jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lisda Rimayani Nasution | SEREN ERNEST FLAVIA | Yade Metri Permata | Muchlisyam Bachri | Hafid Syahputra | Chemayanti Surbakti
Source: International Journal of Applied Pharmaceutics (article, 2025-03-07)
Field: Chemistry — Analytical Chemistry

SIMULTANEOUS ANALYSIS OF ISONIAZID AND PYRIDOXINE HYDROCHLORIDE IN TABLETDOSAGE FORM USING PARTIAL LEAST SQUARES BASED ON INFRAREDSPECTRA PROFILE Objective: The purpose of this research was to simultaneously analyse a mixture of Isoniazid (INH) and Pyridoxine Hydrochloride (PDX) in tablet dosage form using Partial Least Square (PLS) based on infrared spectra profile. Methods: The calibration models were measured at five concentrations levels (w/w) of INH and PDX within the wavenumber ranges of 779.24-713.66 cm-1for INH and 829.39-763.81 cm-1for PDX. Model performance was evaluated through internal validation using leave-one-out-cross validation (LOO-CV), with accuracy and precision assessed by the coefficient of determination (R2), Prediction Error Sum of Squares (PRESS), and Root mean Square Error of Cross Validation (RMSECV). Divisor approach was applied to separate the spectrum of the individual components within the mixture. Results: The PLS models for INH and PDX levels showed excellent validation results, with R2 values of 0.9996 and 0.9969, PRESS values of 0.8106 and 0.3129, and RMSCEV values of 0.3675 and 0.2283, respectively. The INH level on INHA® 400 and Pehadoxin Forte® tablets were 102.90% and 105.45% of the labelled amount, while the PDX level was 98.93% and 101.57% of the labelled amount, respectively. Conclusion: The PLS model based on infrared spectra profiles demonstrated high accuracy, precision, and effectiveness, offering a non-destructive method for simultaneous analysis of INH and PDX in tablet dosage form. This method is applicable to pharmaceutical quality monitoring. Isoniazid ; Pyridoxine ; Pyridoxine Hydrochloride ; Partial least squares regression ; Hydrochloride ; Chemistry ; Chromatography ; Mathematics ; Medicine ; Statistics ; Organic chemistry ; Tuberculosis ; Biochemistry Spectroscopy and Chemometric Analyses ; Analytical Methods in Pharmaceuticals ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Long Chen | Jian Wei You | Qian Ma | Jian Lin Su | Shi Long Qin | Qiao Cong Peng | Qiang Xiao | Tie Jun Cui
Source: Nature Communications (article, 2025-12-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quantum-inspired superposition and nonseparable states of reconfigurable metasurfaces in classical systems Classical and quantum bits serve as cornerstone in information science. As this field rapidly evolves, the interplay between the two continues to enrich and inspire each other. Here, analog superposition states and analog nonseparable states are theoretically explored and experimentally demonstrated in a reconfigurable time-varying metasurface. To implement the quantum-inspired states in classical system, we have developed a reconfigurable metasurface capable of synthesizing analog superposition states across the temporal dimension and analog nonseparable states across spatial and polarization dimensions. Due to its unique features of analog superposition and nonseparability, the proposed metasurface holds great potentials to revolutionize the information processing capabilities beyond those offered by the classical information metasurface. This work not only offers a reconfigurable physical platform to advance classical and quantum information, but also will both enable unknown wave phenomena and provide promising perspectives in the fields of information science, quantum physics and material science. Superposition principle ; Quantum ; Dimension (graph theory) ; Quantum superposition ; Polarization (electrochemistry) ; Quantum information processing ; Field (mathematics) ; Quantum information Metamaterials and Metasurfaces Applications ; Molecular Communication and Nanonetworks ; Neural Networks and Reservoir Computing
Authors: Deni Kurnia | Hanif Fakhrurroja | Marno Marno | Joniko Joniko
Source: Jurnal POLIMESIN (article, 2025-12-31)
Field: Materials Science — Polymers and Plastics

