jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nader El-Shanhorey | Abdrabbo Abdel-Azim Shehata
Source: Alexandria Journal of Agricultural Sciences (article, 2024-11-07)
Field: Chemistry — Analytical Chemistry

Response Foliar Applied with Ascorbic Acid to Mitigate the Detrimental Impact of Lead Pollution in Water Irrigation on Jatropha curcas Plants The present study was carried out at Antoniadis Research Branch, Horticultural Research Institute, A.R.C. Alexandria, during the two successive seasons of 2022 and 2023. This study aimed to evaluate the effects of irrigation water contaminated with lead on Jatropha curcas plants grown in sandy soil, and the possibility of using ascorbic acid spray treatments to overcome the effects of lead pollution. Seedlings of Jatropha curcas were planted individually in plastic pots (30 cm diameter) filled with 8 kg of sandy soil. The contaminated irrigation water treatments were four concentrations of lead 0,100, 200, and 300 mg/l applied. The plants also were sprayed with ascorbic acid at concentrations of 0, 250, and 500 mg/l by monthly spraying in both seasons. The results showed that for vegetative growth parameters, there was no significant difference in the interaction between lead concentrations and foliar spray by ascorbic acid. While a significant reduction was observed in all parameters after irrigation with lead-contaminated water and a significant increase in vegetative growth parameters was observed after 500 mg/l ascorbic acid application. For chlorophyll and carbohydrate content the highest significant value was obtained from plants irrigated with tap water and sprayed 500 mg/l ascorbic acid while the highest significant amount of lead content in leaves, stem and roots was obtained from the treatment of 300 mg/l lead without application of ascorbic acid. The results showed that the interaction between lead concentrations and ascorbic acid foliar spray about vegetative growth indices was not significantly different. Jatropha curcas ; Ascorbic acid ; Irrigation ; Agronomy ; Pollution ; Environmental science ; Lead (geology) ; Jatropha ; Biology ; Horticulture ; Biodiesel ; Ecology Heavy Metals in Plants ; Environmental and Analytical Chemistry Studies ; Agricultural Science and Fertilization
Authors: Yanjun Bao | Hongsheng Shi | Rui Wei | Boyou Wang | Zhou Zhou | Cheng‐Wei Qiu | Baojun Li
Source: arXiv (Cornell University) (preprint, 2024-08-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High-Capacity Metasurface at Limits of Polarization and Wavelength Multiplexing Polarization and wavelength multiplexing are the two most widely employed techniques to improve the capacity in the metasurfaces. Existing works have pushed each technique to its individual limits. For example, the polarization multiplexing channels working at a single wavelength have been significantly increased by using noise engineering. However, it is still challenging to achieve the multiplexing limits of wavelength and polarization simultaneously. Besides, such multiplexing methods suffer from computational inefficiencies, hindering their application in tasks like image recognition that require extensive training computation. In this work, we introduce a gradient-based optimization algorithm using deep neural network (DNN) to achieve the limits of both polarization and wavelength multiplexing with high computational efficiency. We experimentally demonstrate this capability, achieving a record-breaking capacity of 15 holographic images across five wavelengths and the maximum of three independent polarization channels, as well as 18 holographic images across three wavelengths and six corelated polarization channels. Moreover, leveraging the high computational efficiency of our DNN-based method, which is well-suited for processing large datasets, we implement large-scale image recognition tasks across 36 classes encoded in a record of nine multiplexed channels (three wavelengths * three polarizations), achieving 96% classification accuracy in calculations and 91.5% in experiments. This work sets a new benchmark for high-capacity multiplexing with metasurfaces and demonstrates the power of gradient-based inverse design for realizing multi-functional optical elements. Multiplexing ; Polarization (electrochemistry) ; Wavelength ; Optics ; Optoelectronics ; Physics ; Materials science ; Telecommunications ; Computer science ; Chemistry Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Photonic and Optical Devices
Authors: J. Joselin Zibia | D. Rajkumar
Source: Journal of Chemistry (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

