jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Petr A. Buikin | Анна В. Вологжанина | Аlexander А. Korlyukov
Source: Molbank (article, 2024-01-26)
Field: Chemistry — Physical and Theoretical Chemistry

Sumatriptan Succinate Hemi(Ethanol Solvate) 1-(3-(2-(Dimethylammonio)ethyl)-1H-indol-5-yl)-N-methylmethanesulfonamide succinate (sumatriptan succinate, HSum+·HSucc−) is a serotonin receptor agonist used to treat migraines. By the recrystallization of this substance from ethanol, its hemi(ethanol solvate), HSum+·HSucc−·0.5EtOH, was obtained. The solid was characterized by X-ray diffraction and FT-IR spectroscopy. In HSum+·HSucc−·0.5EtOH, solvent molecules link succinate anions into infinite O–H…O bonded chains, which are further connected by N–H…O interactions with cations into H-bonded layers. Chemistry ; Ethanol ; Sumatriptan ; Combinatorial chemistry ; Organic chemistry ; Stereochemistry ; Biochemistry ; Receptor ; Agonist Crystallography and molecular interactions ; Crystal structures of chemical compounds ; Radioactive element chemistry and processing
Authors: S.A. Waheed | Fakiha Nazakat | Nasir Abbas | Muhammad Sajid Nadeem | Sidra Ghafoor | Ghulam Shabir | Aamer Saeed
Source: FRONTIERS IN CHEMICAL SCIENCES (article, 2024-12-30)
Field: Chemistry — Spectroscopy

Synthesis of 2-(4-Methyl-Phenoxymethyl) Benzoic Acid; Cresol and its Metal Coordinate Complexes A series of phenoxymethylbenzoic acid derivatives were synthesized by reacting p-cresol with phthalide. The resulting phenoxymethyl benzoic acid was converted into corresponding acid chloride by reacting with cyanuric chloride. These phenoxymethyl benzoyl chlorides were then reacted with various aminobenzenesulfonamides and synthesize d new sulfonamide derivatives. The targeted sulfonamides were subjected to structural characterization by contemporary spectroscopic techniques like UV-visible and FT-IR. The presence of a peak at 3400/cm confirmed the existence of amide functionality, and furthermore , the broad peak at1250/cm showed that the sulfone group is present in the molecule. Benzoic acid ; Cresol ; Chemistry ; Metal ; p-Cresol ; Organic chemistry ; Phenol Analytical Chemistry and Chromatography
Authors: Mukilan Poyyamozhi | Balasubramanian Murugesan | R Narayanamoorthi | Digvijay Pandey | Ahmed Emara
Source: Materials (article, 2024-11-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Transmission and Reflection Properties of Iron Pyrite-Epoxy Resin Composite for Electromagnetic Applications This study examines the electromagnetic properties of a composite material composed of iron pyrite (FeS<sub>2</sub>) and epoxy resin, mixed in a 3:2 weight ratio to create a 10 cm<sup>3</sup> cube. The research analyzes transmission and reflection coefficients and band gap parameters to determine its viability as an antenna substrate for electromagnetic wave applications. The composite displays a tunable band gap of 1.3 eV, enabling selective absorption and emission of electromagnetic radiation. The transmission coefficient achieved 90% throughout a frequency range of 1 GHz to 15 GHz, whilst the reflection coefficient was measured at 10%, significantly reducing reflecting losses. The epoxy resin binder was essential for preserving structural integrity and augmenting the dielectric characteristics of the composite, thereby raising transmission efficiency. UV-Vis spectroscopy showed an absorption value of 0.875% at the band gap, indicating efficient interaction with UV energy. The S21 transmission coefficient ranged from -10 dB to -80 dB, with a maximum of -40 dB at 6 GHz, indicating strong energy transfer capability for antenna applications. The S21 values exhibited negligible signal attenuation between 2 GHz and 7 GHz, indicating the material's exceptional suitability for antenna substrates necessitating dependable transmission. The S11 reflection coefficient varied from -5 dB to -55 dB, with substantial decreases between 4 GHz and 14 GHz, when reflection decreased to -45 dB, signifying little signal reflection at essential frequencies. The results underscore the composite's appropriateness for applications requiring high transmission efficiency, little reflection, and effective engagement with electromagnetic waves, especially as an antenna substrate. Measurements were performed using a vector network analyzer (VNA) to obtain the S11 and S21 characteristics, underscoring the material's potential in sophisticated electromagnetic applications. Epoxy ; Composite number ; Pyrite ; Materials science ; Composite material ; Reflection (computer programming) ; Composite epoxy material ; Transmission (telecommunications) ; Metallurgy ; Computer science ; Telecommunications Electromagnetic wave absorption materials ; Material Properties and Applications ; Aluminum Alloys Composites Properties
Authors: Anxin Yang | Zhijuan Du | Tao Sun
Source: arXiv (Cornell University) (preprint, 2024-04-09)
Field: Chemistry — Inorganic Chemistry

A Survey of Reasoning for Substitution Relationships: Definitions, Methods, and Directions Substitute relationships are fundamental to people's daily lives across various domains. This study aims to comprehend and predict substitute relationships among products in diverse fields, extensively analyzing the application of machine learning algorithms, natural language processing, and other technologies. By comparing model methodologies across different domains, such as defining substitutes, representing and learning substitute relationships, and substitute reasoning, this study offers a methodological foundation for delving deeper into substitute relationships. Through ongoing research and innovation, we can further refine the personalization and accuracy of substitute recommendation systems, thus advancing the development and application of this field. Substitution (logic) ; Computer science ; Management science ; Engineering ; Programming language Asymmetric Hydrogenation and Catalysis
Authors: Abir Douzi | Sami Slimi | Pavel Loiko | Víctor Llamas | Josep María Serres | Rosa Maria Solé | Magdalena Aguiló | Francesc Dı́az | Ezzedine Ben Salem | Xavier Mateos
Source: Journal of Materials Science Materials in Electronics (article, 2024-05-01)
Field: Materials Science — Materials Chemistry

Temperature sensing by means of a near-infrared luminescent Ca8NaBi(PO4)6F2:Nd3+ fluorapatite phosphor Abstract Microrods of calcium sodium bismuth fluorapatite doped with neodymium, denoted as Ca 8 NaBi 1-x Nd x (PO 4 ) 6 F 2 (with x ranging from 0 to 0.5), were synthetized using a modified Pechini sol–gel method. The crystalline structure of these phosphors was refined using the Rietveld method and exhibited hexagonal symmetry with space group P6 3 /m—C 2 6h , where the lattice parameters were a = 9.3855(5) Å and c = 6.8998(6) Å for x = 0.2. The particles morphology was analyzed through SEM, revealing an average length of approximately 1.5 µm. When excited at 808 nm, the Ca 8 NaBi(PO 4 ) 6 F 2 :0.2Nd 3+ microrods emitted strongly at 872, 957 and 1055 nm, falling within the near-infrared region. These emissions correspond to the 4 F 3/2 → 4 I 9/2 (P2), 4 F 5/2 → 4 I 11/2 (P3), 4 F 3/2 → 4 I 11/2 (P1) transitions of Nd 3+ ions, respectively, and are situated within the first and second biological windows. The luminescence lifetime of the 4 F 3/2 state of Nd 3+ was measured to be 294.4 µs for the sample with the lowest Nd 3+ concentration of x = 0.05. In addition, the luminescence intensity ratios P2/P1 and P3/P1 were found to be temperature dependent, potentially making it suitable for luminescent ratiometric thermal sensing. These findings suggest that the synthesized Ca 8 NaBi(PO 4 ) 6 F 2 :Nd 3+ microrod thermometers exhibit favorable characteristics in terms of relative sensitivity, temperature uncertainty, and repeatability within the temperature range of 303–403 K. Fluorapatite ; Luminescence ; Phosphor ; Materials science ; Excited state ; Analytical Chemistry (journal) ; Ion ; Rietveld refinement ; Apatite ; Mineralogy ; Nuclear chemistry ; Crystal structure ; Crystallography ; Chemistry ; Atomic physics ; Physics ; Optoelectronics Luminescence Properties of Advanced Materials ; Glass properties and applications ; Solid-state spectroscopy and crystallography
Authors: Yuri E. M. van der Burgt | Fred P.H.T.M. Romijn | Maxim M. Treep | L. Renee Ruhaak | Christa M. Cobbaert
Source: Clinical Chemistry and Laboratory Medicine (CCLM) (article, 2024-10-25)
Field: Chemistry — Spectroscopy