A hybrid pareto–fishbone and IoT-based monitoring framework for reducing DTY yarn defects Quality Control (QC) challenges in the textile industry increasingly require data-driven and real-time solutions to reduce critical production defects. This research aims to develop a hybrid Pareto-Fishbone analysis integrated with an IoT-based monitoring framework to reduce the incidence of dominant defects in Draw Textured Yarn (DTY) yarns (X-stitch and Broken Filament). Defect data collected in 2024 (n=2,396) and early 2025 (n=1,177) were analyzed using Pareto charts, which identified X-stitch (40.15%) and Broken Filament (37.15%) as contributing 77.3% of total defects in 2024. Fishbone diagrams traced root causes to machine vibration and yarn tension anomalies. An IoT prototype was designed using ADXL345 vibration sensors (200 Hz sampling), tension monitoring, and MQTT communication to a Node-RED dashboard to enable real-time alerts. Preliminary testing achieved 95% MQTT transmission success and detected vibration anomalies correlating with 85% of X-stitch incidents. The proposed hybrid framework combines the diagnostic strength of Pareto–Fishbone analysis with the preventive capability of IoT monitoring, offering a scalable Industry 4.0-oriented solution for textile QC and predictive maintenance. Yarn ; MQTT ; Tension (geology) ; Textile industry ; Textile ; Vibration ; Transmission (telecommunications) ; Scalability Textile materials and evaluations ; Advanced Sensor and Energy Harvesting Materials ; Industrial Vision Systems and Defect Detection
Authors: N. S. Khalid | M. Thaqif B. N Ashimi | N. D. Nor Dalila | Nordiana Shariffudiin | Shazmin Aniza Abdul Shukor | H. Mansor | M.T.M. Talib | Shahdan Sudin | I Ibrahim | M. Z. Hasan | Siti Marhainis Othman
Source: Journal of Engineering Research and Education (JERE) (article, 2025-01-03)
Field: Chemistry — Analytical Chemistry

Hand-Held Shelf Life Decay Detector for Non-Destructive Fruits Quality Assessment Perishable food such as fruits have a limited shelf life and can quickly degrade if not properly stored. One method for detecting decay in these foods is the use of ethylene gas. Ethylene is a naturally occurring hormone that is released by fruits as they ripen. By measuring the levels of ethylene in the storage area, it is possible to detect when fruits and vegetables are starting to degrade. This information can then be used to act, such as removing spoiled produce and adjusting storage conditions, to extend the shelf life of the remaining products. By utilizing ethylene gas for early detection of decay, it is possible to improve food safety and reduce food waste. The project aims to utilized ethylene gas from perishable food such as fruits before decay. This project proposed portable or hand-held detection ethylene gas by including temperature and humidity. The sensor will be measuring the level of ethylene gas, temperature and humidity. Next, machine learning method; K-Nearest Neighbour(KNN) were used to evaluate the accuracy of the proposed system. This project, a hand-held decay detector for perishable food products is believed can help to prevent food waste by detecting early signs of spoilage in fruits. Shelf life ; Off the shelf ; Detector ; Quality (philosophy) ; Environmental science ; Biology ; Computer science ; Physics ; Optics ; Food science Analytical chemistry methods development ; Radiation Effects and Dosimetry ; Advanced Chemical Sensor Technologies
Authors: Nicolas Giovannini | Diego Mariano Sacchero | Christian Carlos Quispe Bonilla | M.D. Quispe | Edgar Carlos Quispe Peña
Source: South African Journal of Animal Science (article, 2025-05-24)
Field: Materials Science — Polymers and Plastics

Human counting versus artificial intelligence for assessing medullation in mohair fibres The fleeces of mammals with dense coats, such as the mohair fleeces of Angora goats, usually include medullated fibres. These fibres constitute a problem for the textile industry because of their structural characteristics. Three experiments were conducted in this study, with the aim of comparing human image analysis to digital image analysis and artificial intelligence (AI), in terms of their ability to determine the incidence of medullation in mohair samples. The experiments entailed determining the incidences of industry non-objectionable medullated (NOB) fibres and objectionable medullated (SME) fibres, as percentages of the non-medullated fibres. In each experiment, a set of samples was analysed by both laboratory personnel and by different AI models using a Smart Fiber Medullometer. Laboratory personnel showed better coincidence and higher correlations with the AI models when counting SME fibres (r = 0.64–0.97) than when counting NOB fibres (r = 0.57–0.87). This could be the result of the more clearly defined characteristics of SME fibres, in relation to NOB fibres. The results of this studyindicate a great advance in the automatic detection of SME and NOB fibres in mohair samples. However, further adjustments of the AI models are required for counting NOB fibres. Fiber ; Artificial intelligence ; Mathematics ; Computer science ; Pattern recognition (psychology) ; Materials science ; Composite material Textile materials and evaluations ; Forensic Entomology and Diptera Studies ; 3D Shape Modeling and Analysis
Authors: Arif Ramdhan Achmad | Muhammad Soleh | Sugeng Suprijadi
Source: Journal of Emerging Innovations in Engineering (article, 2025-10-29)
Field: Materials Science — Materials Chemistry

Analysis of gas pressure decline SF&lt;sub&gt;6&lt;/sub&gt; in 70kV circuit breaker bay transformer 3 at Babakan substation This study analyzes the decrease in SF₆ gas pressure in the 70 kV circuit breaker Transformer Bay 3 at Babakan Substation, which affects the reliability of the power system. SF₆ gas is used as an insulating medium due to its high dielectric strength but is susceptible to micro-leakage, which degrades equipment performance. This research employs a qualitative approach with a case study strategy based on primary data obtained from field observations, interviews, and testing documentation before and after the replacement of the T-phase pole. Gas pressure monitoring was conducted using a FLIR Gas 306 camera and digital measuring instruments, with thematic analysis employed to identify causes and evaluate repair effectiveness. The results showed that a fine leak at the lower T-phase pole was the main cause of gas pressure reduction. After pole replacement, the rate of pressure drop decreased from 0.00459 MPa/day to 0.00016 MPa/day, indicating a 35.3% increase in insulation effectiveness and a 64.6% reduction in leakage rate. Operational feasibility tests met the SPLN 52-1:1983 standard, confirming that the circuit breaker is suitable for operation. I while applying condition-based maintenance (CBM) and infrared detection proved efficient in identifying SF₆ leakage and supporting predictive maintenance practices at substations. Circuit breaker ; Leak ; Gas pressure ; Transformer ; Leakage (economics) ; Dissolved gas analysis ; Pressure measurement ; Sulfur hexafluoride ; Dielectric strength ; Short circuit High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Thermal Analysis in Power Transmission
Authors: Jiřı́ Barek
Source: Chemické listy (article, 2025-04-15)
Field: Chemistry — Physical and Theoretical Chemistry

First International Doctoral Conference on Advances in Chemistry at the University of Chemistry and Technology Prague The education of high-quality university graduates in chemistry is probably the most important prerequisite for further development of Czech and European chemistry. In spite of different opinions and approaches, most chemistry-oriented university teachers will agree with my presumption (admittedly somewhat conservative from the point of view of recent trends) that the best way how to teach our students anything is to let them to do it by themselves. An illustrious example of this possibility and its practical application is 1st International Doctoral Conference on Advances in Chemistry (IDCAC 2024) held in English at the University of Chemistry and Technology Prague (UCT Prague), which was perfectly organized by doctoral students of this University on November 9, 2024 (in excellent cooperation with young foreign students from other European countries). This article tries to characterize the best awarded presentations and the whole IDCAC 2024, its atmosphere and its contribution for the Czech and European chemistry communities. Full text English translation is available in the on-line version. Chemistry ; Engineering ; Engineering physics ; Engineering ethics ; Library science ; Computer science History and advancements in chemistry
Authors: Yizhe Chen | Feng Guo | Zhiyong Lan
Source:  (article, 2025-08-22)
Field: Chemistry — Analytical Chemistry

Online intelligent recognition of debris based on spectral imaging technology This study aims to use machine vision technology to design and implement an intelligent recognition and removal system for impurities in tobacco production, in order to improve the purity of tobacco and the quality of cigarettes. By collecting image data on the conveyor belt and combining it with deep learning algorithms, rapid recognition of tobacco debris is achieved, and real-time removal is carried out through automatic devices. In this study, we provided a detailed introduction to the overall design concept of the system, hardware device design, recognition methods, dataset construction, model validation, and research on exclusion methods. Firstly, we chose the YOLO v8 framework as the core of the software algorithm, which has excellent performance in debris recognition due to its efficient image analysis and processing capabilities. By conducting five fold cross validation on a dataset containing various impurities, we verified that the designed deep learning model achieved an accuracy of up to 98.2% in detecting impurities and had good real-time performance, which could meet the real-time requirements of the production line. Secondly, in terms of the research and application effectiveness of the removal method, we have designed corresponding removal methods for the identification results of tobacco debris, and achieved comprehensive removal of tobacco debris by converting digital signals into level signals to drive the removal device. The actual application effect shows that the system reduces the quality control time of wind sorting debris from 30 minutes to 5 minutes, significantly improving production efficiency and product quality. In summary, this study designed and implemented a tobacco debris recognition and removal system based on machine vision, which has made a positive contribution to improving tobacco production efficiency and product quality. Software ; Image processing ; Deep learning ; Sorting ; Automation ; Machine vision ; Image quality ; Debris Spectroscopy and Chemometric Analyses ; Fire Detection and Safety Systems ; Industrial Vision Systems and Defect Detection
Authors: Zhichao Cheng | Linhui Zhai | Li Yu | Kaifeng Chen | Wensi Zhao | Minjia Tan | Yan Fu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-05-28)
Field: Chemistry — Spectroscopy

Deconvolution of multiplexed peptidoform mass spectra enables high-resolution profiling of complex protein modification patterns Abstract Combinatorial patterns of post-translational modifications (PTMs), like the histone code, play critical roles in regulating protein functionality. However, in bottom-up proteomics, isobaric modification peptidoforms (IMPs) frequently co-elute and co-fragment during liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), resulting in multiplexed mass spectra that cannot be properly analyzed by conventional protein identification and quantification methods. Existing solutions are either limited to highly narrow scenarios or unavailable for public use. Here, we introduce PTMdecoder, a robust and versatile software tool for discriminating and quantifying IMPs by deconvoluting their multiplexed MS/MS spectra and ion chromatograms without requiring a spectral library of individual peptidoforms. Tested on 34 samples of synthesized IMPs, PTMdecoder achieved an overall sensitivity of 95.7% for IMP identification and root mean square errors mostly &lt;0.05 for quantification. In human histone samples, it detected and quantified 36.7–44.8% more IMPs than conventional methods, providing a higher-resolution view of histone modification patterns. Deconvolution ; Profiling (computer programming) ; Multiplexing ; Computer science ; High resolution ; Algorithm ; Biological system ; Analytical Chemistry (journal) ; Chemistry ; Chromatography ; Remote sensing ; Telecommunications ; Biology ; Geology Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Marie Lenski | Sébastien Anthérieu | Delphine Allorge
Source: Annales de Toxicologie Analytique (article, 2025-03-01)
Field: Chemistry — Spectroscopy

Développement et application d’une approche de métabolomique pour l’identification de biomarqueurs précoces de toxicité du tabac, de la cigarette électronique et du tabac chauffé Medicine Analytical Chemistry and Chromatography ; Microbial Metabolic Engineering and Bioproduction ; Computational Drug Discovery Methods
Authors: Lavanya Yegnaraman | Natesan Chidambaranathan | Adhityan Rajendran
Source: NMR in Biomedicine (article, 2025-10-22)
Field: Materials Science — Materials Chemistry

Preoperative Grading of WHO Grade 3 Gliomas and Comprehensive Glioma Assessment Using APTw MRI: Enhancing Diagnostic Thresholds and Noninvasive Tumor Characterization Accurate preoperative grading of gliomas is essential for prognostic stratification and surgical planning. However, conventional MRI often struggles to differentiate between WHO Grade 2 and Grade 3 gliomas. This study evaluated the diagnostic value of amide proton transfer-weighted (APTw) imaging, a noninvasive and contrast-free molecular MRI technique, in improving glioma grading. We retrospectively analyzed 57 treatment-naive glioma patients who underwent preoperative APTw imaging and compared APTw signal intensities with histopathological grades and molecular subtypes. Receiver operating characteristic analysis identified an APTw signal intensity threshold of 2.3% that optimally distinguished Grade 2 from Grade 3 gliomas, yielding 75% sensitivity, 80% specificity, and 77.8% accuracy. Applying this threshold corrected presurgical undergrading in five of seven initially misclassified Grade 3 tumors. Mean APTw values were significantly higher in IDH-wild-type gliomas than in IDH-mutant gliomas (AUC 0.94), supporting the role of APTw imaging in molecular stratification. However, within Grade 4 tumors, APTw did not differentiate between IDH-mutant and IDH-wild-type subtypes. In addition, APTw imaging revealed intratumoral heterogeneity not evident on conventional MRI sequences in 43% of cases, suggesting a potential role in guiding biopsy targeting. APTw signal differences also indicated variations in tumor extent that were not captured on conventional imaging. These findings suggest that incorporating APTw imaging into the preoperative workflow can improve glioma grading, reveal biological heterogeneity, and enhance molecular characterization, ultimately supporting more informed clinical decision-making. Wider use of standardized APTw acquisition protocols and multicenter validation of the proposed thresholds may support broader clinical adoption, positioning APTw as a valuable complement to conventional MRI in the individualized management of glioma patients. Glioma ; Grading (engineering) ; Magnetic resonance imaging ; Biopsy ; Stereotactic biopsy ; Brain tumor Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Medical Imaging Techniques and Applications
Authors: Reynaldo Manalo
Source: International Journal For Multidisciplinary Research (article, 2025-09-17)
Field: Chemistry — Inorganic Chemistry

Assessing the Production Practices, Challenges and Opportunities of the Coconut Sap Industry in Oriental Mindoro This study examined coconut sap farming in Oriental Mindoro, Philippines, using a convergent parallel mixed-methods approach to analyze production practices, productivity, challenges, and opportunities. Quantitative data were obtained from structured surveys of 58 farmers, complemented by qualitative insights from in-depth interviews and field observations. Findings revealed that coconut sap farming is a traditional and labor-intensive practice. Farmers predominantly use Tacunan Dwarf and native coconut varieties aged 5–9 years, maintain standard spacing, and refrain from chemical inputs. Average sap yields range from 2 to 3.5 liters per tree daily, with sugar content averaging 12.9° Brix and a sap collection efficiency of 32.22%. Labor productivity is measured at 5.44 liters per hour per laborer, with notable correlations between production factors and productivity metrics. Challenges include an aging workforce, limited access to technical training, poor infrastructure, and inadequate financial support. Environmental risks and outdated postharvest practices further complicate the situation. However, farmers are open to improvements, expressing interest in high-yield varieties, organic inputs, hygienic tools, value addition, and cooperative ventures. In conclusion, while coconut sap farming in Oriental Mindoro faces significant constraints, targeted, farmer-centered interventions in training, inputs, and market access could enhance sustainable growth and improve rural livelihoods. Productivity ; Production (economics) ; Agriculture ; Sugar ; Sustainability ; Postharvest Coconut Research and Applications