jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: R. Rajesh | P. V. Manivannan
Source: Engineered Science (article, 2024-01-01)
Field: Materials Science — Biomaterials

Automatic Traffic Sign, Animal Detection, and Recognition using YOLOv8n to avoid Human-Animal Road Conflicts This study presents a deep-learning-based solution to mitigate human-animal conflicts on the road, utilizing You Only Look Once (YOLOv8n) for automatic traffic signs, animal detection, and recognition (ATSADR).In addition, this study introduces a custom dataset that includes Indian traffic signs and animal images (i.e., monkey and deer) collected from the Indian Institute of Technology Madras (IITM) Campus.Furthermore, the collected dataset was used to train the YOLOv8n model (with and without pretrained weights).A detailed comparative analysis of performance metrics, such as recall, mean Average Precision (mAP), accuracy, precision, F1-Score, and computational efficiency, was performed to select the most suitable model for the specified task.Real-time testing was conducted to demonstrate the practical performance of the proposed model.These findings signify the efficacy of the trained YOLOv8n model in real-time scenarios, showing promising solutions for addressing human-animal road conflicts.The trained model achieved the mAP of 73.7% and an average accuracy of 99.3%.The present work holds great potential to help prevent road accidents involving animals (deer and monkeys), and if trained with different animal datasets, the YOLOv8n model will offer a proactive solution to mitigate human-animal conflicts, ultimately enhancing the overall safety of both drivers and wildlife. Dyeing ; Anthocyanin ; Metal ; Fading ; SILK ; Chemistry ; Botany ; Materials science ; Food science ; Biology ; Computer science ; Organic chemistry ; Telecommunications ; Composite material Silk-based biomaterials and applications ; Microbial Metabolism and Applications ; Dyeing and Modifying Textile Fibers
Authors: Johannes Brockelt | Felix Schmauder | Kim Brettschneider | Marina Creydt | Stephan Seifert | Markus Fischer
Source: Molecular Omics (article, 2024-11-22)
Field: Chemistry — Analytical Chemistry

Competing technologies: determining the geographical origin of strawberries ( <i>Fragaria</i> × <i>ananassa</i> ) using laboratory based near-infrared spectroscopy compared to a simple portable device The application and development of fast and simple screening methods for the authentication of foods has increased continuously in recent years. A widely used analytical technique is Fourier transform near-infrared spectroscopy (FT-NIR). Despite the simple application of FT-NIR analysis, the analyses are usually carried out on benchtop devices in the laboratory. However small, inexpensive and mobile NIR devices could be used on-site. Despite the simple use of FT-NIR analysis, the examinations are usually carried out on a stationary benchtop device in a laboratory. However, in order to be able to perform the application directly on site, the application of small, cost-effective and mobile NIR devices for food analysis is crucial. In this study, both, a benchtop NIR instrument and a handheld NIR device with a lower resolution and analyzed wavenumber range were applied for the differentiation of strawberries from different geographical origins. Distinguishing German and non-German strawberries using linear discriminant analysis (LDA) yielded an accuracy of 91.9% and 84.0% using the benchtop and the handheld devices, respectively. Relevant variables could be assigned to lipids, carbohydrates and proteins. Overall, our study demonstrated for the first time that analyzing the geographical origin of strawberries using NIR spectroscopy is also possible by means of a handheld device. Fragaria ; Simple (philosophy) ; Table (database) ; Computer science ; Biological system ; Analytical Chemistry (journal) ; Chemistry ; Chromatography ; Botany ; Biology ; Data mining Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Benjamin A. Neely | Yasset Pérez‐Riverol | Magnus Palmblad
Source:  (article, 2024-09-11)
Field: Chemistry — Spectroscopy

Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer The past decade has seen widespread advances in quality control (QC) materials and software tools focused specifically on mass spectrometry-based proteomics, yet the rate of adoption is inconsistent. Despite the fundamental importance of QC, it typically falls behind learning new techniques, instruments, or software. Considering how important QC is in a core setting where data is generated for non-mass spectrometry experts and confidence in delivered results is paramount, we have created this quick-start guide focusing on off-the-shelf QC materials and relatively easy-to-use QC software. We hope that by providing a background on the different levels of QC, different materials and their uses, describing QC design options, and highlighting some current QC software, implementing QC in a core setting will be easier than ever. There continues to be development in each of these areas (such as new materials and software), and the current generation of QC for mass spectrometry-based proteomics is more than capable of conveying confidence in results as well as minimizing laboratory downtime by guiding experimental, technical, and analytical troubleshooting from sample to results. Primer (cosmetics) ; Mass spectrometry ; Proteomics ; Quality (philosophy) ; Chemistry ; Chromatography ; Computer science ; Physics ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications
Authors: Maxim Avdeev
Source: Acta Crystallographica Section B Structural Science Crystal Engineering and Materials (article, 2024-09-17)
Field: Materials Science — Materials Chemistry

Search for missing symmetry in the Inorganic Crystal Structure Database (ICSD) An exhaustive search for missing symmetry was performed for 223 076 entries in the ICSD (2023-2 release). Approximately 0.65% of them can be described with higher symmetry than reported. Out of the identified noncentrosymmetric entries, ∼74% can be described by centrosymmetric space groups; this has implications for compatible physical properties. It is proposed that the information on the correct space group is included in the ICSD. Symmetry (geometry) ; Physics ; Space group ; Space (punctuation) ; Group (periodic table) ; Symmetry operation ; Database ; Computer science ; Crystallography ; Chemistry ; Geometry ; Mathematics ; Optics ; Quantum mechanics ; X-ray crystallography ; Diffraction X-ray Diffraction in Crystallography ; Inorganic Fluorides and Related Compounds ; Crystal Structures and Properties
Authors: Rheal A. Towner | Ranga Dissanayake | Marya Ahmed
Source: Journal of Pharmacology and Experimental Therapeutics (review, 2024-04-05)
Field: Materials Science — Biomaterials

Clinical Advances in Triple Negative Breast Cancer Treatment: Focus on Poly (L-lactide-coglycolide) Nanoparticles Triple-negative breast cancer ; Breast cancer ; Paclitaxel ; Clinical trial ; Medicine ; Drug ; Drug resistance ; Metastatic breast cancer ; PLGA ; Cancer ; Drug delivery ; Oncology ; Internal medicine ; Pharmacology ; Nanotechnology ; Nanoparticle ; Materials science ; Biology Nanoparticle-Based Drug Delivery ; Cancer Treatment and Pharmacology ; Cancer Research and Treatment
Authors: Zeynep Uruk | Alper Kiraz | Bağdagül Karaağaç
Source: Polymer Engineering and Science (article, 2024-08-24)
Field: Materials Science — Polymers and Plastics

Optimization of rubber mixture production using a validated technological sequence of methods Abstract In this study, a combination of Plackett–Burman and Box–Behnken designs is applied to discover the relationships between the components of rubber compounds and technical specifications. Optimization of rubber compound formulation is realized by support vector regression integrated genetic algorithm to minimize compound cost. Twelve components potentially affecting the technical specifications of rubber compound, which are natural rubber, carbon black, white filler, stearic acid, zinc oxide, antiozonant, antioxidant, process oil, curing retarder, curing agent, and accelerator, are screened through Plackett–Burman design to decide the significant variables. Afterwards, four significant parameters, including carbon black, process oil, curing agent, and accelerator are analyzed using Box–Behnken design to minimize the number of experiments while obtaining the correlation between formulation and specifications. Lastly, a support vector regression integrated genetic algorithm is implemented to predict optimum compound formulation at minimum cost. Highlights Optimization of rubber compound to reduce the mixture and curing cost. Combination of Plackett–Burman and Box–Behnken designs. Integration of support vector regression to genetic algorithm. Correlations between the amounts of components and technical specifications. Box–Behnken design ; Natural rubber ; Plackett–Burman design ; Curing (chemistry) ; Materials science ; Carbon black ; Synthetic rubber ; Stearic acid ; Genetic algorithm ; Response surface methodology ; Process engineering ; Computer science ; Composite material ; Engineering ; Machine learning Polymer Nanocomposites and Properties ; Lubricants and Their Additives ; Polymer composites and self-healing
Authors: Amudha Kumari Duraisamy | Neli Fonseca | Gerard J. Kleywegt | Ardan Patwardhan | Kyle L. Morris
Source: Bioinformatics Advances (article, 2024-12-26)
Field: Materials Science — Materials Chemistry

