jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sandip Thite | Deepali Godse | Kailas Patil | Prawit Chumchu | Alfa Nyandoro
Source: Data in Brief (article, 2024-09-21)
Field: Chemistry — Analytical Chemistry

Facilitating spice recognition and classification: An image dataset of Indian spices This data paper presents a comprehensive visual dataset of 19 distinct types of Indian spices, consisting of high-quality images meticulously curated to facilitate various research and educational applications. The dataset includes extensive imagery of the following spices: Asafoetida, Bay Leaf, Black Cardamom, Black Pepper, Caraway Seeds, Cinnamon Stick, Cloves, Coriander Seeds, Cubeb Pepper, Cumin Seeds, Dry Ginger, Dry Red Chilly, Fennel Seeds, Green Cardamom, Mace, Nutmeg, Poppy Seeds, Star Anise, and Stone Flowers. Each image in the dataset has been captured under controlled conditions to ensure consistency and clarity, making it an invaluable resource for studies in food science, agriculture, and culinary arts. The dataset can also support machine learning and computer vision applications, such as spice recognition and classification. By providing detailed visual documentation, this dataset aims to promote a deeper understanding and appreciation of the rich diversity of Indian spices. Spice ; Computer science ; Pattern recognition (psychology) ; Research article ; Artificial intelligence ; Information retrieval ; Engineering ; Library science Spectroscopy and Chemometric Analyses ; GABA and Rice Research ; Coconut Research and Applications
Authors: A. Dalvin Vinoth kumar | Harsimran Singh | Devinder Kumar | Vineet Kapoor
Source: Journal for Research in Applied Sciences and Biotechnology (review, 2024-06-28)
Field: Chemistry — Spectroscopy

Ethanopharmacology of Myrica esculenta: A Systemic Review This systematic review focuses on Myrica Esculenta, a medicinal plant with a rich history in traditional medicine. The aim of the review is to provide a comprehensive overview of the ethnopharmacology of the plant, including its traditional uses, phytochemistry and pharmacological benefits. Common uses of M. Esculenta include treating respiratory diseases such as asthma and bronchitis, as well as gastrointestinal problems such as diarrhea and ulcers. The plant is also used to treat fever, anemia and various ear, nose and throat diseases. With its recognition in the Ayurvedic Pharmacopoeia and its widespread use in folk medicine, M. Esculenta has significant ethnopharmacological value. Through phytochemical analysis, flavonoids, tannins, steroids and terpenes have been identified as the plant's main components, which are believed to contribute to its medicinal properties such as analgesic, anti-inflammatory, antioxidant and anti-cancer effects. Pharmacological studies have confirmed the therapeutic potential of M. Esculenta and demonstrated its antiasthmatic, antiulcerative, anxiolytic, hepatoprotective and wound healing properties. Conservation measures are crucial to protect the plant from over-exploitation and habitat loss. Suggestions such as micropropagation, germplasm preservation and synthetic seed production make sense for sustainable use. Myrica rubra ; Botany ; Biology Analytical Chemistry and Chromatography ; Phytochemicals and Antioxidant Activities ; Genomics, phytochemicals, and oxidative stress
Authors: William Yamada | Jerry H. Cherney | D. J. R. Cherney | Troy Runge | Matthew F. Digman
Source: Sensors (article, 2024-08-08)
Field: Chemistry — Analytical Chemistry

Handheld Near-Infrared Spectroscopy for Undried Forage Quality Estimation This study investigates the efficacy of handheld Near-Infrared Spectroscopy (NIRS) devices for in-field estimation of forage quality using undried samples. The objective is to assess the precision and accuracy of multiple handheld NIRS instruments-NeoSpectra, TrinamiX, and AgroCares-when evaluating key forage quality metrics such as Crude Protein (CP), Neutral Detergent Fiber (aNDF), Acid Detergent Fiber (ADF), Acid Detergent Lignin (ADL), in vitro Total Digestibility (IVTD)and Neutral Detergent Fiber Digestibility (NDFD). Samples were collected from silage bunkers across 111 farms in New York State and scanned using different methods (static, moving, and turntable). The results demonstrate that dynamic scanning patterns (moving and turntable) enhance the predictive accuracy of the models compared to static scans. Fiber constituents (ADF, aNDF) and Crude Protein (CP) show higher robustness and minimal impact from water interference, maintaining similar R2 values as dried samples. Conversely, IVTD, NDFD, and ADL are adversely affected by water content, resulting in lower R2 values. This study