Strategies to verify equimolar peptide release in mass spectrometry-based protein quantification exemplified for apolipoprotein(a) These data further corroborate the validity of our apo(a) candidate RMP as higher order method for certification of commercial Lp(a) tests that is endorsed by the International Federation of Clinical Chemistry and Laboratory Medicine. MS-based molecular detection and quantification of heterogeneous apo(a) proteoforms will allow manufacturers' transitioning from confounded lipoprotein(a) [Lp(a)] mass levels into accurate molar apo(a) levels. Peptide ; Apolipoprotein B ; Mass spectrometry ; Chemistry ; Analyte ; Selected reaction monitoring ; Chromatography ; Certified reference materials ; Apolipoprotein A1 ; Tandem mass spectrometry ; Biochemistry ; Cholesterol ; Detection limit Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Blood disorders and treatments
Authors: K. Arpitha | P. Sujatha | K. Jhansi Rani | S. Triveni
Source: Journal of Experimental Agriculture International (article, 2024-06-25)
Field: Materials Science — Polymers and Plastics

Compatibility of Commercial Polymers Used by the Seed Industry for Maize Biological Seed Coating An efficient biological seed coating begins with the choice of a suitable polymer. Experiments were conducted at the Department of Seed Science and Technology, Professor Jayashankar Telangana State Agricultural University, Hyderabad, to determine the compatibility of commercial polymers and biocontrol agents. Five polymers commercially used by the seed industry were procured from seed companies. Three bioformulations were purchased from the commercial biofertilizer units and the pure cultures of Trichoderma viride, Pseudomonas fluorescens, and Bacillus subtilis were isolated from the bioformulations through serial dilutions, culturing and subculturing on microbial media. The compatibility of commercially used polymers has been tested with biocontrol agents using poisoned food technique (for fungal bioagents) and the inhibition zone technique (for bacterial bioagents). Observations on the reduction in radial growth of the fungal bioagent and zone of inhibition of bacterial bioagents was recorded in mm. The results revealed that all the 5 polymers commercially used by the seed industry were tested to show 96–100% compatibility with Trichoderma viride, 100% compatibility with Pseudomonas fluorescens, and 95–100% compatibility with Bacillus subtilis. These findings indicate that there is a greater compatibility of all the commercial polymers used in the seed industry with the bioagents which can also be used for effective seed coating with bioagents economically without incurring any additional inventory from the part of the industry. Compatibility (geochemistry) ; Coating ; Polymer ; Agronomy ; Agricultural engineering ; Materials science ; Engineering ; Biology ; Nanotechnology ; Composite material Natural Fiber Reinforced Composites ; Agricultural Engineering and Mechanization ; Seed Germination and Physiology
Authors: Qinhao Bu | Sheng Liu | Le Feng | Haowei Xu | Qiaogen Zhang
Source: Advances in Engineering Technology Research (article, 2024-07-24)
Field: Materials Science — Materials Chemistry

High Frequency Breakdown Characteristics of Alumina Filler Content Epoxy Resin Power electronic transformers have high insulation frequency and compact insulation structure, and insulation performance is one of the main factors restricting their further development. Epoxy resin is an important insulating material in the electrical industry, its thermal conductivity and mechanical properties can not meet the needs of high-frequency transformers, usually metal oxide (Al2O3, etc.) is added to form composite insulation material. It is of great reference value for the insulation design of power electronic transformer to study the insulation performance of composite insulation materials with different filler content ratio under high-frequency AC. The effects of power supply frequency and alumina filler content on the breakdown performance of the composite were investigated experimentally. The results show that the breakdown voltage of pure epoxy resin decreases exponentially with frequency. At any filler content, the breakdown voltage of epoxy resin decreases with the increase of frequency, and the decreasing trend gradually slows down when the frequency increases from 50Hz to 1000Hz, and the decreasing trend gradually increases when the frequency increases to 2000Hz. The breakdown voltage of epoxy resin showed a down-rise-down trend with the increase of filler content, and the effect of filler content on breakdown voltage gradually weakened with the increase of frequency. Epoxy ; Materials science ; Composite material ; Filler (materials) ; Transformer ; Breakdown voltage ; Composite number ; Voltage ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Lightning and Electromagnetic Phenomena
Authors: Tara Akhound-Sadegh | Jarrid Rector-Brooks | Avishek Joey Bose | Sarthak Mittal | Pablo Lemos | Chenghao Liu | Marcin Sendera | Siamak Ravanbakhsh | Gauthier Gidel | Yoshua Bengio | Nikolay Malkin | Alexander Tong
Source: arXiv (Cornell University) (preprint, 2024-02-09)
Field: Materials Science — Surfaces, Coatings and Films

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Efficiently generating statistically independent samples from an unnormalized probability distribution, such as equilibrium samples of many-body systems, is a foundational problem in science. In this paper, we propose Iterated Denoising Energy Matching (iDEM), an iterative algorithm that uses a novel stochastic score matching objective leveraging solely the energy function and its gradient -- and no data samples -- to train a diffusion-based sampler. Specifically, iDEM alternates between (I) sampling regions of high model density from a diffusion-based sampler and (II) using these samples in our stochastic matching objective to further improve the sampler. iDEM is scalable to high dimensions as the inner matching objective, is simulation-free, and requires no MCMC samples. Moreover, by leveraging the fast mode mixing behavior of diffusion, iDEM smooths out the energy landscape enabling efficient exploration and learning of an amortized sampler. We evaluate iDEM on a suite of tasks ranging from standard synthetic energy functions to invariant $n$-body particle systems. We show that the proposed approach achieves state-of-the-art performance on all metrics and trains $2-5\times$ faster, which allows it to be the first method to train using energy on the challenging $55$-particle Lennard-Jones system. Matching (statistics) ; Sampling (signal processing) ; Iterated function ; Energy (signal processing) ; Statistical physics ; Boltzmann constant ; Noise reduction ; Mathematics ; Computer science ; Statistics ; Physics ; Artificial intelligence ; Mathematical analysis ; Computer vision ; Thermodynamics Electron and X-Ray Spectroscopy Techniques ; Generative Adversarial Networks and Image Synthesis ; Machine Learning in Materials Science
Authors: Varada Soujanya | Revu Baby Nalanda
Source: International Journal of TROPICAL DISEASE & Health (article, 2024-06-10)
Field: Chemistry — Analytical Chemistry

Stability-indicating Reverse Phase-HPLC Method Development and Method Validation for Quantitative Determination of Degradation Products in Favipiravir API and Drug Product Introduction: Favipiravir is an antiviral medication shown to be broad spectrum activity against RNA viruses, and potentially treating the COVID-19. Methodology: In this study, the HPLC method for the quantification of degradation impurities (Favipiravir Acid Impurities) were developed and validated for Favipiravir in Tablet dosage form. The specificity of the method was achieved in analytical column Agilent HPLC-C18, 5µm, (4.6 x250) mm. using a suitable mobile phase was 10 mM Phosphate buffer (pH 3.5 with orthophosphoric acid) and Acetonitrile in the Isocratic more of 70:30 v/v. The flow rate is 1.0 mL/min. the injection volume is 10 µL, detection at 320 nm in UV and total run time is 8.0 minutes. The samples were made for forced degradation under hydrolysis, oxidation, photolytic and thermal conditions. The method was validated for specific, selective, linear, robust and accurate as per the ICH guidelines. Results and Conclusion: The linearity of the method for Impurities and the analytes was found from 25 to 150 % concentration level with the correlation coefficient (r2) &gt; 0.999. The accuracy for impurity and the analytes was performed from 50 to 150% level concentration, and mean recovery was found from 98-102%. The analytical degradation and validated study results indicate its unstable nature in acidic, basic and thermal conditions. Therefore, this method is simple, selective and sensitive, this method can be used in pharmaceutical research and development and quality control departments. Chromatography ; Forced degradation ; Favipiravir ; Chemistry ; Analyte ; High-performance liquid chromatography ; Degradation (telecommunications) ; Dosage form ; Impurity ; Hydrolysis ; Acetonitrile ; Reversed-phase chromatography ; Coronavirus disease 2019 (COVID-19) ; Organic chemistry Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Electrochemical sensors and biosensors
Authors: Zainab Usman | Vaishnavi C. Kamatagi | Tilak Matagunde | Raviprakash Surgali | Revathi G.P.
Source: International Journal of Computer Applications (review, 2024-12-26)
Field: Chemistry — Analytical Chemistry