A Comparative Study of Spectrophotometric Determination of Malathion With Ammonium Meta Vanadate and Potassium Bromate Malathion is one of the commonly used pesticides in India which is toxic as per the World Health Organization. Its residue has been found in industrial effluent, water streams, and agricultural products. Various analytical methods such as gas chromatography, infrared spectroscopy, and thin‐layer chromatography were used for identifying the concentration of pesticides in aqueous phase. Though gas chromatography is one of the best available techniques in pesticide analysis, it involves higher cost. In this study, simple spectrophotometric methods for identifying the malathion in aqueous phase are experimented and compared using UV visible double beam spectrophotometer. Comparing these two methods will help us to select the most suitable method for specific analytical needs, considering factors such as accuracy, sensitivity, ease of use, and safety. This comparative analysis aids in choosing the best method for reliable and efficient determination of malathion. A regression analysis of Beers–Lambert plots showed a good correlation in the concentration range of 0.5–15 mg/L for the abovementioned two spectrophotometrical methods. The results showed that potassium bromate exhibits rapid, stable color complex and linearity in absorbance versus concentration study when compared with ammonium meta vanadate. Chemistry ; Vanadate ; Potassium bromate ; Malathion ; Bromate ; Ammonium ; Potassium ; Chromatography ; Nuclear chemistry ; Inorganic chemistry ; Organic chemistry ; Detection limit ; Pesticide ; Bromide Analytical chemistry methods development ; Electrochemical Analysis and Applications ; Pesticide Residue Analysis and Safety
Authors: Gangqi Chen | Zhaoyong Mao | Junge Shen | Dongdong Hou
Source: Complex & Intelligent Systems (article, 2024-11-18)
Field: Chemistry — Analytical Chemistry

Enhancing classification efficiency in capsule networks through windowed routing: tackling gradient vanishing, dynamic routing, and computational complexity challenges Abstract Capsule networks overcome the two drawbacks of convolutional neural networks: weak rotated object recognition and poor spatial discrimination. However, they still have encountered problems with complex images, including high computational cost and limited accuracy. To address these challenges, this work has developed effective solutions. Specifically, a novel windowed dynamic up-and-down attention routing process is first introduced, which can effectively reduce the computational complexity from quadratic to linear order. A novel deconvolution-based decoder is also used to further reduce the computational complexity. Then, a novel LayerNorm strategy is used to pre-process neuron values in the squash function. This prevents saturation and mitigates the gradient vanishing problem. In addition, a novel gradient-friendly network structure is developed to facilitate the extraction of complex features with deeper networks. Experiments show that our methods are effective and competitive, outperforming existing techniques. Computational intelligence ; Adaptive routing ; Routing (electronic design automation) ; Computer science ; Computational complexity theory ; Multipath routing ; Distributed computing ; Artificial intelligence ; Dynamic Source Routing ; Algorithm ; Routing protocol ; Computer network Spectroscopy and Chemometric Analyses ; Machine Learning and ELM ; Face and Expression Recognition
Authors: Guohang Zhuang | Yue Hu | Tianxing Yan | Jiazhan Gao
Source: arXiv (Cornell University) (preprint, 2024-03-18)
Field: Chemistry — Analytical Chemistry

GCAM: Gaussian and causal-attention model of food fine-grained recognition Currently, most food recognition relies on deep learning for category classification. However, these approaches struggle to effectively distinguish between visually similar food samples, highlighting the pressing need to address fine-grained issues in food recognition. To mitigate these challenges, we propose the adoption of a Gaussian and causal-attention model for fine-grained object recognition.In particular, we train to obtain Gaussian features over target regions, followed by the extraction of fine-grained features from the objects, thereby enhancing the feature mapping capabilities of the target regions. To counteract data drift resulting from uneven data distributions, we employ a counterfactual reasoning approach. By using counterfactual interventions, we analyze the impact of the learned image attention mechanism on network predictions, enabling the network to acquire more useful attention weights for fine-grained image recognition. Finally, we design a learnable loss strategy to balance training stability across various modules, ultimately improving the accuracy of the final target recognition. We validate our approach on four relevant datasets, demonstrating its excellent performance across these four datasets.We experimentally show that GCAM surpasses state-of-the-art methods on the ETH-FOOD101, UECFOOD256, and Vireo-FOOD172 datasets. Furthermore, our approach also achieves state-of-the-art performance on the CUB-200 dataset. Gaussian ; Computer science ; Artificial intelligence ; Statistical physics ; Econometrics ; Mathematics ; Chemistry ; Physics ; Computational chemistry Spectroscopy and Chemometric Analyses ; Nutritional Studies and Diet ; Traditional Chinese Medicine Studies
Authors: Thabo Mhlongo | Thomas Dipogiso Sedumedi
Source: Research Square (preprint, 2024-01-10)
Field: Chemistry — Physical and Theoretical Chemistry

