jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Muhammad Abdurrahman Munir | Ahlam Inayatullah | Sofian Ibrahim | Imram Radne Rimba Putri | EMELDA EMELDA | ANNISA FATMAWATI | NURHIDAYANTI NURHIDAYANTI
Source: International Journal of Applied Pharmaceutics (article, 2023-01-07)
Field: Chemistry — Analytical Chemistry

A MODEST UV SPECTROPHOTOMETRIC ASSISTED BY CHEMOMETRIC APPROACH FOR VERIFICATION OF ACETAMINOPHEN LEVEL IN VARIOUS MANUFACTURED TABLETS AND SYRUPS IN INDONESIAN PHARMACIES Objective: This study aimed to verify the paracetamol level in some fabricated tablets and syrups in Indonesian pharmacies. Methods: The fabricated tablets and syrups were analyzed using a spectrophotometer UV that was assisted by the chemometric approach. Partial least squares (PLS) and principal component regression (PCR) were the chemometric methods employed to verify the paracetamol level in pharmaceutical products. There were 25 different samples (tablets and syrups) applied in this study. The validation study was employed in this study to verify the approach according to the ICH guidelines. The double-distilled water was applied as a solvent before the samples were analyzed using a spectrophotometer. Results: This technique was efficient and require double-distilled water only as a solvent. The results of this study reveal that there was a deviation in absorbance of the samples with RSD ranging from (0.15-0.45). The technique was linear, ranging from 1.0–6.0 µg·ml-1, with an R2 (0.9991) obtained at 242 nm. The percentage recovery was applied to study the accuracy of the technique and was acquired at 99.18%. The results have shown that the approach was the potential to be applied in estimating the level of paracetamol in tablets and syrups. Conclusion: The detection of paracetamol levels in tablets and syrups using UV spectrophotometric showed satisfactory outcomes. The application of the chemometric approach by using PLC and PCR as the statistical assessment indicated that there was no significant distinction among the validated methods. Furthermore, the method can be used by industries particularly small industries to secure medicines that comply with Indonesian rules. Chromatography ; Distilled water ; Principal component regression ; Partial least squares regression ; Chemometrics ; Chemistry ; Absorbance ; Solvent ; Linear regression ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Analytical Methods in Pharmaceuticals ; Advanced Chemical Sensor Technologies
Authors: Buddhi Dayananda | Priyam Chahwala | Daniel Cozzolino
Source: AppliedChem (article, 2023-09-01)
Field: Chemistry — Analytical Chemistry

The Ability of Near-Infrared Spectroscopy to Discriminate Plant Protein Mixtures: A Preliminary Study The aim of this paper was to evaluate the effect of two different matrices (e.g., starch base flour vs. protein base flour) on the ability of near-infrared (NIR) spectroscopy to classify binary mixtures of chickpea (protein), corn and tapioca (starch) flours. Binary mixtures were made by mixing different proportions of chickpea plus corn, chickpea plus tapioca, and corn plus tapioca flour. Spectra were collected using NIR spectroscopy and the data analyzed using techniques such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The results showed an effect of the matrix on the PLS-DA classification results, in both classification rates and PLS loadings. The different combinations of flours/mixtures showed changes in absorbance values around 4752 cm−1 that are associated with starch and protein. Nevertheless, the use of NIR spectroscopic might provide a valuable initial screening and identification of the potential contamination of flours along the supply and value chains, enabling more costly methods to be used more productively on suspect samples. Principal component analysis ; Absorbance ; Starch ; Linear discriminant analysis ; Wheat flour ; Chemometrics ; Food science ; Partial least squares regression ; Near-infrared spectroscopy ; Spectroscopy ; Chemistry ; Analytical Chemistry (journal) ; Mathematics ; Chromatography ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Identification and Quantification in Food
Authors: Yaohua Hu | Yichen Qiao | Bingru Hou | Zhanghao Qu | Peng Zhang | Runzhe Han | Jiapan Guo
Source: Infrared Physics & Technology (article, 2023-12-04)
Field: Chemistry — Analytical Chemistry

