jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ahmad Mohammadi-Farani | Milad Takesh | Mahsa Mohammadi | Amin Hosseini | Amin Aliabadi | Alireza Aliabadi
Source: Pharmaceutical Sciences (article, 2024-04-14)
Field: Chemistry — Organic Chemistry

<b>Synthesis, Docking and Acetylcholinesterase Inhibitory Evaluation of 1,3,4-Thiadiazole Derivatives as Potential Anti-Alzheimer Agents</b> Background: According to the cholinergic hypothesis for Alzheimer’s disease, potentiation of cholinergic neurotransmission is one of the best strategies for combating dementia. Methods: A new series of benzamide derivatives bearing 1,3,4-thiadiazole nucleus were synthesized and subsequently, their anticholinesterase activity was evaluated. Molecular docking was carried out to explore the likely binding mode and interactions. Results: Fortunately, some of the tested compounds exhibited more activity than donepezil as a reference drug (IC50 = 0.6 ± 0.05 µM). Some of the evaluated derivatives displayed potency in the nanomolar range. Compound 7e with fluorine atom on the meta position of the phenyl ring was the most active compound in this series (IC50 = 1.82 ± 0.6 nM). Conclusion: The 1,3,4-thiadiazole derivatives that were synthesized and tested in the current manuscript demonstrated remarkable anticholinesterase activity. Therefore, these compounds could be suggested as potential anti-Alzheimer agents. Acetylcholinesterase ; Inhibitory postsynaptic potential ; Docking (animal) ; Chemistry ; Pharmacology ; Acetylcholinesterase inhibitor ; Stereochemistry ; Combinatorial chemistry ; Biochemistry ; Medicine ; Neuroscience ; Enzyme ; Biology Synthesis and biological activity ; Cholinesterase and Neurodegenerative Diseases ; Synthesis and Characterization of Heterocyclic Compounds
Authors: Rui Fang | Amir Ghasemi | Dagou A. Zeze | Mehdi Keshavarz Hedayati
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inverse design of lateral hybrid metasurfaces structural colour: an AI approach In conventional metasurface structural colour design, simulations combined with human intuition are used for design and optimization, making it challenging to find the best solution. Here we introduce an innovative AI-assisted design process that bypasses the need for complex simulations, enabling swift and precise mapping between metasurface parameters and colour coordinates. Instead of assigning one colour to one geometry, we demonstrate that multiple colours can be generated from a single geometry under varying levels of strain. This can be achieved through a single model, facilitating the development of active metasurfaces using AI. This finding enables designers to create active metasurfaces that account for both geometric properties and dynamic responses in a unified model which could accelerate the development of active metamaterials closer to practical applications in the real world. Inverse ; Identification (biology) ; Computer science ; Process (computing) ; Inverse problem ; Artificial intelligence ; Machine learning ; Mathematics ; Geometry Metamaterials and Metasurfaces Applications ; Acoustic Wave Phenomena Research ; Polydiacetylene-based materials and applications
Authors: Anmol Kumar | Alexander D. MacKerell
Source: ChemRxiv (preprint, 2024-02-29)
Field: Chemistry — Organic Chemistry

FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation Developing production quality CHARMM force-field (FF) parameters is a very detailed process involving a variety of calculations many of which are specific for the molecule of interest. The first version of FFParam was developed as a standalone python package designed for optimization of electrostatic and bonded parameters of the CHARMM additive and polarizable Drude FFs using quantum mechanical (QM) target data. The new version of FFParam has multiple new capabilities for FF parameter optimization and validation, with emphasis on the ability to use condensed phase target data in the optimization. FFParam-v2 allows optimization of Lennard-Jones (LJ) parameters using potential energy scans of interactions between selected atoms in a molecule and noble gases viz. He, Ne and through condensed phase calculations from which experimental observables such as heats of vaporization and free energies of solvation may be obtained. This functionality serves as a gold-standard for both optimizing parameters and validating the performance of the final parameters. A new bonded parameter optimization algorithm has been introduced to account for simultaneously optimizing multiple molecules sharing parameters. FFParam-v2 also supports comparison of normal modes and the percent contribution of internal coordinates towards each normal mode obtained from QM and molecular mechanics calculations. Such comparison capability is vital to validate the balance amongst various bonded parameters that contribute to the complex normal modes of molecules. User interaction has been extended beyond the original graphical user interface (GUI), to include command line interface capabilities that allows for integration of FFParam in workflows thereby facilitating automation of parameter optimization. With these new functionalities, FFParam is a more comprehensive parameter optimization tool for both beginner and advanced users. Force field (fiction) ; Python (programming language) ; Solvation ; Polarizability ; Computer science ; Graphical user interface ; Chemistry ; Statistical physics ; Materials science ; Molecule ; Physics ; Artificial intelligence Chemical Thermodynamics and Molecular Structure ; Advanced Chemical Physics Studies ; Machine Learning in Materials Science
Authors: Elisa Pereira | Rafael Garibotti | Luciano Ost | Ney Calazans | Fernando Gehm Moraes
Source: Journal of Integrated Circuits and Systems (article, 2024-08-01)
Field: Materials Science — Materials Chemistry

A Complementary Survey of Radiation-Induced Soft Error Research: Facilities, Particles, Devices and Trends Soft errors caused by external radiation sources have historically affected the reliability of electronic devices. The radiation effects community has dedicated significant effort to understanding and addressing circuit failures, offering insights and techniques for their mitigation. Nevertheless, the broad nature of the radiation field research poses challenges to identifying the overall progress made by its community. This survey analyses a collection of 295 articles published between 2018 and 2022, with the aim to characterize the current stage of radiation-induced errors research. The focus is on experimental research considering radiation effects on electronic devices, excluding from consideration works that solely involve simulation and radiation modeling. Furthermore, it limits the analysis scope to effects of particle radiation originating from space, overlooking device- or material-related radiation sources such as those due to specific chip packaging or used solder bumps. The survey contributes to the characterization of particles, facilities, and devices used in current radiation-induced experiments, bringing both quantitative and qualitative analyses of the literature over the past five years. Lastly, this review reports trends in radiation research, revealing which particles are currently considered most relevant, highlighting the most used facilities available for testing radiation effects, and emphasizing which technological nodes and/or devices are addressed preferentially with regard to radiation-induced effects studies. Radiation ; Soft error ; Survey research ; Computer science ; Medical physics ; Statistics ; Medicine ; Psychology ; Physics ; Engineering ; Optics ; Mathematics ; Applied psychology ; Electronic engineering Graphite, nuclear technology, radiation studies ; Risk and Safety Analysis
Authors: Samir F. Matar | Vladimir L. Solozhenko
Source: ChemRxiv (preprint, 2024-03-29)
Field: Materials Science — Materials Chemistry

Novel tetragonal boron pnictides BX (X = N, P, As, Sb, Bi) with square B2X2 motifs from crystal chemistry and first principles Novel tetragonal (P42/mnm) boron pnictides BX (X = N, P, As, Sb, Bi) with chromium boride (crb) topology exhibiting a square B2X2 motif with resulting edge- and corner-sharing tetrahedra have been predicted from crystal chemistry and extensively characterized by density functional theory (DFT) calculations. All new BX phases were found to be cohesive with decreasing cohesive energy along the series. Mechanically stable with positive sets of elastic constants, all crb phases exhibit slightly lower hardness than other BX polymorphs due to increased openness of the crystal structures. All-positive phonon frequencies characterize the crb BX family except for X = Bi, which shows a slight acoustic instability; also the shape of the phonon spectra changes from band-like for X = N, P, As to flat bands for the heavier elements. The electronic band structures reveal insulating to semiconducting properties for crb BX, depending on the pnictogen nature along the series. Tetragonal crystal system ; Boron ; Chemistry ; Square (algebra) ; Crystallography ; Crystal chemistry ; Crystal structure ; Mathematics ; Organic chemistry Boron and Carbon Nanomaterials Research ; 2D Materials and Applications ; Crystal Structures and Properties
Authors: Simone Di Muzio | A. Paolone | F. Trequattrini | Oriele Palumbo
Source: Applied Sciences (article, 2024-12-07)
Field: Chemistry — Spectroscopy

