jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yang Cheng | Rui Gong | XianFeng Zhang | Tao Zhang | Zha Xi | Zhonghua Cao | Jiguang Zhang | Weilong Ding | Shibiao Xu
Source:  (article, 2024-11-21)
Field: Chemistry — Analytical Chemistry

Enhanced YOLO and RAFT for Real-Time Detection and Depth Estimation of Multiple Fruits in Orchard Environments In the modern fruit and vegetable industry, manual harvesting incurs significant costs.Harvesting robots can reduce labor costs and improve efficiency and economic benefits.However, challenges such as occlusion, uneven lighting, and adverse weather conditions complicate the rapid and accurate identification and localization of fruits and vegetables.To address these issues, we propose a solution that integrates an enhanced YOLO (You Only Look Once) network for real-time and accurate object detection with RAFT (Recurrent All-Pairs Field Transforms) for depth estimation.This combination significantly improves both the speed and accuracy of the detection and localization process.We conducted experiments on our own orchard dataset and public datasets, demonstrating good performance in terms of average precision, frame rate, and depth estimation error.The results show that our method is suitable for real-time orchard harvesting tasks and has practical value.Additionally, to enhance the model's generalizability, we extended our experiments to include a variety of other fruits and vegetables across multiple natural orchard environments, confirming robust performance under different conditions. Orchard ; Raft ; Computer science ; Estimation ; Engineering ; Materials science ; Ecology ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Industrial Vision Systems and Defect Detection
Authors: Dhanashri D Chavan | Rohit R. Bhosale | Vandana M Thorat | Amol Shete | Sarika J Patil | Devkumar D Tiwari
Source: Cureus (review, 2024-09-27)
Field: Materials Science — Biomaterials

Recent Advances in the Development and Utilization of Nanoparticles for the Management of Malignant Solid Tumors The purpose of nanotechnology-based drug delivery systems or novel drug delivery systems is to improve the effectiveness of therapy, and their promising properties have led to their increasing significance in the management of cancer. The researchers have primarily focused on designing novel nanocarriers, like nanoparticles (NPs), that can effectively deliver drugs to target cells and respond specifically to conditions particular to cancer. Whether passive or active targeting, these nanocarriers can deliver therapeutic cargoes to the tumor site to release the drug from the drug delivery systems. The purpose of this study is to provide recent scientific literature and key findings to researchers as well as the scientific community from the medical and pharmaceutical domains by reporting current advancements in the development of NPs for the treatment of different malignant solid tumors, such as colorectal, pancreatic, prostate, and cervical cancer. Medicine ; Nanoparticle ; Intensive care medicine ; Nanotechnology Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: Caio Lima Firme | Elvis S. Boes
Source: Research Square (preprint, 2024-09-24)
Field: Materials Science — Materials Chemistry

Local potential energy density-supramolecular energy (LPED-SME) machine learning prediction – a web application to obtain the local SME from simple inputs Simple (philosophy) ; Energy (signal processing) ; Computer science ; Artificial intelligence ; Mathematics ; Statistics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Chemical Physics Studies
Authors: Zhengdan LIN
Source: Institutional Repositories DataBase (IRDB) (article, 2024-09-01)
Field: Chemistry — Organic Chemistry