Building models to evaluate internal comprehensive quality of apples and predict storage time Mean squared error ; Calibration ; Coefficient of determination ; Partial least squares regression ; Correlation coefficient ; Computer science ; Statistics ; Quality (philosophy) ; Mathematics ; Physics Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Horticultural and Viticultural Research
Authors: June Anne Caladcad | Eduardo Piedad
Source: Data in Brief (article, 2023-01-26)
Field: Chemistry — Inorganic Chemistry

Acoustic dataset of coconut (Cocos nucifera) based on tapping system During the fruit sample preparation process, coconut fruits classified under the tall coconut variety in their post-harvest period are considered the subject of this article. All samples are pre-classified by local farmers and experts into three maturity levels; premature, mature, and overmature. Each coconut underwent the synchronized tapping and recording process using developed hardware and software. The analog recordings are then converted into digital signals. Sampled frequency and amplitude in discrete-time signals of each sample went through a quantization process. The data presented in this article provides the general differentiation of the coconuts according to their maturity levels through their acoustic properties. This dataset can also be useful in creating an advanced and intelligent classification system of fruits through machine learning and deep learning techniques. Cocos nucifera ; Tapping ; Computer science ; Maturity (psychological) ; Process (computing) ; Sample (material) ; Agricultural engineering ; Horticulture ; Biology ; Acoustics ; Engineering ; Chemistry Coconut Research and Applications ; Advanced Chemical Sensor Technologies ; Smart Agriculture and AI
Authors: Manish Kumar | Gopinath Bej | Himanshu Pandey
Source: Journal of Experimental Agriculture International (review, 2023-03-22)
Field: Chemistry — Inorganic Chemistry

Status and Scope of Automated Coconut Harvester in India: A Review Coconut plays a substantial role in the Indian economy. South Indian states, namely Kerala, Karnataka, Tamil Nadu, and Andhra Pradesh are the leading producers accounting for more than 90% of the total coconut produced in the country. The traditional/conventional process of coconut harvesting includes climbing on the tree and cutting the coconut bunches with a cutter, which involves high risk. Climbing on a coconut tree is the main risk factor and it is life-threatening. The present review paper presents the status and future research need for automated coconut harvesting machines in India. The maximum speed or climbing with remote controlled coconut harvester was reported 0.055 ms-1. This paper also focuses on the basic components of the automated coconut harvesting machine, as well as the advantages and disadvantages of each component are critically analyzed based on its findings, future research needs are proposed in order to meet all the fundamental aspects of autonomous coconut harvesting machines. Tamil ; Scope (computer science) ; Agricultural engineering ; Mathematics ; Agroforestry ; Engineering ; Agricultural science ; Business ; Computer science ; Environmental science Coconut Research and Applications ; Date Palm Research Studies
Authors: Ewa Ropelewska | Justyna Szwejda‐Grzybowska
Source: Foods (article, 2023-05-24)
Field: Chemistry — Analytical Chemistry

The Estimation of Chemical Properties of Pepper Treated with Natural Fertilizers Based on Image Texture Parameters The cultivar and fertilization can affect the physicochemical properties of pepper fruit. This study aimed at estimating the content of α-carotene, β-carotene, total carotenoids, and the total sugars of unfertilized pepper and samples treated with natural fertilizers based on texture parameters determined using image analysis. Pearson's correlation coefficients, scatter plots, regression equations, and coefficients of determination were determined. For red pepper Sprinter F<sub>1</sub>, the correlation coefficient (<i>R</i>) reached 0.9999 for a texture from color channel B and -0.9999 for a texture from channel <i>Y</i> for the content of α-carotene, -0.9998 (channel <i>a</i>) for β-carotene, 0.9999 (channel <i>a</i>) and -0.9999 (channel <i>L</i>) for total carotenoids, as well as 0.9998 (channel <i>R</i>) and -0.9998 (channel <i>a</i>) for total sugars. The image textures of yellow pepper Devito F<sub>1</sub> were correlated with the content of total carotenoids and total sugars with the correlation coefficient reaching -0.9993 (channel <i>b</i>) and 0.9999 (channel <i>Y</i>), respectively. The coefficient of determination (R<sup>2</sup>) of up to 0.9999 for α-carotene content and the texture from color channel <i>Y</i> for pepper Sprinter F<sub>1</sub> and 0.9998 for total sugars and the texture from color channel <i>Y</i> for pepper Devito F<sub>1</sub> were found. Furthermore, very high coefficients of correlation and determination, as well as successful regression equations regardless of the cultivar were determined. Texture (cosmology) ; Pepper ; Estimation ; Artificial intelligence ; Biological system ; Natural (archaeology) ; Image (mathematics) ; Pattern recognition (psychology) ; Mathematics ; Computer vision ; Agronomy ; Environmental science ; Computer science ; Biology ; Food science ; Engineering Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Food Drying and Modeling
Authors: Andy Lin | Donavan See | William E. Fondrie | Uri Keich | William Stafford Noble
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-06-20)
Field: Chemistry — Spectroscopy

Target-decoy false discovery rate estimation using Crema Abstract Assigning statistical confidence estimates to discoveries produced by a tandem mass spectrometry proteomics experiment is critical to enabling principled interpretation of the results and to assess the cost/benefit ratio of experimental follow-up. The most common technique for computing such estimates is to use target-decoy competition (TDC), in which observed spectra are searched against a database of real (target) peptides and a database of shuffled or reversed (decoy) peptides. TDC procedures for estimating the false discovery rate (FDR) at a given score threshold have been developed for application at the level of spectra, peptides, or proteins. Although these techniques are relatively straightforward to implement, it is common in the literature to skip over the implementation details or even to make mistakes in how the TDC procedures are applied in practice. Here we present Crema, an open source Python tool that implements several TDC methods of spectrum-, peptide- and protein-level FDR estimation. Crema is compatible with a variety of existing database search tools and provides a straightforward way to obtain robust FDR estimates. Decoy ; False discovery rate ; Python (programming language) ; Computer science ; Data mining ; False positive rate ; Artificial intelligence ; Chemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Krishna K. Raut | Samjhana Pandey | Gyanendra Kharel | Steven M. Pascal
Source: Protein Science (article, 2023-12-14)
Field: Materials Science — Biomaterials

Evidence of direct interaction between cisplatin and the caspase‐cleaved prostate apoptosis response‐4 tumor suppressor Prostate apoptosis response-4 (Par-4) tumor suppressor protein has gained attention as a potential therapeutic target owing to its unique ability to selectively induce apoptosis in cancer cells, sensitize them to chemotherapy and radiotherapy, and mitigate drug resistance. It has recently been reported that Par-4 interacts synergistically with cisplatin, a widely used anticancer drug. However, the mechanistic details underlying this relationship remain elusive. In this investigation, we employed an array of biophysical techniques, including circular dichroism spectroscopy, dynamic light scattering, and UV-vis absorption spectroscopy, to characterize the interaction between the active caspase-cleaved Par-4 (cl-Par-4) fragment and cisplatin. Additionally, elemental analysis was conducted to quantitatively assess the binding of cisplatin to the protein, utilizing inductively coupled plasma-optical emission spectroscopy and atomic absorption spectroscopy. Our findings provide evidence of direct interaction between cl-Par-4 and cisplatin, and reveal a binding stoichiometry of 1:1. This result provides insights that could be useful in enhancing the efficacy of cisplatin-based and tumor suppressor-based cancer therapies. Cisplatin ; Apoptosis ; Chemistry ; Circular dichroism ; Cancer research ; Prostate cancer ; Suppressor ; Biophysics ; Chemotherapy ; Cancer ; Biochemistry ; Biology ; Medicine ; Internal medicine ; Gene Nanoparticle-Based Drug Delivery ; Metal complexes synthesis and properties ; Protein Interaction Studies and Fluorescence Analysis
Authors: Alessio Di Fatta | Antonino Imburgia | Giuseppe Rizzo | Ghulam Akbar | Vincenzo Li Vigni | Pietro Romano | Guido Ala
Source:  (article, 2023-10-15)
Field: Materials Science — Materials Chemistry

Modified Hierarchical Clustering Algorithm for Partial Discharge Separation To date, one of the main tools for evaluating the reliability of an insulation system is the continuous monitoring of those phenomena which, by interacting with the elements of the system, can induce aging processes or failures. For power grids, a signal that identifies possible aging or improper use of the component is Partial Discharge (PD) activity. Generally, the evaluation of the PD phenomenon is carried out through a two-step procedure: measurement and data analysis. To optimize the PD analysis process, increasingly sophisticated PD separation/classification algorithms are needed. Especially for the measurements carried out in HVDC systems for which the absence of a phase reference makes more difficult to identify the different types of discharge. The purpose of this article is to investigate the possibility of optimizing the input data to a hierarchical clustering algorithm in order to obtain a subdivision of the dataset more faithful to the real behavior of the phenomena. Specifically, the proposed approach is based on the use of the cross-correlation matrix to carry out the clustering operation. This matrix replaces the matrix of the distances among the points distributed in the map used for the representation of the data. Results show that with this modification it is possible to separate phenomena that present partially or completely overlapping patterns. Moreover, the algorithm turns out to be automatic and does not require the choice of references or thresholds to define the similarity among pulses. Separation (statistics) ; Cluster analysis ; Computer science ; Partial discharge ; Hierarchical clustering ; Algorithm ; Artificial intelligence ; Machine learning ; Engineering ; Voltage High voltage insulation and dielectric phenomena ; Advanced Algorithms and Applications ; Advanced Sensor and Control Systems
Authors: Wen‐Ping Peng | Zhong Ren | Junli Wu | Chengxin Xiong | Longjuan Liu | Bingheng Sun | Gaoqiang Liang | Mingbin Zhou
Source: Foods (article, 2023-05-15)
Field: Chemistry — Analytical Chemistry

Qualitative and Quantitative Assessments of Apple Quality Using Vis Spectroscopy Combined with Improved Particle-Swarm-Optimized Neural Networks Exploring a cost-effective and high-accuracy optical detection method is of great significance in promoting fruit quality evaluation and grading sales. Apples are one of the most widely economic fruits, and a qualitative and quantitative assessment of apple quality based on soluble solid content (SSC) was investigated via visible (Vis) spectroscopy in this study. Six pretreatment methods and principal component analysis (PCA) were utilized to enhance the collected spectra. The qualitative assessment of apple SSC was performed using a back-propagation neural network (BPNN) combined with second-order derivative (SD) and Savitzky-Golay (SG) smoothing. The SD-SG-PCA-BPNN model's classification accuracy was 87.88%. To improve accuracy and convergence speed, a dynamic learning rate nonlinear decay (DLRND) strategy was coupled with the model. After that, particle swarm optimization (PSO) was employed to optimize the model. The classification accuracy was 100% for testing apples via the SD-SG-PCA-PSO-BPNN model combined with a Gaussian DLRND strategy. Then, quantitative assessments of apple SSC values were performed. The correlation coefficient (<i>r</i>) and root-square-mean error for prediction (RMSEP) in testing apples were 0.998 and 0.112 °Brix, surpassing a commercial fructose meter. The results demonstrate that Vis spectroscopy combined with the proposed synthetic model has significant value in qualitative and quantitative assessments of apple quality. Principal component analysis ; Particle swarm optimization ; Artificial neural network ; Mathematics ; Correlation coefficient ; Artificial intelligence ; Biological system ; Pattern recognition (psychology) ; Smoothing ; Computer science ; Statistics ; Machine learning ; Algorithm ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Horticultural and Viticultural Research
Authors: Juan David Zorrilla Henao | Alejandro Segura | Alejandro Tenorio | Harold José Diaz | Alejandro Paz
Source: Data in Brief (article, 2023-12-20)
Field: Materials Science — Materials Chemistry

Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators This article presents the data collection process for the classification of partial discharges in electrical generators using PNG format images. The data were collected through field measurements on over 40 generators in various locations in Colombia, in addition to utilizing a partial discharge simulator provided by Omicron Energy. Throughout the collection process, special attention was given to the accuracy and coherence of the images, avoiding deformations and distortions that could impact the nature of partial discharges. Emphasis was placed on achieving high resolution in phase-resolved patterns (PRPD) to effectively correlate them with the adjacent physical phenomenon. The analysis focused on classifying the images according to the type of partial discharge, identifying them as internal, surface, or corona discharges. The obtained pulse patterns are represented in RGB color, which aids in assessing the repeatability of pulses across their distribution. These data hold potential for the development of pattern classification software for generator monitoring systems. They enable the training and validation of classification algorithms, simplifying the automated detection and analysis of partial discharges in electrical generators. Their applicability extends beyond the electrical industry and can be valuable in other fields requiring complex signal and pattern analysis. The article highlights the rigorous data collection process and precise analysis conducted to obtain a valuable set of PNG format images for partial discharge classification. These data have significant potential in advancing pattern classification software, driving progress in the monitoring and analysis of electrical generators. Partial discharge ; Computer science ; Data collection ; Software ; Process (computing) ; Field (mathematics) ; Artificial intelligence ; Generator (circuit theory) ; Pattern recognition (psychology) ; Data mining ; Electrical engineering ; Voltage ; Engineering ; Power (physics) ; Physics ; Mathematics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Islanding Detection in Power Systems
Authors: Sophie E. Lellman | C.K. Reynolds | A. K. Jones | Nick Taylor | Rainer Cramer
Source: Journal of Agricultural and Food Chemistry (article, 2023-09-07)
Field: Chemistry — Spectroscopy

LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis Detecting bovine tuberculosis (bTB) primarily relies on the tuberculin skin test, requiring two separate animal handling events with a period of incubation time (normally 3 days) between them. Here, we present the use of liquid atmospheric pressure (LAP)-MALDI for the identification of bTB infection, employing a three-class prediction model that was obtained by supervised linear discriminant analysis (LDA) and tested with bovine mastitis samples as disease-positive controls. Noninvasive collection of nasal swabs was used to collect samples, which were subsequently subjected to a short (<4 h) sample preparation method. Cross-validation of the three-class LDA model from the processed nasal swabs provided a sensitivity of 75.0% and specificity of 90.1%, with an overall classification accuracy of 85.7%. These values are comparable to those for the skin test, showing that LAP-MALDI MS has the potential to provide an alternative single-visit diagnostic platform that can detect bTB within the same day of sampling. Linear discriminant analysis ; Tuberculosis ; Chromatography ; Tuberculin ; Bovine tuberculosis ; Medicine ; Mycobacterium tuberculosis ; Mycobacterium bovis ; Pathology ; Chemistry ; Artificial intelligence ; Computer science Mass Spectrometry Techniques and Applications ; Biosensors and Analytical Detection ; Advanced Chemical Sensor Technologies
Authors: Alessandra Scaravilli | Mario Tranfa | Giuseppe Pontillo | Fabrizia Falco | Chiara Criscuolo | Marcello Moccia | Serena Monti | Roberta Lanzillo | Vincenzo Brescia Morra | Giuseppe Palma | Maria Petracca | Enrico Tedeschi | Andrea Elefante | Arturo Brunetti | Sirio Cocozza
Source: American Journal of Neuroradiology (article, 2023-03-02)
Field: Materials Science — Materials Chemistry

MR Imaging Signs of Gadolinium Retention Are Not Associated with Long-Term Motor and Cognitive Outcomes in Multiple Sclerosis Our findings suggest that gadolinium retention in the brains of patients with MS is not associated with long-term motor or cognitive outcomes. Medicine ; Multiple sclerosis ; Gadolinium ; Magnetic resonance imaging ; Cognition ; Term (time) ; Neuroscience ; Radiology ; Psychiatry Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis