal mining ; Safety monitoring ; Methane ; Environmental science ; Coal ; Warning system ; Mine safety ; Waste management ; Engineering ; Mining engineering ; Process engineering ; Telecommunications ; Chemistry Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Gas Sensing Nanomaterials and Sensors
Authors: Ayushman Gadnayak | Budheswar Dehury | Ananya Nayak | Sudipta Jena | Ambika Sahoo | Pratap Chandra Panda | Asit Ray | Sanghamitra Nayak
Source: PLoS ONE (article, 2022-07-22)
Field: Chemistry — Organic Chemistry

‘Mechanistic insights into 5-lipoxygenase inhibition by active principles derived from essential oils of Curcuma species: Molecular docking, ADMET analysis and molecular dynamic simulation study Inflammation is caused by a cascade of events, one of which is the metabolism of arachidonic acid, that begins with oxidation by the enzyme 5-lipoxygenase. 5-Lipoxygenase (5-LOX) plays an important role in the inflammation process by synthesizing leukotrienes and several lipid mediators and has emerged as a possible therapeutic target for treatment of inflammatory diseases such as asthma and rheumatoid arthritis. Most of the existing 5-LOX inhibitors are synthetic and exhibit adverse side effects. In view of this, there is need to search for an alternate source of 5-LOX inhibitor with minimal side effects. The essential oil of several species of Curcuma has received considerable attention in recent times in traditional system of medicine especially for treating various inflammatory disorders. Therefore, the present study was carried out to screen the most potential 5-LOX inhibitors from essential oil components of Curcuma species and elucidate their mechanisms of action through computational biology approaches. Twenty-three phytoconstituents derived from the essential oil of Curcuma species were docked and their predictive binding energies were calculated to select the best possible ligand for 5-LOX. The top 8 ranked compounds from docking was tested for drug-likeness properties, bioactivity score, and toxicity analysis. The phytoconstituents such as α-turmerone, β-turmerone, α-terpineol and dihydrocarveolshowed the best binding affinity with 5-LOX and displayed favorable physicochemical properties. Molecular dynamics simulation in POPC lipid bilayers was carried out to understand the intrinsic dynamics and flexibility of the 5-LOX (apo) and 5-LOX-complex (α-terpineol, α-turmerone, β-turmerone and dihydrocarveol) systems. The molecular dynamic results showed that these 4 phytoconstituents interacted stably with the 5-LOX active site residues and the important bonds that were observed in the initial ligand docked compounds did not alter during the course of simulation. In general, our integrative computational approach demonstrated that the natural compounds like α-turmerone, β-turmerone, α-terpineol, and dihydrocarveol could be considered for designing specific anti-inflammatory drugs using structure-based drug design. Curcuma ; Docking (animal) ; Lipoxygenase ; Chemistry ; Biochemistry ; Arachidonate 5-lipoxygenase ; Molecular dynamics ; Pharmacology ; Enzyme ; Arachidonic acid ; Biology ; Traditional medicine ; Medicine ; Computational chemistry Synthesis and biological activity ; Computational Drug Discovery Methods ; Bioactive Compounds and Antitumor Agents
Authors: David Nugroho | Chayanee Keawprom | Saksit Chanthai | Won‐Chun Oh | Rachadaporn Benchawattananon
Source: Nanomaterials (article, 2022-01-26)
Field: Materials Science — Materials Chemistry

Highly Sensitive Fingerprint Detection under UV Light on Non-Porous Surface Using Starch-Powder Based Luminol-Doped Carbon Dots (N-CDs) from Tender Coconut Water as a Green Carbon Source This study aims to synthesize carbon dots from a natural resource and will be used to detect a latent fingerprint on a non-porous surface. The carbon dots (CDs) were prepared by adding luminol to coconut water and ethanol via a hydrothermal method. Luminol enhances the chemiluminescence of the CDs, which show more distinct blue light under a UV lamp compared with bare CDs. To detect the latent fingerprint, luminol carbon dots (N-CDs) were combined with commercial starch and stirred at room temperature for 24 h. Their characteristics and optical properties were measured using EDX-SEM, HR-TEM, FTIR, XPS, UV-visible absorption, and fluorescence. In this research, it was found that the N-CDs had a d-spacing of 0.5 nm and a size of 12.9 nm. The N-CDs had a fluorescence intensity 551% higher than the standard normally used. N-CDs can be used to detect latent fingerprints on a non-porous surface and are easy to detect under a UV lamp at 395 nm. Therefore, luminol has a high potential to increase sensitive and stable traces of chemiluminescence from the green CDs for forensic latent fingerprint detection. Materials science ; Carbon fibers ; Fluorescence ; Luminol ; Chemiluminescence ; Visible spectrum ; Absorption (acoustics) ; Analytical Chemistry (journal) ; Chemical engineering ; Nuclear chemistry ; Chemistry ; Chromatography ; Optoelectronics ; Optics ; Composite material ; Composite number Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Melamine detection and toxicity
Authors: Xiaoyuan Sha | Leung Chan | Xiaoyi Fan | Penghao Guo | Tianfeng Chen | Lian Liu | Jingxiang Zhong
Source: International Journal of Nanomedicine (article, 2022-03-01)
Field: Chemistry — Organic Chemistry

Thermosensitive Tri-Block Polymer Nanoparticle-Hydrogel Composites as Payloads of Natamycin for Antifungal Therapy Against Fusarium Solani Gel@PLGA-PEI-PEG@NAT was shown to be a safe and effective nanodrug delivery system for NAT. It has great potential to improve the cure rate of fungal keratitis, reduce the administration frequency during the treatment process, and improve patient compliance. Natamycin ; Antifungal ; Fusarium solani ; Polymer ; Cure rate ; Fusarium Antimicrobial agents and applications ; Advanced Drug Delivery Systems ; Hydrogels: synthesis, properties, applications
Authors: Elisabet Fuguet | Clara Ràfols | Meritxell Mañé | Rebeca Ruiz | Elisabeth Bosch
Source: Talanta (article, 2022-11-13)
Field: Chemistry — Organic Chemistry

Acidity constants of hydroxyl groups placed in several flavonoids: Two flavanones, two flavones and five flavonols Acidity constants (pKa) of nine flavonoids have been spectrophotometrically determined and the obtained values carefully contrasted with those derived from various experimental approaches given in literature, as well as with the ones predicted by Percepta and SPARC programs. To obtain robust pKa values, titrations in both pH ways, from acid to base and vice-versa, have been performed. The well-known instability of most flavonoids in basic media originates some discrepancies between obtained pKa by both titration ways and also with those coming from different experimental approaches previously published. This study tries to overcome the mentioned lack of integrity of several flavonoids avoiding measurements at high pH values or designing titrations at higher speed, which are able to cover the whole pH range with a minimum damage of studied compound. Suitable spectrophotometric titrations in pure water and, for instance, in methanol/water mixtures have been carried out. Achieved results allow the pKa assignation to hydroxyl groups belonging to two flavanones (Hesperetin and Naringenin), two flavones (Apigenin and Crysin) and five flavonols (Fisetin, Galangin, Kaempherol, Morin and Quercetin). Chemistry ; Flavones ; Titration ; Flavonols ; Hesperetin ; Fisetin ; Morin ; Galangin ; Naringenin ; Apigenin ; Quercetin ; Chrysin ; Flavonoid ; Organic chemistry ; Chromatography ; Kaempferol ; Antioxidant Free Radicals and Antioxidants ; Computational Drug Discovery Methods ; Phytochemicals and Antioxidant Activities
Authors: Nurlan Zhangabay | Ulanbator Suleimenov | Akmaral Utelbayeva | Alexandr Kolesnikov | Kanat Baibolov | Kuanysh Imanaliyev | Arman Moldagaliyev | Galymzhan Karshyga | Bolat Duissenbekov | Роман Федюк | Mugahed Amran
Source: Buildings (article, 2022-09-14)
Field: Materials Science — Materials Chemistry

Analysis of a Stress-Strain State of a Cylindrical Tank Wall Vertical Field Joint Zone In the study, experimental and theoretical studies were carried out to assess the influence of the vertical mounting joint zone of the tank on the stress-strain state of the defect zone. Thus, experimental tests of models of a tank wall fragment with an imperfection of the mounting joint evaluated the stress-strain state of the mounting joint zone and established the dependence of the stress concentration in the joint zone on the deflection, the width of the zone and the thickness of the tank wall. It is shown that with a 50 mm bending boom, the annular stresses increase by 1.3 times than with a 30 mm bending boom and the meridional stresses increase by 1.16 times. The same nature of the increase is observed with the stress concentration indicator. By numerical analysis of the stress-strain state of tanks with joint imperfections in the ANSYS medium, the stress-strain state of the tank is estimated for various values of the joint bending parameters ς and ξ. The dependences of the stress concentration coefficient on the geometric dimensions of the imperfection, radius and thickness of the tank wall are also obtained. From the results of calculating the stress concentration coefficient, with an increase in the dimensionless parameters ς and ξ, the values of the stress concentration coefficient Kσ increase by 1.35 times. As a result of the calculations, an interpolation polynomial (5), approximating the stress concentration coefficient Kσ, is obtained, which can be used to estimate the strength, durability and residual resource of the tank. In addition, the obtained results can be used to normalize the limiting dimensions of the imperfection of the joint and to establish the values of the coefficient, taking into account the peculiarities of the work of structures at stress concentrations. Materials science ; Stress (linguistics) ; Joint (building) ; Bending moment ; Structural engineering ; Dimensionless quantity ; Stress concentration ; Stress field ; Stress–strain curve ; Mechanics ; Composite material ; Finite element method ; Deformation (meteorology) ; Engineering ; Physics Structural mechanics and materials ; Mining and Gasification Technologies ; Industrial Engineering and Technologies