EMICSS: added-value annotations for EMDB entries EMICSS is implemented in Python and it is an open-source, distributed under the Apache license version 2.0, with core code available on GitHub (https://github.com/emdb-empiar/added_annotations). Value (mathematics) ; Computer science ; Machine learning Machine Learning in Materials Science ; Research Data Management Practices ; Electron and X-Ray Spectroscopy Techniques
Authors: Panagiota Polydoropoulou | Vasilis N. Burganos
Source: Molecules (article, 2024-10-19)
Field: Materials Science — Materials Chemistry

Heat Transfer in Carbon-Nanotube Dispersions: A Simulation Study of the Role of Nanotube Morphology and Connectivity Simulation of the behavior of carbon nanotubes (CNTs) can become a very challenging task considering their complicated shape and large aspect ratio. This study aims to elucidate the role of CNT shape, length, and connectivity during heat transfer in CNT dispersions through a three-dimensional (3D) simulator. Three characteristic shapes for the CNTs are considered, namely, straight, moderately curved, and strongly curved. The results reveal that the commonly used assumption of viewing CNTs as straight cylinders leads to significant overestimation of the overall medium conductivity. The CNT length has an important effect on the nanofluid conductivity for all types of CNT shapes considered here. In addition, use of CNTs with higher conductivity than a certain value appears to have no further beneficial effect, thus relaxing the need for extremely pure or single-wall CNTs. On the contrary, the conductivity remains a strong function of the CNT concentration and may be even increased upon organization of CNTs into loose clusters. The overall approach and concept can be extended to CNT composites in a straightforward manner. Carbon nanotube ; Nanofluid ; Materials science ; Nanotube ; Conductivity ; Heat transfer ; Nanotechnology ; Thermal conductivity ; Morphology (biology) ; Composite material ; Mechanics ; Nanoparticle ; Chemistry ; Physics Carbon Nanotubes in Composites ; Thermal properties of materials ; Nanopore and Nanochannel Transport Studies
Authors: Ron Westfall
Source: Communications of the ACM (article, 2024-08-26)
Field: Materials Science — Materials Chemistry

Non-Volatile Memory Technology Poised for Game-Changing Breakthrough Why novel nanocomposite-superlattices for low-energy, high-stability nanoscale phase-change memory is poised as an innovation touchstone for the memory segment and the entire industrial ecosystem. Phase-change memory ; Nanoscopic scale ; Computer science ; Materials science ; Nanotechnology Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing ; Chalcogenide Semiconductor Thin Films
Authors: Anil Kumar Tomar | Ayushi Thapliyal | Sandeep Mathur | Rajinder Parshad | Suhani | Savita Yadav
Source: Biochemistry Research International (article, 2024-01-01)
Field: Chemistry — Spectroscopy

Exploring Molecular Alterations in Breast Cancer Among Indian Women Using Label‐Free Quantitative Serum Proteomics The clinical data indicate that diverse parameters characterize breast cancer patients in India, including age at presentation, risk factors, outcomes, and behavior. Alarming incidence and mortality rates emphasize the crucial need for early screening measures to combat breast cancer-related deaths effectively. Quantitative proteomic approaches prove pivotal in predicting cancer prognosis, analyzing protein expression patterns tied to disease aggressiveness and metastatic potential, and facilitating conversant therapy selection. Thus, this study was envisioned with the goal of identifying protein markers associated with breast cancer in Indian women, which could potentially be developed as diagnostic tools and therapeutic targets in the future. Applying label-free proteomic quantitation method and statistical analysis, several differentially expressed proteins (DEPs) were identified in the serum of breast cancer patients compared to controls, including SBSN, ANG, PCOLCE, and WFDC3 (upregulated), and PFN1, FLNA, and DSG2 (downregulated). The expression of SBSN was also validated by western blotting. Statistical methods were employed to proteomic expression data, which highlighted the ability of DEPs to distinguish between breast cancer and control samples. Conclusively, this study recognizes prospective biomarkers for breast cancer among Indian women and highlights the requisite of in-depth functional studies to elucidate their precise roles in breast cancer development. We particularly emphasize on SBSN and PFN1, as these proteins were observed to be progressively overexpressed and under expressed, respectively, in breast cancer samples compared to control samples, ranging from early-stage to metastatic cases. Breast cancer ; Medicine ; Cancer ; Oncology ; Disease ; Proteomics ; Internal medicine ; Bioinformatics ; Biology ; Gene ; Genetics Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Mass Spectrometry Techniques and Applications
Authors: Huadian Zhang | A. M. Rajendran | Manoj K. Shukla | Sasan Nouranian | Ahmed Al‐Ostaz | Steven L. Larson | Shan Jiang
Source: Journal of Composites Science (article, 2024-04-23)
Field: Materials Science — Materials Chemistry