The Periodic Table and The Learning of Chemistry: Possibilities of Integrating Robotics and Concept-Based Approaches in Teaching Abstract In this study, the authors investigate the potential of integrating robotics technology and concept-based teaching approaches to enhance the learning of abstract Chemistry concepts, focusing on the periodic table as both subject matter and tool. Utilizing a quasi-experimental design, the research employs descriptive quantitative and qualitative methods for data collection, including pre- and post-test experimental designs. Results suggest that combining robotics with concept-based teaching improves learners' deep understanding of chemistry concepts. The study highlights the promising benefits of integrating robotics technology and a concept-based approach for teaching chemistry, emphasizing the need for further research in this area. Robotics ; Table (database) ; Artificial intelligence ; Computer science ; Mathematics education ; Cognitive science ; Management science ; Engineering ; Robot ; Psychology ; Data mining Various Chemistry Research Topics ; Visual and Cognitive Learning Processes ; Semantic Web and Ontologies
Authors: H.-R. Seo | Seung Hwan Oh | Ji Woo Lee | Ja‐Hyoung Ryu | Hae Chan Jeon | Seul Ki Lee | Jin Gook Kim | Seung Wook Song
Source: Journal of Bio-Environment Control (article, 2024-10-31)
Field: Chemistry — Analytical Chemistry

Model for Non-destructive Quality Prediction of ‘Mihong’ Peach using Hyperspectral Imaging This study aims to develop a non-destructive quality prediction model for 'Mihong' peach under open-field conditions using hyperspectral imaging.The primary objective is to identify wavelengths and vegetation indices that exhibit strong correlation with soluble solids content (SSC), titratable acidity (TA), and firmness in the image data captured by a hyperspectral camera.These indices were subsequently used to construct predictive models for SSC, TA, and firmness.Hyperspectral imaging data were collected from 120 'Mihong' peach samples during the 2023 and 2024 growing seasons.The data preprocessing methods (IQR, SNV, SG) were applied to improve the accuracy of the models, and predictive models were developed using partial least squares regression (PLSR), random forest (RF), and extreme gradient boosting (XGB) algorithms.Model performance was assessed using the coefficient of determination (R 2 ) and root mean square error (RMSE). Hyperspectral imaging ; Quality (philosophy) ; Computer science ; Artificial intelligence ; Remote sensing ; Computer vision ; Environmental science ; Geology ; Physics Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Remote Sensing in Agriculture
Authors: Guanhai Li | Jie Wang | Jin Chen | Feilong Yu | Rongsheng Chen | Jiuxu Wang | Zengyue Zhao | Xuenan Li | Huaizhong Xing | Xiaohong Chen | Wei Lü
Source: Research Square (preprint, 2024-03-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Unlocking Ultra-High Holographic Information Capacity through Nonorthogonal Polarization Multiplexing Multiplexing ; Holography ; Polarization (electrochemistry) ; Computer science ; Optics ; Physics ; Telecommunications Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Photonic and Optical Devices
Authors: Levent Arın | Efe Arın
Source: Research Square (preprint, 2024-10-03)
Field: Chemistry — Analytical Chemistry

Artificial Intelligence Powered Multi-Dimensional Feature Analysis of Osmo-Priming on Pepper Seeds Pepper ; Priming (agriculture) ; Feature (linguistics) ; Computer science ; Artificial intelligence ; Biology ; Horticulture ; Computer security ; Linguistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Yinghao Cao | Jianxing Zhao | Jianhong Zhou | Yinglin Song
Source: Journal of Physics D Applied Physics (article, 2024-04-02)
Field: Materials Science — Materials Chemistry