A Review of Machine Learning Techniques to Enhance Vegetable Grading and Spoilage Detection Examining the nexus of machine learning and farming, this paper navigates through the landscape of AI-driven fruit and vegetable grading, revealing strides in accuracy alongside ongoing computational and quality related hurdles.YOLOv5, Faster R-CNN, and Vision Transformers (ViT) are some of the techniques reviewed for object detection and classification tasks that have very high accuracy with real-time performance.This survey presents a novel approach for fruit and vegetable classification through modified K-Means, SVM, and ANN techniques with remarkable efficiency and cost reducing abilities.The discussion incorporates traditional edge detection methods like Sobel, Prewitt, and Canny, along with innovative approaches like GrabCut and DeepSORT, for contributions in the field of image segmentation and object counting.Despite improvements with high impact, overfitting, dependence on the quality of images, and computational costs remain, which require continued research.This paper surveys the current methodologies in agricultural Machine Learning and Deep Learning applications and presents some directions of future improvements. Computer science ; Grading (engineering) ; Food spoilage ; Artificial intelligence ; Machine learning ; Data science ; Biology ; Ecology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Ajaya Bhattarai | Man Singh
Source: Journal of Nepal Chemical Society (article, 2024-02-21)
Field: Chemistry — Organic Chemistry

The interfacial tension at the liquid junction of petrol and Sodium dodecyl sulphate solution The precise measurements of petrol interfacial tension (IFT) in the presence of Sodium dodecyl sulphate (SDS) at room temperature by Mansingh Survismeter are reported. The concentration of sodium dodecyl sulphate was varied from above and below the critical micelle concentration (CMC) to cover the minimum and maximum concentrations of the investigated surfactant. Petrol was taken from the dealer in Nepal and used without purification. Therefore, when surfactant is added to the system, the surfactant decreases its free energy, thus decreasing its surface tension Pulmonary surfactant ; Surface tension ; Sodium dodecyl sulfate ; Critical micelle concentration ; Sodium ; Gasoline ; Chemistry ; Chromatography ; Micelle ; Chemical engineering ; Organic chemistry ; Aqueous solution ; Thermodynamics ; Biochemistry Surfactants and Colloidal Systems ; Enhanced Oil Recovery Techniques ; Electrowetting and Microfluidic Technologies
Authors: Ahmed M. Gomaa | Yixing Huang | Amr Hagag | Charlotte Schmitter | Daniel Höfler | Thomas Weißmann | Katharina Breininger | Manuel Schmidt | Jenny Stritzelberger | Daniel Delev | Roland Coras | Arnd Dörfler | Oliver Schnell | Benjamin Frey | Udo S. Gaipl | Sabine Semrau | Christoph Bert | Rainer Fietkau | Florian Putz
Source: arXiv (Cornell University) (preprint, 2024-05-21)
Field: Materials Science — Materials Chemistry

Comprehensive Multimodal Deep Learning Survival Prediction Enabled by a Transformer Architecture: A Multicenter Study in Glioblastoma Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability. Method: We propose and evaluate a transformer-based non-linear and non-proportional survival prediction model. The model employs self-supervised learning techniques to effectively encode the high-dimensional MRI input for integration with non-imaging data using cross-attention. To demonstrate model generalizability, the model is assessed with the time-dependent concordance index (Cdt) in two training setups using three independent public test sets: UPenn-GBM, UCSF-PDGM, and RHUH-GBM, each comprising 378, 366, and 36 cases, respectively. Results: The proposed transformer model achieved promising performance for imaging as well as non-imaging data, effectively integrating both modalities for enhanced performance (UPenn-GBM test-set, imaging Cdt 0.645, multimodal Cdt 0.707) while outperforming state-of-the-art late-fusion 3D-CNN-based models. Consistent performance was observed across the three independent multicenter test sets with Cdt values of 0.707 (UPenn-GBM, internal test set), 0.672 (UCSF-PDGM, first external test set) and 0.618 (RHUH-GBM, second external test set). The model achieved significant discrimination between patients with favorable and unfavorable survival for all three datasets (logrank p 1.9\times{10}^{-8}, 9.7\times{10}^{-3}, and 1.2\times{10}^{-2}). Conclusions: The proposed transformer-based survival prediction model integrates complementary information from diverse input modalities, contributing to improved glioblastoma survival prediction compared to state-of-the-art methods. Consistent performance was observed across institutions supporting model generalizability. Glioblastoma ; Deep learning ; Transformer ; Computer science ; Artificial intelligence ; Architecture ; Computer architecture ; Medicine ; Engineering ; Cancer research ; Electrical engineering ; Geography Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications