jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Vincent Jorgsson | Raghav Kumar | Mustaf Ahmed | Maxx Yung | Aryaman Pattnayak | Sri Pradhyumna Sridhar | V. Manikanta Varma | Arun Ram Ponnambalam | Georg A. Weidlich | Dimitris A. Pinotsis
Source: arXiv (Cornell University) (preprint, 2024-07-12)
Field: Materials Science — Materials Chemistry

AI-Driven Physics-Informed Bio-Silicon Intelligence System: Integrating Hybrid Systems, Biocomputing, Neural Networks, and Machine Learning, for Advanced Neurotechnology We present the Bio-Silicon Intelligence System (BSIS), an innovative hybrid platform that integrates biological neural networks with silicon-based computing. The BSIS, a Physics-Informed Hybrid Hierarchical Reinforcement Learning State Machine, employs carbon nanotube-coated electrodes to interface rat brains with computational systems, enabling high-fidelity neural interfacing and bidirectional communication through self-organizing systems in both biological and silicon forms. Our system leverages both analogue and digital AI theory, incorporating concepts from computational theory, chaos theory, dynamical systems theory, physics, and quantum mechanics. Additionally, the BSIS replicates the neuronal dynamics typical of intelligent brain tissue, employing nonlinear operations underlying learning and information storage. Neural signals are read through the FreeEEG32 board and BrainFlow software, then features are extracted and mapped to game actions by tracking feature changes in continuous data. Metadata is encoded into both analogue and digital brain stimulation signals at the microvolt level using our proprietary software and hardware. The system employs a dual signaling approach for training the rat brain, incorporating a reward solution and sound as well as human-inaudible distress sounds. This paper details the design, theory, functionality, and technical specifications of the BSIS, highlighting its interdisciplinary approach and advanced technological integration. Artificial neural network ; Artificial intelligence ; Silicon valley ; Computer science ; Engineering ; Nanotechnology ; Materials science Machine Learning in Materials Science ; Cell Image Analysis Techniques
Authors: Iva Majić | Marta Zajec | Maja Benković | Tamara Jurina | Ana Jurinjak Tušek | Davor Valinger | Jasenka Gajdoš Kljusurić
Source: Processes (article, 2024-08-21)
Field: Chemistry — Analytical Chemistry

Qualitative and Quantitative Potential of Low-Cost Near-Infrared (NIR) Devices for Rapid Analysis of Infant Formulas for Regular and Special Needs Infant formulas and their quality are an extremely important factor for proper growth and development and their composition and nutritional quality are extremely important. Fast, green, and cheap quality analysis methods are definitely desirable. Therefore, the aim of this work was to examine the potential of applying near-infrared (NIR) spectroscopy using two devices: a (i) laboratory NIR analyzer and (ii) portable NIR device. Both devices record the vibrations of molecules in the NIR region of 900–1699 nm. Infant formulas intended for children up to 6 months (n = 6) and for infants with a sensitive digestive system or confirmed allergy to cow’s milk proteins (n = 5) were tested. Each infant formula was recorded in the form of powder and in the form of prepared samples corresponding to different ages, according to the instructions on the product declaration. The parameters of color, conductivity, and total dissolved solids (TDS) were also measured. The measured parameters and the chemical composition of infant formulas were associated with NIR spectra and with the application of chemometric tools (principal component analysis (PCA) and partial least squares regression (PLSR)), the similarity and/or difference between the samples was determined and the qualitative/quantitative potential was determined through applications of both devices. Characteristic peaks at certain wavelengths indicate the presence of carbohydrates, proteins, and water were identified and are specific for regular and specific purpose infant formulas. It is precisely these specificities in the composition, which are visible in the NIR spectrum, that make it possible to distinguish samples on a qualitative level. The connection of NIR spectra as input variables and 22 parameters (color, TDS, conductivity, and energy–nutrient composition) as output variables, using PLSR, gave an insight into the quantitative potential, i.e., the possibility of predicting the observed parameters on the basis of NIR spectra (recorded using two devices). The quantitative potential was confirmed on the basis of model parameters that resulted in acceptable values for both NIR devices: the coefficient of determination for the calibration, Rc2 &gt; 0.9, and Range Error Ratio, RER &gt; 6. Near-infrared spectroscopy ; Qualitative analysis ; Computer science ; Qualitative research ; Optics ; Physics ; Sociology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; GABA and Rice Research
Authors: Swathi Balakrishnan | Remya Unnikrishnan | R. Yasodha | Suma Arun Dev
Source: Forestry An International Journal of Forest Research (article, 2024-06-08)
Field: Chemistry — Organic Chemistry

SSR marker-based individual identification system to trace illegal logging and geographic origin of teak (<i>Tectona grandis</i> L.f.) wood in India Abstract Illegal tree felling is one of the crucial problems in forestry worldwide. It is essential to develop adequate forensic techniques that can verify the origin of timber sourced at logging concessions. Teak wood—one of the most important timber species in India—is often illegally logged and also imported from other countries without certification. In our study, the best combination of Simple Sequence Repeat (SSR) markers identified was utilized for match testing the genetic profiles of seized and evidence woods. A genetic reference database was also developed to assign unknown wood samples to their source populations. Our results found a perfect match between the genetic profiles of seized wood and their respective evidence wood which ascertains the utility of genetic profiles as an efficient forensic tool. Further, efficiency of assignment tools based on different approaches such as distance-based, model-based and machine learning were tested. Mycorrhiza, a machine learning algorithm, was identified as the best assignment tool. However, only broad provenance-level assignment was possible due to the genetic admixture in a few natural teak populations. Mycorrhiza was then used to identify the origin of two plantations in India. The assignment test predicted that both the plantations had similar origin, having sourced seeds from multiple natural populations (through clonal seed orchards and seed production areas) and local populations in different ratio. The SSR markers and assignment tool from this study can be used as an effective forensic tool to curb illegal felling and to verify integrity of timber supply chains in India. Also, provenance-based assignment guarantees usage of these markers in a global scale. However, a collective global effort to develop and deposit a robust reference database in a common repository is a prerequisite to strengthen timber traceability worldwide. Tectona ; Felling ; Identification (biology) ; Reforestation ; Illegal logging ; Logging ; Coppicing ; Agroforestry ; Forestry ; Biology ; Geography ; Woody plant ; Botany Wood and Agarwood Research ; Forest Ecology and Biodiversity Studies ; Remote Sensing and LiDAR Applications
Authors: Yu‐Jen Chiu | D.J. Evans | Ahmad K. Omar
Source: arXiv (Cornell University) (preprint, 2024-09-11)
Field: Chemistry — Physical and Theoretical Chemistry

Theory of Nonequilibrium Multicomponent Coexistence Multicomponent phase separation is a routine occurrence in both living and synthetic systems. Thermodynamics provides a straightforward path to determine the phase boundaries that characterize these transitions for systems at equilibrium. The prevalence of phase separation in complex systems outside the confines of equilibrium motivates the need for a genuinely nonequilibrium theory of multicomponent phase coexistence. Here, we develop a mechanical theory for coexistence that casts coexistence criteria into the familiar form of equality of state functions. Our theory generalizes traditional equilibrium notions such as the species chemical potential and thermodynamic pressure to systems out of equilibrium. Crucially, while these notions may not be identifiable for all nonequilibrium systems, we numerically verify their existence for a variety of systems by introducing the phenomenological Multicomponent Active Model B+. Our work establishes an initial framework for understanding multicomponent coexistence that we hope can serve as the basis for a comprehensive theory for high-dimensional nonequilibrium phase transitions. Non-equilibrium thermodynamics ; Statistical physics ; Physics ; Economics ; Theoretical physics ; Thermodynamics History and advancements in chemistry
Authors: Junfang Fu | Rongyao Chen
Source: Sustainable Chemical Engineering (article, 2024-01-19)
Field: Materials Science — Materials Chemistry

Ratio Optimization of Magnesium Oxychloride Cement and Improvement of Its Water Resistance Based on Response Surface Methodology Magnesium oxychloride has excellent early strength, lightweight and environmentally friendly properties, and excellent application value. However, insufficient water resistance affects its engineering application. This paper uses fly ash to improve the water resistance of magnesium oxychloride cement (MOC). The response surface method was used to optimize the ratio of magnesium oxychloride cement. The influence of fly ash content, magnesium oxychloride cement ratio, and their interaction on the water resistance of magnesium oxychloride cement was studied using a response surface experiment. The fly ash content and magnesium oxychloride cement ratio were optimized to form magnesium oxychloride cement with good water-resistance. The experimental results show that the fitting efficiency of the response surface model is R2 = 0.9951; the model reflects the relationship between the factors of magnesium oxychloride cement and water resistance well. The magnesium oxychloride cement has a maximum softening coefficient of 0.898 when the amount of fly ash added is 21.94%, and the molar ratio of magnesium oxychloride cement is 11.49: 1:11.77. The magnesium oxychloride cement has good water resistance by optimizing the ratio based on external fly ash and response surface methodology. The study provides a reference for improving the water resistance of magnesium oxychloride cement. Magnesium ; Cement ; Fly ash ; Materials science ; Response surface methodology ; Magnesium phosphate ; Metallurgy ; Chemical engineering ; Composite material ; Chemistry ; Chromatography Magnesium Oxide Properties and Applications
Authors: Haruki Tajika | Kentaro Kutsukake | Noritaka Usami
Source: Journal of Crystal Growth (article, 2024-10-10)
Field: Materials Science — Materials Chemistry

Stress analysis and dislocation cluster generation in silicon crystal with artificial grain boundaries Dislocation ; Grain boundary ; Cluster (spacecraft) ; Materials science ; Silicon ; Stress (linguistics) ; Crystallography ; Composite material ; Metallurgy ; Chemistry ; Computer science ; Microstructure Microstructure and mechanical properties ; Silicon and Solar Cell Technologies ; Aluminum Alloy Microstructure Properties
Authors: Dao Manh Lan | Phạm Văn Đông | Mohamed A. Eltaher | Nguyen Trong Hai
Source: Heliyon (article, 2024-11-01)
Field: Materials Science — Materials Chemistry

Dynamic of composite nanobeams resting on an elastic substrate with variable stiffness This study introduces a novel approach by combining finite simulation and an enhanced shear deformation theory to analyze the dynamic behavior of multi-layer composite nanobeams supported by an elastic foundation. The calculation formulae are derived from nonlocal theory in order to account for the impact of size effect. An intriguing aspect of this research is the presence of intricate curved profiles in the two material layers of the beam. The elastic foundation exhibits varying stiffness throughout the beam's length, accounting for many imperfections in the beam and including the drag parameter of the material. These elements contribute to the steady evolution of the issue model towards more realistic structures. Nevertheless, the computation gets intricate and impedes the precise approach. However, our work has successfully resolved this difficult and significant difficulty using the two-node element. This research demonstrates the temporal evolution of the dynamic reactions of the point with the greatest displacement and velocity, as dictated by the law of change. Simultaneously, it also presents visual representations of every point on the beam as it undergoes temporal variations. These conclusions possess both scientific and practical value, establishing a foundation for real-world implementations. Stiffness ; Computation ; Beam (structure) ; Composite number ; Drag ; Displacement (psychology) ; Foundation (evidence) ; Node (physics) ; Deformation (meteorology) ; Work (physics) ; Mechanics ; Timoshenko beam theory ; Point (geometry) ; Variable (mathematics) ; Structural engineering ; Computer science ; Mathematics ; Physics ; Materials science ; Mathematical analysis ; Geometry ; Mechanical engineering ; Engineering ; Law ; Composite material Nonlocal and gradient elasticity in micro/nano structures ; Mechanical and Optical Resonators ; Force Microscopy Techniques and Applications
Authors: Zheng Ser | Radoslaw M. Sobota
Source: PROTEOMICS (article, 2024-11-07)
Field: Chemistry — Spectroscopy

Proteome integral solubility alteration via label‐free DIA approach (PISA‐DIA), game changer in drug target deconvolution Drug protein-target identification in past decades required screening compound libraries against known proteins to determine drugs binding to specific protein. Protein targets used in drug-target screening were selected predominantly used laborious genetic manipulation assays. In 2013, a team led by Pär Nordlund from Karolinska Institutet (Stockholm, Sweden) developed Cellular Thermal Shift Assay (CETSA), a method which, for the first time, enabled the possibility of drug protein-target identification in the complex cellular proteome. High throughput, quantitative mass spectrometry (MS) proteomics appeared as a compatible analytical method of choice to complement CETSA, aka Thermal Protein Profiling assay (TPP). Since the seminal CETSA-MS/ TPP-MS publications, different protein-target deconvolution strategies emerged including Proteome Integral Solubility Alteration (PISA). The work of Emery-Corbin et al. (Proteomics 2024, 2300644), titled Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA), introduces Data-Independent Acquisition (DIA) as a quantification method, opening new avenues in drug target-deconvolution field. Application of DIA for target deconvolution offers attractive alternative to widely used data dependent methodology. Proteome ; Deconvolution ; Solubility ; Drug ; Chemistry ; Proteomics ; Drug development ; Computer science ; Computational biology ; Chromatography ; Biochemistry ; Biology ; Pharmacology ; Algorithm ; Organic chemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Computational Drug Discovery Methods
Authors: Zitong Yang | Neil Band | Shuangning Li | Emmanuel Candès | Tatsunori Hashimoto
Source: arXiv (Cornell University) (preprint, 2024-09-11)
Field: Chemistry — Organic Chemistry

Synthetic continued pretraining Pretraining on large-scale, unstructured internet text enables language models to acquire a significant amount of world knowledge. However, this knowledge acquisition is data-inefficient--to learn a given fact, models must be trained on hundreds to thousands of diverse representations of it. This poses a challenge when adapting a pretrained model to a small corpus of domain-specific documents, where each fact may appear rarely or only once. We propose to bridge this gap with synthetic continued pretraining: using the small domain-specific corpus to synthesize a large corpus more amenable to learning, and then performing continued pretraining on the synthesized corpus. We instantiate this proposal with EntiGraph, a synthetic data augmentation algorithm that extracts salient entities from the source documents and then generates diverse text by drawing connections between the sampled entities. Synthetic continued pretraining with EntiGraph enables a language model to answer questions and follow generic instructions related to the source documents without access to them. If, instead, the source documents are available at inference time, we show that the knowledge acquired through our approach compounds with retrieval-augmented generation. To better understand these results, we build a simple mathematical model of EntiGraph, and show how synthetic data augmentation can "rearrange" knowledge to enable more data-efficient learning. Psychology ; Business Organometallic Complex Synthesis and Catalysis ; Model-Driven Software Engineering Techniques
Authors: Chuan Liu | Yi Tang | Jian Wang
Source: Symmetry (article, 2024-12-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High-Efficiency and Ultrawideband Polarization Conversion Metasurface Based on Topology and Shape Optimizaiton Design Method This study introduces a two-stage optimization method for designing an ultrawideband polarization conversion metasurface. By integrating topology and shape optimization techniques, the proposed method expands the design space to achieve enhanced polarization conversion bandwidth. The first stage employs genetic-algorithm-based topology optimization to establish the initial structural configuration through binary coding. Subsequently, the second stage refines the design through shape optimization by extracting and modifying the boundaries of the topology-optimized structure. The optimized design demonstrates high polarization conversion efficiency (&gt;90%) across 4.08–14.39 GHz, yielding a relative bandwidth of 111.64%, which represents a 4.88% improvement compared to topology-only optimization. This enhancement demonstrates the effectiveness of our combined optimization method in ultrawideband polarization conversion metasurface design, offering a promising method for developing high-performance electromagnetic devices. Topology optimization ; Topology (electrical circuits) ; Polarization (electrochemistry) ; Computer science ; Bandwidth (computing) ; Binary number ; Electronic engineering ; Physics ; Engineering ; Mathematics ; Telecommunications ; Electrical engineering ; Finite element method Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Canyi Lu | Encheng Liu | Yingzhan Li | Guocheng Zhu | Yiqin Shao
Source: Materials (article, 2024-09-04)
Field: Materials Science — Polymers and Plastics

Design and Coupled Moisture–Thermal Transfer Simulation of Opposite Cross-Section Polyethylene Terephthalate Knitted Fabric with Hygroscopic Quick-Drying Capability In addition to sportswear and outdoor equipment, moisture-absorbent quick-drying fabrics are also widely used in everyday clothing and home textiles. In this study, three types of weft-knitted fabrics were designed using Coolmax fiber and polypropylene fiber. The Coolmax/PP fabric exhibits good stretchability with a strain of 180.5% and achieves a high cumulative individual transfer capability of 691.6%, with a water absorption rate of 50.2%/s. The moisture conductivity gradient presented good moisture and heat conductivity in a simulated human body temperature environment using an infrared camera. Furthermore, mathematical modeling was constructed and visual simulation analysis was conducted to explore moisture-thermal transfer behavior. The simulation results closely align with experimental data, providing insights into designing flexible and wearable quick-drying fabrics for thermal management. Materials science ; Composite material ; Moisture ; Polypropylene ; Polyethylene terephthalate ; Fiber ; Thermal conductivity ; Polyethylene ; Heat transfer ; Thermal ; Thermal transfer ; Shrinkage ; Mechanics ; Layer (electronics) Textile materials and evaluations ; Thermoregulation and physiological responses ; Heat Transfer and Optimization
Authors: Zhiyi Hu | Feng-Jian Jiang | Jingyan He | Yulin Dai | Ya Wang | Nanyang Xu | Jiangfeng Du
Source: Nano Letters (article, 2024-02-23)
Field: Materials Science — Materials Chemistry

Four-Order Power Reduction in Nanoscale Electron–Nuclear Double Resonance with a Nitrogen-Vacancy Center in Diamonds Detecting nuclear spins using single nitrogen-vacancy (NV) centers is of particular importance in nanoscale science and engineering but often suffers from the heating effect of microwave fields for spin manipulation, especially under high magnetic fields. Here, we realize an energy-efficient nanoscale nuclear-spin detection using a phase-modulation electron-nuclear double resonance scheme. The microwave field can be reduced to 1/250 of the previous requirements, and the corresponding power is over four orders lower. Meanwhile, the microwave-induced broadening to the line-width of the spectroscopy is significantly canceled, and we achieve a nuclear-spin spectrum with a resolution down to 2.1 kHz under a magnetic field at 1840 Gs. The spectral resolution can be further improved by upgrading the experimental control precision. This scheme can also be used in sensing microwave fields and can be extended to a wide range of applications in the future. Vacancy defect ; Nitrogen ; Nanoscopic scale ; Electron ; Atomic physics ; Resonance (particle physics) ; Center (category theory) ; Materials science ; Reduction (mathematics) ; Nitrogen-vacancy center ; Stopping power ; Order (exchange) ; Power (physics) ; Condensed matter physics ; Physics ; Nuclear physics ; Chemistry ; Nanotechnology ; Crystallography ; Quantum mechanics Diamond and Carbon-based Materials Research ; Magnetism in coordination complexes ; Advanced Electron Microscopy Techniques and Applications
Authors: Aditi Rawal | Peter Mason | Stoyan Stoyanov | C. Bailey | Jurgen Huber
Source: Journal of the Institute of Conservation (article, 2024-05-03)
Field: Materials Science — Biomaterials

A prognostic and health management approach using colour fade to determine the condition of silk in a museum display environment A prognostic and health management approach using colour fade to determine the condition of silk in a museum display environment SILK ; Fade ; Visual arts ; Art ; Architectural engineering ; Computer graphics (images) ; Computer science ; Engineering ; Telecommunications Silk-based biomaterials and applications ; Date Palm Research Studies ; Silkworms and Sericulture Research