Experimental study of DC Kerr effect of chalcogenide glass film by free space coupling method Abstract Chalcogenide glass is an important nonlinear optical material that has attracted much attention in the areas of integrated photonics, supercontinuum sources, and all-optical switches in recent years. However, the current research mainly focuses on the nonlinear effect excited by light, and the research on its properties under the action of a DC field is still deficient. Here, a metal-cladding optical waveguide, which is composed of a chalcogenide glass film coated on a glass substrate, is presented to analyze the quadratic electro-optic (QEO) effect of the chalcogenide glass film. The DC Kerr coefficient and the whole components of the QEO tensor of the sample were experimentally determined by the free space coupling method. Chalcogenide ; Materials science ; Supercontinuum ; Kerr effect ; Chalcogenide glass ; Cladding (metalworking) ; Optics ; Coupling (piping) ; Optoelectronics ; Nonlinear system ; Physics ; Composite material ; Photonic-crystal fiber Phase-change materials and chalcogenides ; Nonlinear Optical Materials Studies ; Photonic and Optical Devices
Authors: Jie Li | Zhiyuan Yu | Luoyi Li | Kaixuan Zhang | Qiliang Li | Yu Shao | Shuo Chen
Source: Journal of Applied Physics (article, 2024-12-27)
Field: Materials Science — Materials Chemistry

The ordering behaviors of liquid under many-body dissipative particle dynamics potential at solid–liquid interface This study utilizes many-body dissipative particle dynamics to analyze in detail the structural orderings of liquid density, stress, and other physical properties near solid–liquid (S-L) interfaces, examining their relationship with S-L and liquid–liquid (L-L) interaction potentials. By discerning the individual contributions from different phases to the overall force profile, our research reveals that the mutual influence between forces and density variations causes the wall’s impact to extend several multiples beyond the cutoff radius. Through a variety of scenarios involving different potentials, we demonstrate that the stratification period is a fundamental characteristic of the liquid phase, unaffected by the type of solid or the specific S-L interaction potential. Besides, the distance of the first liquid layer from the solid substrate is positively correlated with the position of zero potential (σ) of the S-L potential. Moreover, the oscillation amplitude of the density profiles does not necessarily increase monotonically with hydrophilicity, instead depends on the specific potential form and is a competing outcome of the two S-L potential parameters σ, and ε (the minimum potential energy). Therefore, for cases with the same wettability (e.g., the same liquid but different solids), the density ordering profiles may not completely align. Dissipative particle dynamics ; Dissipative system ; Interface (matter) ; Particle (ecology) ; Dynamics (music) ; Chemical physics ; Liquid liquid ; Materials science ; Physics ; Mechanics ; Classical mechanics ; Statistical physics ; Condensed matter physics ; Thermodynamics ; Chemistry ; Wetting ; Chromatography ; Geology ; Polymer ; Composite material Block Copolymer Self-Assembly ; Material Dynamics and Properties ; Spectroscopy and Quantum Chemical Studies
Authors: Eliza Flores-Souza | Alisson Samuel Portes Caldeira | Carolina Colombelli Pacca Mazaro | Tamiris Vanessa Miguel-de Souza | Thaís M. Acácio | Emerson Castro | Douglas E. V. Pires | Naiara Clemente Tavares | Carlos Eduardo Calzavara-Silva | Carlos Leomar Zani | Jaquelline Germano de Oliveira | Tânia Maria de Almeida Alves
Source: Preprints.org (preprint, 2024-07-22)
Field: Chemistry — Organic Chemistry