Tailoring Self-Assembling Structures of Block Copolymers via Side-Chain Post-Functionalization Using Thiol-Ene Reaction Copolymer ; Block (permutation group theory) ; Polymer ; Polymerization ; Monomer Advanced Polymer Synthesis and Characterization ; Block Copolymer Self-Assembly ; Synthesis and Properties of Aromatic Compounds
Authors: Lei Zhu | Hongda Zhang | Liang Dong | Zhengliang Lv | Xumin Ding
Source: Photonics (article, 2024-10-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamic Attention Mixer-Based Residual Network Assisted Design of Holographic Metasurface Multi-channel holographic metasurfaces have great potential for applications in wireless communications and radar. However, geometric phase-based multichannel metasurface units often have complex phase spectra, making the design of holographic metasurfaces complex and time-consuming. To address this challenge, we propose a dynamic attention mixer-based residual network to streamline the optimization and design of a multi-channel holographic metasurface unit. We conduct validation using multi-channel metasurface units, with a training set mean squared error (MSE) of 0.003 and a validation set MSE of 0.4. Additionally, we calculate the mean absolute error (MAE) for the geometric parameters θ1 and θ2 of the backward-predicted metasurface units in the validation set, which are 0.2° and 0.6°, respectively. Compared to traditional networks, our method achieves robust learning outcomes without the need for extensive datasets and provides accurate results even in complex electromagnetic responses. It is believed that the method presented in this paper is also applicable to the design of other artificial materials or multifunctional metasurfaces. Holography ; Residual ; Computer science ; Materials science ; Optoelectronics ; Optics ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: David S. Cerutti | Simon Boothroyd | Rafal Wiewiora | Woody Sherman
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-03-28)
Field: Chemistry — Spectroscopy

STORMM: Structure and TOpology Replica Molecular Mechanics for chemical simulations The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM is built to run thousands of independent molecular mechanical calculations on a single GPU with novel implementations that optimize numerical precision, mathematical operations, throughput, and resource management. The libraries are built around accessible classes with detailed documentation, supporting fine-grained parallelism and algorithm development as well as macroscopic manipulations of groups of systems on and off of the GPU. A primary intention of the STORMM libraries is to provide developers of atomic simulation methods with access to a high-performance molecular mechanics engine with extensive facilities to prototype and develop bespoke tools aimed toward drug discovery applications. In its present state, STORMM delivers molecular dynamics simulations of small molecules and small proteins in implicit solvent with tens to hundreds of times the throughput of conventional codes. The engineering paradigm also transforms two of the most memory bandwidth-intensive aspects of condensed-phase dynamics, particle-mesh mapping and valence interactions, into compute-bound problems for several times the scalability of existing programs. Numerical methods for getting the most out of each bit of information present in stored coordinates and lookup tables are also presented, delivering improved accuracy over methods implemented in other molecular dynamics engines. The open-source code is released under the MIT license. Replica ; Topology (electrical circuits) ; Molecular mechanics ; Statistical physics ; Physics ; Computer science ; Molecular dynamics ; Theoretical physics ; Mathematics ; Quantum mechanics ; Combinatorics ; Geography Advanced NMR Techniques and Applications ; Catalysis and Oxidation Reactions ; Machine Learning in Materials Science
Authors: Shuo Tao | Xuecheng Shao | Li Zhu
Source: arXiv (Cornell University) (preprint, 2024-01-25)
Field: Materials Science — Materials Chemistry

Accelerating Structural Optimization through Fingerprinting Space Integration on the Potential Energy Surface Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique in particular. In this study, we introduce a novel method that enhances the efficiency of local optimization by integrating an extra fingerprint space into the optimization process. Our approach utilizes a mixed energy concept in the hyper potential energy surface (PES), combining real energy and a newly introduced fingerprint energy derived from the symmetry of local atomic environment. This method strategically guides the optimization process toward high-symmetry, low-energy structures by leveraging the intrinsic symmetry of atomic configurations. The effectiveness of our approach was demonstrated through structural optimizations of silicon, silicon carbide, and Lennard-Jones cluster systems. Our results show that the fingerprint space biasing technique significantly enhances the performance and probability of discovering energetically favorable, high-symmetry structures, as compared to conventional optimizations. The proposed method is anticipated to streamline the search for new materials and facilitate the discovery of novel, energetically favorable configurations. Fingerprint (computing) ; Symmetry (geometry) ; Cluster (spacecraft) ; Computer science ; Energy (signal processing) ; Potential energy surface ; Space (punctuation) ; Process (computing) ; Component (thermodynamics) ; Global optimization ; Statistical physics ; Topology (electrical circuits) ; Algorithm ; Computational science ; Physics ; Artificial intelligence ; Mathematics ; Quantum mechanics ; Geometry ; Molecule Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; X-ray Diffraction in Crystallography
Authors: Joshua M. Lawrence | Emma Albertini | Alberto Scarampi | Paolo Bombelli | Lucia B. Giron | Lena Kuzmich | Christopher J. Howe
Source: Applied Phycology (article, 2024-12-10)
Field: Materials Science — Biomaterials

Algal biomusic generation Acknowledgements: The authors thank Peter Coppola, Ezra Kitson and Henry Lloyd-Laney for helpful discussions. Environmental science Diatoms and Algae Research ; Cephalopods and Marine Biology ; Biocrusts and Microbial Ecology
Authors: Meriem Taier | Hamza Allal | Salim Bousba | Fathi Bouhadiouche | Soumeya Maza | Maamar Damous | Ahlem Boussadia
Source: Research Square (preprint, 2024-01-05)
Field: Materials Science — Materials Chemistry

A computational investigation on the adsorption behavior of bromoacetone on B 36 borophene nanosheet Abstract Density functional theory (DFT) methods are employed to investigate the capability of B 36 borophene nanosheets as sensors for detecting the bromoacetone (BCT) molecule. An evaluation of the structural and electronic properties of both BCT and B 36 borophene is conducted. Subsequently, through computed metrics such as adsorption energy, charge density difference (CDD), and density of states (DOS), the interaction between B 36 and the BCT molecule is examined via dispersion-corrected density functional theory (DFT). Employing the reduced density gradient (RDG-NCI) approach for the analysis of non-covalent interactions, we further explored the nature of these interactions. The obtained results illustrate that B 36 borophene nanosheets serve as effective sensors for the BCT molecule, showcasing their ability to adsorb up to five BCT molecules through an exothermic process. BCT molecules chemiadsorb onto B 36 borophene by forming B‒O covalent bonds, engaging the oxygen atom of the carbonyl group in BCT with the edge boron atoms of B 36 borophene. Additionally, BCT molecules physio-adsorb on both the concave and convex sides of B 36 borophene, facilitated by van der Waals interactions. Ab-initio molecular dynamics (AIMD) simulations confirm the thermal stability of the BCT@B 36 concave and convex complexes at both 300 K and 400 K. Borophene ; Density functional theory ; Molecule ; van der Waals force ; Nanosheet ; Covalent bond ; Materials science ; Boron ; Chemical physics ; Adsorption ; Atom (system on chip) ; Computational chemistry ; Nanotechnology ; Crystallography ; Chemistry ; Physical chemistry ; Organic chemistry Boron and Carbon Nanomaterials Research ; Graphene research and applications ; Advancements in Battery Materials
Authors: Ruitao Lu | L. Qiu | Subo Dong | Qiyang Xue | Zhaohui Lu | Rui Zhai | Zhi Gang Wang | Chengquan Yang | Lingfei Xu
Source: Foods (article, 2024-11-24)
Field: Chemistry — Analytical Chemistry

Quantitative Classification and Prediction of Starkrimson Pear Maturity by Near-Infrared Spectroscopy Scientific evaluation of pear maturity is important for commercial reasons. Near-infrared spectroscopy is a non-destructive method that could be used for rapid assessment of pear maturity. The aim of this study was to develop a reasonable and effective method for the assessment of Starkrimson pear maturity using near-infrared technology. Partial least squares regression and five classification methods were used for analysis of the data. Among the indices used with the competitive adaptive reweighting-partial least squares regression method for quantitation, the visual ripeness index had the best modeling effect (Rp2: 0.87; root mean square error of prediction: 0.39). The classification model constructed with the visual ripeness index and post-ripeness score gave a cross-validation neural network model with the best classification effect and the highest accuracy (classification accuracy: 88.7%). The results showed that combination of quality indices with near-infrared spectroscopy was effective for rapidly evaluating the maturity of Starkrimson pears. PEAR ; Maturity (psychological) ; Biology ; Botany ; Psychology ; Developmental psychology Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Postharvest Quality and Shelf Life Management
Authors: А. В. Вахрушев | Aleksey Yu. Fedotov | Olesya Severyukhina | Anastasia Salomatina | Vladimir Boian | Anatolie Sidorenko
Source:  (preprint, 2024-03-28)
Field: Materials Science — Materials Chemistry

Numerical study of magnetic properties for Co-Fe-Nb nanofilms as promising materials for magnetoresistive memory The paper presents an overview of the magnetic resistive memory varieties, discusses their design features, weaknesses and benefits, and provides a comparative characteristic. A review of a combined mathematical model that jointly describes the change of spins and coordinates of atoms (spin-lattice dynamics) is given. In general, the model can use any form of interatomic force potential and describes various contributions to the magnetic Hamiltonian. In this work, a simplified form of the magnetic Hamiltonian, taking into account only the Zeeman and exchange interactions, was considered to investigate magnetic interactions. The described model is implemented in the SPIN software package in the freely distributed LAMMPS complex. In this work, computational experiments were performed using the MEAM potential. The computational experiments represent three separate series of calculations. In the first one, the formation and structuring processes in a multilayer cobalt-iron-niobium nanocomposite were considered. It was shown that during the deposition of niobium, a rough nanofilm is formed, with height differences of several angstroms. It was noted that between the nanofilms of iron and niobium, the formation of a more diffuse contact zone was observed, compared to the contact of the layers of cobalt and iron. In the second version of the numerical experiments, the mutual self-ordering of directions and reorientation of spins in crystalline iron were analyzed, both in the presence of an external magnetic field and in its absence. During the simulation, the formation of vortex flows (skyrmions) was revealed. It was shown that under the influence of an external magnetic field an induced magnetic moment occurs in crystalline iron. Its direction is opposite to the direction of the magnetic induction vector of the applied field. The third numerical experiment was focused on modeling the magnetic properties of the cobalt-iron bilayer film under the conditions of a uniform external magnetic field. The formation of skyrmions was more typical for the Fe layer. Clearly defined magnetic domain regions were obtained in the cobalt nanofilm. It was revealed that the total magnetization of the Co-Fe system is low due to the absence of a clearly defined priority direction of the magnetic moments. Magnetoresistance ; Materials science ; Condensed matter physics ; Engineering physics ; Optoelectronics ; Magnetic field ; Physics Shape Memory Alloy Transformations ; Magnetic properties of thin films ; Magnetic Properties and Applications
Authors: Roman Shendrik | Е. А. Раджабов | Alexandra Myasnikova | Viktorija Pankratova | Anatolijs Šarakovskis | A. I. Nepomnyashchikh | Alexander Bogdanov | Veronika Gavrilenko | Vladimir Pankratov
Source: arXiv (Cornell University) (preprint, 2024-12-05)
Field: Materials Science — Materials Chemistry

Ultrafast core-to-core luminescence in BaF$_2$-LaF$_3$ single crystals This study investigates the mechanisms underlying ultrafast cross-luminescence observed in BaF$_2$ crystals doped with LaF$_3$. We identified an ultrafast luminescent component with a decay time of approximately 150 ps, which emerges under excitation energies exceeding 24 eV as a novel radiative recombination process between electrons in the 5p core band of Ba2+ and holes in the 5p core band of La$^{3+}$. Ab initio calculations support this hypothesis, showing that the energy levels of the core bands facilitate such transitions. The findings indicate that BaF$_2$-LaF$_3$ scintillators hold significant promise for applications in time-of-flight tomography. Core (optical fiber) ; Luminescence ; Ultrashort pulse ; Materials science ; Optics ; Optoelectronics ; Physics ; Laser Luminescence Properties of Advanced Materials ; Inorganic Fluorides and Related Compounds ; Atmospheric Ozone and Climate
Authors: Yuto Miyahara | Takahiro Haga
Source: arXiv (Cornell University) (preprint, 2024-12-13)
Field: Chemistry — Analytical Chemistry

Unsupervised classification of disordered patterns in an oppositely charged colloidal system We develop an unsupervised machine learning approach to classify disordered phases in a system of oppositely charged colloids. In this system, the interplay between Coulomb and van der Waals interactions leads to transitions in local structures, while the global structure remains disordered. Our method involves representing the local structures of the system as high-dimensional vectors and applying principal component analysis to identify distinct features of each phase. We demonstrate that our method results in a reasonable classification of disordered phases, which is consistent with that obtained from radial distribution functions. The interpretability of the method reveals the key characteristics of each phase and provides valuable insights into the mechanisms underlying the unconventional phase transitions. Colloid ; Materials science ; Artificial intelligence ; Nanotechnology ; Computer science ; Chemistry ; Physical chemistry Spectroscopy and Chemometric Analyses ; Electrostatics and Colloid Interactions
Authors: Karin Huizer | Ivneet Banga | Ruchita Makesh Kumar | Sriram Muthukumar | Shalini Prasad
Source:  (preprint, 2024-05-31)
Field: Chemistry — Physical and Theoretical Chemistry

Nanobiosensing-Enabled Biorhythm Tracking for Psychiatric Disorders This review paper explores the transformative potential of nanobiosensing in biorhythm tracking for psychiatric disorders. Psychiatric diseases, characterized by a complex, heterogeneous and multifactorial pathophysiology, pose challenges in both diagnosis and treatment. Common denominators in the pathophysiology of psychiatric diseases include disruptions in the stress response, sleep-wake cycle, energy metabolism and the immune response: all of these are characterized by a strong biorhythmic regulation (e.g., circadian), leading to dynamic changes in the levels of biomarkers involved. Technological and practical limitations have hindered the analysis of such dynamic processes to date. The integration of nanobiosensors marks a paradigm shift in psychiatric research. These advanced technologies enable multiplex, non-invasive and continuous analysis of biorhythmic biomarkers in real time, overcoming the constraints of conventional approaches. Focusing on the regulation of the stress response, sleep/wake cycle, energy metabolism, and immune response, nanobiosensing allows for a deeper understanding of the heterogeneous and multifactorial pathophysiology of psychiatric diseases. Continuous monitoring of biomarkers can provide a foundation for personalized medicine in Psychiatry, and allow for the transition from syndromal diagnostic entities to pathophysiology-based psychiatric diagnoses. This evolution promises enhanced disease tracking, early relapse prediction, and tailored disease management and treatment strategies. As nanobiosensing continues to advance, its integration into biorhythm tracking holds promise not only to unravel the intricate etiology of psychiatric disorders but also for ushering in a new era of precision medicine, ultimately improving the outcomes and quality of life for individuals grappling with these challenging conditions. Tracking (education) ; Psychology ; Psychiatry ; Pedagogy thermodynamics and calorimetric analyses ; Neuroscience and Neural Engineering ; Computational Drug Discovery Methods
Authors: Mayank Nigam | Manvendra Verma
Source: Journal of Engineering Research and Application (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Concrete Performance with Hypo Paper Sludge and Hybrid Fibers In India, modern activities necessitate the excessive use of plastic bags. Because plastic is not biodegradable, it takes years to disintegrate. Poly-ethylene is the primary component of plastic bags. When polyethene is burned, it emits carbon dioxide as a byproduct, contributing to global warming. This study looks at how integrating hypo paper sludge (HPS) and hybrid fibres affects the performance of concrete. Hypo paper sludge, an industrial waste product, was assessed for its potential as a partial substitute for cement in order to improve sustainability and minimise environmental effect. In addition, hybrid fibres, which combine synthetic and natural fibres, were used to increase the mechanical qualities of concrete. A complete experimental programme was used in the study, which included compressive, tensile, flexural, and durability testing. Environmental science ; Business ; Materials science Natural Fiber Reinforced Composites