Simulation of the Dynamic Responses of Layered Polymer Composites under Plate Impact Using the DSGZ Model This paper presents a numerical study on the dynamic response and impact mitigation capabilities of layered ceramic–polymer–metal (CPM) composites under plate impact loading, focusing on the layer sequence effect. The layered structure, comprising a ceramic for hardness and thermal resistance, a polymer for energy absorption, and a metal for strength and ductility, is analyzed to evaluate its effectiveness in mitigating the impact loading. The simulations employed the VUMAT subroutine of DSGZ material models within Abaqus/Explicit to accurately represent the mechanical behavior of the polymeric materials in the composites. The VUMAT implementation incorporates the explicit time integration scheme and the implicit radial return mapping algorithm. A safe-version Newton–Raphson method is applied for numerically solving the differential equations of the J2 plastic flow theory. Analysis of the simulation results reveals that specific layer configurations significantly influence wave propagation, leading to variations in energy absorption and stress distribution within the material. Notably, certain layer sequences, such as P-C-M and C-P-M, exhibit enhanced impact mitigation with a superior ability to dissipate and redirect the impact energy. This phenomenon is tied to the interactions between the material properties of the ceramic, polymer, and metal, emphasizing the necessity of precise material characterization and enhanced understanding of the layer sequencing effect for optimizing composite designs for impact mitigation. The integration of empirical data with simulation methods provides a comprehensive framework for optimizing composite designs in high-impact scenarios. In the general fields of materials science and impact engineering, the current research offers some guidance for practical applications, underscoring the need for detailed simulations to capture the high-strain-rate dynamic responses of multilayered composites. Materials science ; Ceramic ; Composite material ; Ductility (Earth science) ; Izod impact strength test ; Material properties ; Composite number ; Structural engineering ; Computer science ; Engineering High-Velocity Impact and Material Behavior ; Fluid Dynamics Simulations and Interactions ; Structural Response to Dynamic Loads
Authors: Gozde Damla Turhan-Haskara | Anıl Dinç Demirbilek
Source: MATEC Web of Conferences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Large Language Model-aided Life Cycle Analysis for Circular Bio-manufacturing This paper explores the pivotal role of circular manufacturing methods and tools for biobased materials through an assessment tool built on a large language model (LLM) embedded mobile application. The LLMs, trained on extensive textual datasets, can provide precision and efficiency for the life cycle assessment (LCA) for biobased manufacturing. The tool automates data collection, categorises information from diverse sources, and supports ecological decision-making in material and manufacturing method selection. The research follows a methodology based on three main workflows, including database development, LCA specifications, and the LLM-embedded mobile interface development. Furthermore, the study recognizes the intricacy involved in utilising newly developed materials, especially considering the abundance of available formulations. It questions how the tool adapts to various material and manufacturing options and how it could augment practicality and applicability in real-life design and manufacturing stages. The study demonstrates that the tool offers a comprehensive and critical evaluation of biobased materials for manufacturing towards product development across design domains, unlocking new possibilities at the intersection of ecology, circular design, and digital tools. Circular economy ; Manufacturing engineering ; Engineering ; Computer science ; Biology ; Ecology Machine Learning in Materials Science ; Manufacturing Process and Optimization
Authors: Eyasu Ferede | Tamrat Tesfaye | Million Ayele | Desalegn Atalie | Bewuket Teshome Wagaye
Source: Textile & Leather Review (article, 2024-01-05)
Field: Materials Science — Polymers and Plastics

Prediction of the Impact of Ring Spinning Machine Front Roller Rubber Cot Shore Hardness on Spun Yarn Quality Parameters The yarn quality is mostly determined by the spinning settings, process control methods, and raw material. The most crucial and fundamental process in ring spinning is drafting, which has a significant impact on the quality of the yarn. Yarn quality is greatly impacted by drafting elements such as shore hardness. This study aimed to predict the effect of different degrees of shore hardness in the ring machine front roller rubber cot on 100% cotton and 32s Ne ring spun yarn quality parameters. The backline shore hardness was constant. Cotton yarn properties, including mass uniformity, imperfection level, unevenness, hairiness, tensile strength, and elongation, were measured and analyzed in accordance with ASTM D1425-96 and ASTM D2256, 2015 test standards, respectively. Linear regression equations were developed for prediction. A linear regression analysis showed that there is a positive correlation between shore hardness and yarn quality parameters with higher R2 values. Therefore, almost in all cases, the value of R2 was above 0.834, which signifies one can make a definite prediction about the yarn properties with different shore hardness. From the result of this study, it can be concluded that the quality of the produced yarn is superior to about 63-65° shore hardness values. Shore durometer ; Yarn ; Spinning ; Ultimate tensile strength ; Natural rubber ; Composite material ; Materials science ; Quality (philosophy) ; Shore ; Linear regression ; Hardness ; Mathematics ; Statistics ; Geology ; Physics Textile materials and evaluations
Authors: Haya F. Alhuthayli | Mohammed A. Mohammed | Nouf Abdulkareem Omer Alkharashi | Fahad Mohammed Al-Jasass | Abu ElGasim A. Yagoub | Magdi A. Osman
Source: Italian Journal of Food Science (article, 2024-08-13)
Field: Chemistry — Organic Chemistry

Impact of simulated &lt;i&gt;in vitro&lt;/i&gt; gastrointestinal digestion on phenolic compounds and the antioxident potential of olive pomace The study’s aim was to investigate the impact of laboratory-imitated digestion, including mouth, gastric, and intestinal phases of olive pomace on the stability, bioaccessibility, and recovery of phenolic compounds as well as antioxidant ability. The total flavonoid content (TFC) and total polyphenol content (TPC) were extracted using water or 50% and 100% methanol, ethanol, and acetone. The digested mixture after each phase of digestion was centrifuged and used to assess recovery, bioaccessibility, and polyphenolic stability. Compared to other solvents, 100% methanol and ethanol extracts showed the highest values of TPC, TFC, half-maximal inhibitory concentration (IC50) of 2,2-diphenyl-1-picrylhydrazyl (DPPH), and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) IC50. The recovery rates of TPC, TFC, DPPH IC50, and ABTS IC50 decreased in a descending order during the gastrointestinal phases as follows: mouth &gt; stomach &gt; intestines. After gastric (27.20%) and intestinal (26.79%) phases, the TPC bioaccessibility index in olive pomace increased significantly, which was statistically similar to the oral phase (21.20%). For TFC, the bioaccessibility rate did not change significantly after mouth and intestinal phases. There were no significant differences in flavonoids and antioxidant scavenging activities among the three phases of digestion. The pellet fractions had higher phenolic levels and better free radical scavenging activity in all phases of digestion than chyme-soluble fractions. TPC or TFC had a significant and positive relationship with Pearson correlation coefficient (r = 0.891–0.994) with DPPH and ABTS scavenging rates in oral, gastric, and intestinal digestion phases. Overall, our research could pave way for the industrial application of olive pomace waste as a possible food ingredient to generate functional foods with beneficial health effects. Pomace ; Food science ; Digestion (alchemy) ; Chemistry ; In vitro ; Phenols ; Chromatography ; Biochemistry Edible Oils Quality and Analysis