Antivirals for Yellow Fever: Bioassay-Guided Fractionation of Hippeastrum puniceum Bulb Extract with Inhibitory Activity against Wild-Type Yellow Fever Virus and In Silico ADMET Prediction of the Annotated Natural Compounds Despite effective vaccines, yellow fever outbreaks persist, increasing the urgency to find antivirals for patient treatment. This study aimed to discover compounds with potential antiviral properties against the wild-type yellow fever virus (wt-YFV) in Hippeastrum puniceum, of the Amaryllidaceae family, through bioassay-guided fractionation of the crude bulb extract using ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution ESI-QTOF mass spectrometry and subsequent analysis of the pharmacokinetic and toxicological properties (ADMET) of the annotated compounds. In the active fractions against wt-YFV, six alkaloids were proposed such as bulbisine, cathinone, trigonelline, tetrahydroharman-3-carboxylic acid, and 2,7-dimethoxyhomolycorine (or 3-O-acetylnarcissidine). Co-occurring in these fractions were the amino acids arginine, asparagine, tryptophan, and glutamic acid. In silico ADMET analysis of the alkaloids predicted good absorption, distribution, excretion, favorable metabolization profiles, and non-mutagenic toxicity, indicating their potential for drug development. These findings justify further in vitro assessment of the compounds against YFV and in vivo testing in animal models. This strategy seems to be an efficient approach for discovering antiviral compounds against YFV. Such discoveries hold promise not only in combating YFV but also in addressing a spectrum of other flaviviruses. In silico ; Bioassay ; Chemistry ; Virus ; Biology ; Virology ; Biochemistry Chemical synthesis and alkaloids ; Alkaloids: synthesis and pharmacology ; Psychedelics and Drug Studies
Source: ChemBioEng Reviews (article, 2024-02-01)
Field: Materials Science — Materials Chemistry

Table of Contents: ChemBioEng Reviews 1/2024 Effective biobased thermally insulating materials are needed to address growing concerns of both climate change and plastic waste.Many experimental biobased foams exhibit equal or superior properties as traditional thermally insulating foams.This review targets recent developments in biobased foams for use in residential construction, their fabrication methods, and future prospects. Table (database) ; Citation ; Table of contents ; Computer science ; Information retrieval ; World Wide Web ; Library science ; Database Advanced Nanomaterials in Catalysis ; Advanced Photocatalysis Techniques ; Microbial Fuel Cells and Bioremediation
Authors: Lijie Ding | Chi-Huan Tung | Bobby G. Sumpter | Wei-Ren Chen | Changwoo Do
Source: arXiv (Cornell University) (preprint, 2024-09-23)
Field: Materials Science — Polymers and Plastics

Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers We develop off-lattice simulations of semiflexible polymer chains subjected to applied mechanical forces using Markov Chain Monte Carlo. Our approach models the polymer as a chain of fixed-length bonds, with configurations updated through adaptive non-local Monte Carlo moves. This proposed method enables precise calculation of a polymer's response to a wide range of mechanical forces, which traditional on-lattice models cannot achieve. Our approach has shown excellent agreement with theoretical predictions of persistence length and end-to-end distance in quiescent states, as well as stretching distances under tension. Moreover, our model eliminates the orientational bias present in on-lattice models, which significantly impacts calculations such as the scattering function, a crucial technique for revealing polymer conformation. Markov chain Monte Carlo ; Monte Carlo method ; Statistical physics ; Markov chain ; Polymer ; Lattice (music) ; Markov chain mixing time ; Parallel tempering ; Monte Carlo molecular modeling ; Materials science ; Mathematics ; Physics ; Markov model ; Markov property ; Statistics ; Composite material Polymer Foaming and Composites ; Orthopaedic implants and arthroplasty ; Polymer crystallization and properties
Authors: Kaicheng Chen | Sukhoiri Khoiruddin | Chieh-Fong Lin | M.H. Ho | Cheng‐Fu Huang | Sheng‐Chan Lee | Chien‐Wei Chan | Intan Mardiono | Yiin‐Kuen Fuh
Source: Research Square (preprint, 2024-03-11)
Field: Materials Science — Polymers and Plastics

Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts Quality (philosophy) ; Casting ; Investment (military) ; Investment casting ; Business ; Agricultural engineering ; Manufacturing engineering ; Industrial organization ; Engineering ; Materials science ; Composite material ; Physics ; Mold Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies
Authors: Ali Akbar Saberi | Seid Zabihalla Ravari | Ahmad Mehrban | Hamid Reza Ganjali | Hassan Amiri Oghan
Source: Research Square (preprint, 2024-01-22)
Field: Chemistry — Analytical Chemistry

Using artificial neural network to evaluate salinity indices to identify rapeseed salinity tolerant cultivars Salinity ; Rapeseed ; Cultivar ; Artificial neural network ; Environmental science ; Agronomy ; Biology ; Computer science ; Artificial intelligence ; Ecology Spectroscopy and Chemometric Analyses ; Genetics and Plant Breeding ; Nitrogen and Sulfur Effects on Brassica