underscores the importance of understanding the water effects on undried forage, as water's high absorption bands at 1400 and 1900 nm introduce significant spectral interference. Further investigation into the PLSR loading factors is necessary to mitigate these effects. The findings suggest that, while handheld NIRS devices hold promise for rapid, on-site forage quality assessment, careful consideration of scanning methodology is crucial for accurate prediction models. This research contributes valuable insights for optimizing the use of portable NIRS technology in forage analysis, enhancing feed utilization efficiency, and supporting sustainable dairy farming practices. Neutral Detergent Fiber ; Forage ; Mobile device ; Near-infrared spectroscopy ; Environmental science ; Computer science ; Agronomy ; Biology Spectroscopy and Chemometric Analyses ; Ruminant Nutrition and Digestive Physiology ; Effects of Environmental Stressors on Livestock
Authors: Hong-Ju He | Yuling Wang | Shengqi Jiang | Jie Zhang | Jicai Bi | Hong Qiao | Leiqing Pan | Xingqi Ou
Source: Foods (article, 2024-11-18)
Field: Chemistry — Analytical Chemistry

Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging This study investigated and comprehensively compared the performance of spectra (950-1660 nm) acquired respectively from NIR and HSI in the rapid and non-destructive quantification of azodicarbonamide (ADA) content (0-100 mg/kg) in WF and simultaneously identified WF containing excessive ADA (>45 mg/kg). The raw spectra were preprocessed using 14 methods and then mined by the partial least squares (PLS) algorithm to fit ADA levels using different numbers of WF samples for training and validation in five datasets (N<sub>Training</sub>/<sub>Validation</sub> = 189/21, 168/42, 147/63, 126/84, 105/105), yielding better abilities of NIR Savitzky-Golay 1st derivative (SG1D) spectra-based PLS models and raw HSI spectra-based PLS models in quantifying ADA with higher determination coefficients and lower root-mean-square errors in validation (R<sup>2</sup><sub>V</sub> & RMSEV), as well as establishing 100% accuracy in PLS discriminant analysis (PLS-DA) models for identifying excessive ADA-contained WF in each dataset. Twenty-four wavelengths selected from a NIR SG1D spectra in a 168/42 dataset and 23 from a raw HSI spectra in a 147/63 dataset allowed for the better performance of quantitative models in ADA determination with higher R<sup>2</sup><sub>V</sub> and RMSE<sub>V</sub> in validation (R<sup>2</sup><sub>V</sub> > 0.98, RMSE<sub>V</sub> < 3.87 mg/kg) and for discriminant models in WF classification with 100% accuracy. In summary, NIR technology may be sufficient if visualization is not required. Hyperspectral imaging ; Linear discriminant analysis ; Chemical imaging ; Near-infrared spectroscopy ; Spectroscopy ; Chemometrics ; Chemistry ; Mathematics ; Pattern recognition (psychology) ; Chromatography ; Artificial intelligence ; Biology ; Statistics ; Computer science ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Meat and Animal Product Quality
Authors: Eistiak Ahamed | Rasool Keshavarz | Negin Shariati
Source: Scientific Reports (article, 2024-11-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Epsilon negative dynamic coded THz metamaterial beamformer for digital information encryption Light propagation facilitates digital information encryption by utilizing Epsilon Negative (ENG) metamaterials as a medium. Achieving the desired encryption hinges on synchronizing two pivotal features: the phase difference and the epsilon shifting of the metamaterials. The proposed metamaterial is intricately designed to represent digital bit 1 (states 0 and 1), contingent upon the arrangement of material multilayers within the metamaterial device. Specifically, state 1 is fashioned through a combination of Graphene and Gold, while state 0 is solely represented by Graphene on a metamaterial structure. The developed structure exhibits right hand metamaterial (epsilon of [Formula: see text]7.20) for state 0 and plasma metamaterial (epsilon [Formula: see text]6.94) for state 1 at 8.6 THz. Notably, the phase difference between 0 and 1 states is around [Formula: see text]. Primarily leveraging the synchronized combination phase and epsilon as the key design parameters for the metamaterial array, the beamforming pattern enables beam steering within the angular range of [Formula: see text] to [Formula: see text]. Secondly, employing a sophisticated material addition strategy involving Gallium Arsenide (GaAs) systematically manipulates the sidelobe in specific directions, thereby providing a mechanism to modulate the sidelobe and concurrently augment spatial resolution. After preparing the metamaterial coded (MC) lens, the source, lens and receiver strategically encrypt the scanning image, employing techniques including Doppler compression and 2D discrete Fourier transform. The proposed MC lens offers applicability like image encryption, security scanning, conveyor systems, hyperlenses and modern cryptography. Encryption ; Metamaterial ; Terahertz radiation ; Computer science ; Acoustics ; Physics ; Medicine ; Optoelectronics ; Computer security Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Divyanshu S. Morghode | D. G. Thakur | Sachin Salunkhe | Lenka Cepova | Emad Abouel Nasr
Source: Frontiers in Mechanical Engineering (article, 2024-07-25)
Field: Materials Science — Materials Chemistry

Analysis of the thickness of layered armor to provide protection against 7.62 mm ball projectiles using experimental and numerical methods The layered configuration of different material plates is one of the ways of achieving protection against different kinds of kinetic energy ammunitions. The thickness of each plate is one of the most important influencing parameters to prevent the penetration of the projectile. In the present study, a layered configuration of the Al 2 O 3 and Al 7075-T651 is analysed, to prevent the perforation of 7.62 mm Lead core projectile, under normal impact conditions, by using LS-DYNA numerical simulations. Experiments were conducted on Al 7075-T651 plate and Numerical model was validated with experiment results. To achieve the objective, the validated numerical model was used to investigate influence on various Al 2 O 3 and Al 7075-T651 combinations. Three factors led to the selection of Al 7075-T561 and Al 2 O 3 as the target materials. First, the literature review revealed that these materials have already been employed in the construction of armour. Second, Al 2 O 3 is a brittle material whereas Al 7075-T651 is ductile. Consequently, when combined in a layered arrangement, these materials offer the ideal destroyer-absorber arrangement. Thirdly, these materials have lower densities than steel. As a result, these materials offer a lightweight alternative for lead core 7.62 mm bullet defense. From the analysis, it is observed that two layered configurations were found to be effective in the prevention of bullet perforation: a front plate of Al 2 O 3 that was 10 mm thick and had a rear plate of Al 7075-T651 that was 06 mm thick, and a front plate of Al 2 O 3 that was 04 mm thick and had a 12 mm thick layer of Al 7075-T651. Armour ; Projectile ; Materials science ; Brittleness ; Perforation ; Composite material ; Core (optical fiber) ; Ball (mathematics) ; Ammunition ; Ballistic limit ; Structural engineering ; Metallurgy ; Engineering ; Layer (electronics) High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Electromagnetic Launch and Propulsion Technology
Authors: A. Palaev G. | Zhang Fuming | Yifan Tang
Source: International Journal of Engineering (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Method for Assessing Damage to Gas Distribution Network Pipelines based on Nonlinear Guided Wave Polyethylene pipeline is an essential infrastructure of gas distribution network, and there are some problems such as complex damage assessment and tedious assessment process. How to choose an effective damage assessment method for polyethylene pipelines is the focus of the implementation of the gas distribution network at present. In this paper, a nonlinear directional wave method is proposed to detect the damage of polyethylene pipeline by an acoustic wave, and the damage results of polyethylene pipeline are searched. The rationality of this method is verified by calculating the aerodynamic equation.The results show that the nonlinear fixed wave method can accurately determine the damage and crack propagation degree of the pipeline and simplify the damage assessment process, and the results are superior to the linear directional wave method. Therefore, the nonlinear directional wave can be used to assess the damage to ethylene pipelines in gas distribution networks, which has strong rationality and practicality and provides support for the actual pipeline damage assessment. Nonlinear system ; Pipeline transport ; Distribution (mathematics) ; Environmental science ; Petroleum engineering ; Computer science ; Engineering ; Physics ; Mathematics ; Mathematical analysis ; Environmental engineering Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Coal Combustion and Slurry Processing
Authors: Sitti Amalia | Hamdi Azhar | Bayu Hidayatullah | Abdul Rajab | Novizon Novizon | Yusreni Warmi | Andre Febrian Kasmar
Source: TEM Journal (article, 2024-02-27)
Field: Materials Science — Materials Chemistry

The Effect of Humidity and Temperature on Flashover in High Voltage Transmission Line Ceramic Insulators This research aims to determine the flashover voltage on the surface of porcelain insulators on 150 kV transmission lines located in Payakumbuh, where the insulators are contaminated with dust and moss due to the effects of temperature and humidity. The experiment is carried out with only up to seven insulator plates due to the limitations of the available apparatus. For the further testing, a trend analysis is applied. According to the experimental results, a rise in temperature around the insulator will increase the flashover voltage value and accelerate the potential for a flashover event. This happens because high temperatures can reduce the insulator's dielectric strength and insulation resistance and increase the risk of flashover. The dielectric strength values decreased with an average decrease of 44.62% per insulator plate for dusty insulators and 45.08% for each plate for mossy insulators. The results aim to minimize flashover on transmission lines in hilly areas with relatively high contamination. Arc flash ; Insulator (electricity) ; Materials science ; Composite material ; Humidity ; Dielectric ; Electric power transmission ; Transmission line ; Dielectric strength ; Ceramic ; Electrical engineering ; Optoelectronics ; Engineering ; Meteorology ; Physics High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Thermal Analysis in Power Transmission
Authors: Carmela Riefolo | Laura D’Andrea
Source: Experimental Agriculture (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

A non-destructive approach in proximal sensing to assess the performance distribution of SPAD prediction models using hyperspectral analysis in apricot trees Summary SPAD combined with hyperspectral sensors can be an alternative approach to traditional laboratory methods for determining the physiological status of trees. The aim of this work was to assess whether the effectiveness of SPAD predictive models using hyperspectral data might be influenced by where the measurements were carried out. Leaves of apricot trees of two varieties (Farbaly and Farlis) were analysed with SPAD and spectroradiometer, and the data were organized in two different ways: (i) overall dataset (OD), collecting total measurements of trees in each variety; (ii) subset of overall datasets (SOD), collecting the measurements performed on the cardinal points of trees in each variety. Prediction models were built using as regressors: (i) spectral data transformed with Continuum Removal (CR) methodology (CR indices); (ii) vegetation indices (VI) linked to chlorophyll and nitrogen content; (iii) reflectance values associated with chlorophyll content and to wavelengths ranges where (CR) methodology was applied; (iv) reflectance values of full spectrum. The best performances belonged to models using wider ranges of spectrum both in ODs and in SODs. The north cardinal point showed prediction models with the best performances in both varieties. No VI and CR indices showed reliable models. All the reliable prediction models were associated with compounds involved in physiological state and metabolism of leaves in apricot tree. Hyperspectral imaging ; Distribution (mathematics) ; Remote sensing ; Computer science ; Artificial intelligence ; Environmental science ; Pattern recognition (psychology) ; Mathematics ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote Sensing and LiDAR Applications
Authors: C.R. Fernandes | J. Ventura | D J Silva
Source: Heliyon (article, 2024-05-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Impact of different numerical approaches on the magnetocaloric effect modeling As an ecological alternative to the conventional refrigeration technology, magnetocaloric refrigeration is still facing scientific and technological challenges hindering their application. Magnetocaloric devices rely on the magnetocaloric effect, where temperature variations result from magnetic field changes. The correct implementation of the magnetocaloric effect in numerical models is crucial before prototyping the related solutions. Here, we present a comparison between the three most used numerical methods to simulate the magnetocaloric effect: continuous temperature change, discrete temperature change step and heat source obtained from adiabatic temperature. By varying the time and space steps, it was observed that the continuous temperature change method is the most appropriate for small time steps, but has the largest computational cost. The discrete method can only be applied to small time steps, but is the fastest method. Finally, the adiabatic temperature change power source method can be applied in the entire range and is the one that presents the best results for larger time steps. Magnetic refrigeration ; Adiabatic process ; Refrigeration ; Materials science ; Power (physics) ; Thermodynamics ; Computer simulation ; Range (aeronautics) ; Magnetic field ; Process engineering ; Computer science ; Simulation ; Physics ; Engineering ; Magnetization Magnetic and transport properties of perovskites and related materials ; Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials
Authors: Yassmin El morabit | Mohammed El Maadoudi | Naoual Alahlah | Hassan Amhamdi | Amin Salhi | M’hamed Ahari
Source: BIO Web of Conferences (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Detection and quantification of olive oil adulteration using fluorescence spectroscopy and chemometric tools The increasing incidence of fraud in the olive oil market, particularly through adulteration with cheaper oils, poses a major challenge for the industry. This study examines the effectiveness of fluorescence spectroscopy combined with chemometric tools as a method to detect and quantify olive oil adulteration. Chemical analyses were used to measure parameters such as specific absorption coefficients K232 and K270, peroxide value, and acidity, in accordance with International Olive Council (IOC) standards. These measurements were conducted on samples of olive oil blended with varying percentages of adulterating oils. 3D fluorescence spectra were analyzed to examine the changes induced by adulteration. The results show that free acidity and peroxide value decrease with increasing adulteration degree, while the parameters K232 and K270 increase with the degree of adulteration. Principal component analysis (PCA) was effectively used to differentiate samples based on the percentage of adulterant. A partial least squares (PLS) regression model was developed, achieving a correlation coefficient of 0.999 for predicting the percentage of adulterant in olive oil. This PLS model also proved effective in predicting oil quality parameters such as free acidity and K232 and K270 indices. The results of this study demonstrate the significant potential of fluorescence spectroscopy as a rapid and non-destructive method for olive oil authentication. PCA emerges as a powerful tool for characterizing pure oils without requiring sample preparation or destruction. Furthermore, PLS models provide accurate means to predict both the presence of adulterants and olive oil quality parameters. This approach offers a promising solution to combat fraud in the olive oil industry, ensuring product integrity and quality. Olive oil ; Fluorescence spectroscopy ; Chemometrics ; Chromatography ; Fluorescence ; Chemistry ; Analytical Chemistry (journal) ; Environmental chemistry ; Food science Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Identification and Quantification in Food
Authors: Zhiyong Zhang | Shuo Wang | Chen Wang | Li Wang | Yanqing Zhang | Haiyan Song
Source: Agriculture (article, 2024-09-12)
Field: Chemistry — Analytical Chemistry

Segmentation Method of Zanthoxylum bungeanum Cluster Based on Improved Mask R-CNN The precise segmentation of Zanthoxylum bungeanum clusters is crucial for developing picking robots. An improved Mask R-CNN model was proposed in this study for the segmentation of Zanthoxylum bungeanum clusters in natural environments. Firstly, the Swin-Transformer network was introduced into the model’s backbone as the feature extraction network to enhance the model’s feature extraction capabilities. Then, the SK attention mechanism was utilized to fuse the detailed information into the mask branch from the low-level feature map of the feature pyramid network (FPN), aiming to supplement the image detail features. Finally, the distance intersection over union (DIOU) loss function was adopted to replace the original bounding box loss function of Mask R-CNN. The model was trained and tested based on a self-constructed Zanthoxylum bungeanum cluster dataset. Experiments showed that the improved Mask R-CNN model achieved 84.0% and 77.2% in detection mAP50box and segmentation mAP50mask, respectively, representing a 5.8% and 4.6% improvement over the baseline Mask R-CNN model. In comparison to conventional instance segmentation models, such as YOLACT, Mask Scoring R-CNN, and SOLOv2, the improved Mask R-CNN model also exhibited higher segmentation precision. This study can provide valuable technology support for the development of Zanthoxylum bungeanum picking robots. Zanthoxylum ; Segmentation ; Artificial intelligence ; Computer science ; Botany ; Biology Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Traditional Chinese Medicine Studies