Intermolecular Interactions in Mixed Choline Acetate and Maleic Acid Systems Mixed systems based on ionic liquids are promising innovative solvents due to their properties, which are strictly connected to the interactions that arise among the components. The present work investigates the intermolecular interactions of a mixed choline acetate and maleic acid system and their modifications with increasing acid content. MM/DFT calculations provided indications about the possible geometric configurations of the systems while Non-Covalent Interaction analysis was useful to describe and distinguish secondary interactions. The number of available configurations decreases at high acid concentration. Moreover, intramolecular hydrogen bonding was observed in all configurations except that in the most stable one of the lowest acid content mixture. Concomitantly, far-infrared spectroscopy was used to investigate intermolecular interactions and provided support to the computational results. Maleic acid ; Intermolecular interaction ; Intermolecular force ; Chemistry ; Polymer chemistry ; Organic chemistry ; Polymer ; Molecule ; Copolymer Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies ; Chemical and Physical Properties in Aqueous Solutions
Authors: Girish Kumar | S. Raj Kumar | Abhishek Sharma | A.K. Raturi | Ashutosh Shrivastava | A.L.N. Rao | Ashok Kumar Khan
Source: Journal of Nano- and Electronic Physics (article, 2024-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Novel Framework for Enhanced Nanoparticle Detection in Scanning Electron Microscopy Using Synthetic Data Journal of Nano- and Electronic Physics. Scientific journal. ISSN: 2077-6772. Journal abbreviation: J. Nano- Electron. Phys. No page charges. All articles are freely available on-line. Issued 4 times per year. Publisher: Sumy State University. (Sumy, Ukraine) Nanoparticle ; Scanning electron microscope ; Nanotechnology ; Materials science ; Electron microscope ; Microscopy ; Physics ; Optics ; Composite material Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science
Authors: Tamara Kutateladze | Kakha Karchkhadze | Kakha Bitskinashvili | Boris Vishnepolsky | Tata Ninidze | David Mikeladze | Nelly Datukishvili
Source: Preprints.org (preprint, 2024-09-30)
Field: Chemistry — Analytical Chemistry

Novel PCR-Based Technology for the Detection of Sunflower in Edible and Used Cooking Oils Reliable detection of sunflower (Helianthus annuus) in edible and used cooking oil (UCO) is crucial for the sustainable production of food and biodiesel. In this study, a variety of sunflower oils (crude, cold pressed, extra virgin, refined, and UCO) were examined using different methods of DNA extraction and PCR amplification to develop an efficient technology for the identification of sunflower in oils. DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs. The combination of modified CTAB and nested PCR was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in 700 μl of highly processed oil, including refined and used cooking oil. The study will contribute to both the food industry and the energy sector as developed methods can be used for oil authenticity testing in food and biodiesel production. Sunflower ; Edible oil ; Sunflower oil ; Food science ; Biotechnology ; Biology ; Horticulture Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Sixie Huang | Youqu Shen | Bin Li | Guocong Liu | Na Qiang | Weiping Gong
Source: Applied Sciences (article, 2024-02-12)
Field: Materials Science — Ceramics and Composites

The Effect of the Chemical Composition on Mechanical Properties of CMAS Diopside Glass Ceramics Molecular dynamics simulations were performed on CaO-MgO-Al2O3-SiO2 (CMAS) diopside glass ceramics (GCs) to study the effect of nanocrystal on glass and the effect of chemical composition on mechanical properties. Under tensile loading, the GCs demonstrated that the strength lay between its glass and ceramic counterparts and maintained considerable ductility. Moreover, high Mg/Ca ion ratios are conductive to both the strength and ductility of GCs. In addition, Al ions should be avoided as far as possible since they would promote fracture. After analyzing the shear strain and displacement vector map for ion structures, we found that the presence of nanocrystal in glass changes the original deformation pattern and led to the deformation concentration surrounding the nanocrystal. A high Mg/Ca ion ratio would make the deformation more homogeneous, while a high Ca/Mg ion ratio would aggregate the deformation in the glass region near the nanocrystal. The existence of Al ions near the interface between glass and crystal would promote the formation of voids. Materials science ; Nanocrystal ; Composite material ; Ductility (Earth science) ; Ceramic ; Diopside ; Ultimate tensile strength ; Ion ; Glass-ceramic ; Deformation (meteorology) ; Mineralogy ; Nanotechnology ; Chemistry Glass properties and applications ; Advanced ceramic materials synthesis ; Recycling and utilization of industrial and municipal waste in materials production
Authors: Shijie Duan | Ming Yang | Suyuan Zhou | Longhui Zhang | Jinsen Han | Xu Sun | Guang Wang | Changqin Liu | Dongdong Kang | Xiaowei Wang | Jiahao Chen | Jiayu Dai
Source: Chinese Optics Letters (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Efficient terahertz generation from van der Waals α-In2Se3 Two-dimensional (2D) van der Waals materials have attracted tremendous attention due to their versatile physical properties and flexible manipulation approaches. Among the various types of van der Waals materials, α-In2Se3 is remarkable for its intrinsic 2D ferroelectricity and high-performance opto-electronic properties. However, the study of the α-In2Se3 system in terahertz (THz) radiation is scarce, although it is promising for electrically controlled THz field manipulation. We investigate the α-In2Se3 in different thicknesses and report that the THz generation efficiency induced by femtosecond laser pulses can be largely improved by reducing the thickness from the bulk. Furthermore, we reveal the surge current in thin film coupled with THz emission exhibits a different Auger recombination mode, which is helpful in understanding the mechanism and provides insights into the design of 2D highly efficient THz devices. Terahertz radiation ; Optics ; van der Waals force ; Terahertz spectroscopy and technology ; Physics ; Quantum mechanics ; Molecule 2D Materials and Applications ; Advanced Thermoelectric Materials and Devices ; Advanced Semiconductor Detectors and Materials
Authors: Kai Zhang
Source: Journal of Electrical Systems (article, 2024-04-08)
Field: Chemistry — Analytical Chemistry

Application of Statistical Features in Vibro-acoustic Signals to Detect Early Browning Disorder in Pears Compared with Food Chemistry Method - Browning in pears is one of the most serious diseases in pear fruit, which is caused by Alternaria alternata. The browning process is accompanied by changes in the chemical properties of the fruit, which affect its taste and nutritional composition. Additionally, as a typical postharvest disease, internal browning in pears can cause fruit tissue decay during storage that can reduce the shelf stability of fruit, and bring serious losses to sellers. Because it is difficult to identify the browning pears by appearance, a non-destructive detection technology is highly desirable to correctly discriminate a pear at the early stage of browning for increasing the market value. Firstly, 11 and 7 statistical features were calculated from the time-domain and frequency-domain, respectively. Then, sensitive features in time-domain set, frequency-domain set and combined feature set were selected by the distance evaluation technology, respectively. These selected features were used to train classifier based on K-nearest neighbor algorithm under different K-values. With the selected combined features adopted, the constructed KNN classifier performed the best classification performance. It allowed a high overall accuracy of 91.8 % to classify the healthy and browning pears. Also, the F1 value of 92.6 % indicated that the classifier can be successfully generalized. Therefore, the classification model established in this study is effective for identifying the early browning disorder in pear fruit. Browning ; PEAR ; Chemistry ; Biological system ; Horticulture ; Food science ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Pilar Luaces | Rosario Sánchez | Jesús Expósito | Antonio J. Pérez‐Pulido | Ana G. Pérez | Carlos Sanz
Source: International Journal of Molecular Sciences (article, 2024-10-10)
Field: Chemistry — Analytical Chemistry

Functional and Physiological Characterization of Tyrosine Decarboxylases from Olea europaea L. Involved in the Synthesis of the Main Phenolics in Olive Fruit and Virgin Olive Oil The phenolic composition of virgin olive oil (VOO) primarily depends on the phenolic content of the olive fruit. The purpose of this work was to characterize the first metabolic step in the synthesis of tyrosol (Ty) and hydroxytyrosol (HTy), whose derivatives are by far the predominant phenolics in both olive fruit and VOO. To this end, two genes encoding tyrosine/DOPA decarboxylase enzymes, <i>OeTDC1</i> and <i>OeTDC2</i>, have been identified and functionally and physiologically characterized. Both olive TDC proteins exclusively accept aromatic amino acids with phenolic side chains, such as tyrosine and 3,4-dihydroxyphenylalanine (DOPA), as substrates to produce tyramine and dopamine, respectively. These proteins exhibited a higher affinity for DOPA than for tyrosine, and the catalytic efficiency of both proteins was greater when DOPA was used as a substrate. Both olive <i>TDC</i> genes showed a fairly similar expression profile during olive fruit ontogeny, with <i>OeTDC1</i> consistently expressed at higher levels than <i>OeTDC2</i>. Expression was particularly intense during the first few weeks after fruit set, coinciding with the active accumulation of Ty and HTy derivatives. The data suggest that both olive TDCs are responsible for the initial step in the synthesis of the most important phenolics, both quantitatively and functionally, in VOO. Olea ; Olive oil ; Oleaceae ; Oleuropein ; Olive trees ; Botany ; Biology ; Chemistry ; Food science Dye analysis and toxicity ; Biochemical Analysis and Sensing Techniques ; GABA and Rice Research
Authors: Shiva Ebrahimi | Xuan Guo
Source: PubMed (preprint, 2024-02-17)
Field: Chemistry — Spectroscopy

Transformer-based de novo peptide sequencing for data-independent acquisition mass spectrometry Tandem mass spectrometry (MS/MS) stands as the predominant high-throughput technique for comprehensively analyzing protein content within biological samples. This methodology is a cornerstone driving the advancement of proteomics. In recent years, substantial strides have been made in Data-Independent Acquisition (DIA) strategies, facilitating impartial and non-targeted fragmentation of precursor ions. The DIA-generated MS/MS spectra present a formidable obstacle due to their inherent high multiplexing nature. Each spectrum encapsulates fragmented product ions originating from multiple precursor peptides. This intricacy poses a particularly acute challenge in de novo peptide/protein sequencing, where current methods are ill-equipped to address the multiplexing conundrum. In this paper, we introduce Transformer-DIA, a deep-learning model based on transformer architecture. It deciphers peptide sequences from DIA mass spectrometry data. Our results show significant improvements over existing STOA methods, including DeepNovo-DIA and PepNet. Transformer-DIA enhances precision by 15.14% to 34.8%, recall by 11.62% to 31.94% at the amino acid level, and boosts precision by 59% to 81.36% at the peptide level. Integrating DIA data and our Transformer-DIA model holds considerable promise to uncover novel peptides and more comprehensive profiling of biological samples. Transformer-DIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/Transformer-DIA. Mass spectrometry ; Peptide ; Chromatography ; Chemistry ; Computational biology ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications
Authors: Gang Bao | Chang Ma | Yuxuan Gong
Source: arXiv (Cornell University) (preprint, 2024-07-21)
Field: Materials Science — Materials Chemistry

PFWNN: A deep learning method for solving forward and inverse problems of phase-field models Phase-field models have been widely used to investigate the phase transformation phenomena. However, it is difficult to solve the problems numerically due to their strong nonlinearities and higher-order terms. This work is devoted to solving forward and inverse problems of the phase-field models by a novel deep learning framework named Phase-Field Weak-form Neural Networks (PFWNN), which is based on the weak forms of the phase-field equations. In this framework, the weak solutions are parameterized as deep neural networks with a periodic layer, while the test function space is constructed by functions compactly supported in small regions. The PFWNN can efficiently solve the phase-field equations characterizing the sharp transitions and identify the important parameters by employing the weak forms. It also allows local training in small regions, which significantly reduce the computational cost. Moreover, it can guarantee the residual descending along the time marching direction, enhancing the convergence of the method. Numerical examples are presented for several benchmark problems. The results validate the efficiency and accuracy of the PFWNN. This work also sheds light on solving the forward and inverse problems of general high-order time-dependent partial differential equations. Field (mathematics) ; Phase (matter) ; Inverse ; Inverse problem ; Computer science ; Artificial intelligence ; Mathematics ; Physics ; Mathematical analysis ; Geometry Solidification and crystal growth phenomena ; Magnetic Properties and Applications