jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: กันตพงศ์ สุจริตพงษ์พันธ์ | รุ่งโรจน์ จินตเมธาสวัสดิ์ | มติ ห่อประทุม | ระพีพันธ์ แก้วอ่อน
Source: วารสารงานวิจัยและพัฒนาเชิงประยุกต์ โดยสมาคม ECTI (article, 2024-08-29)
Field: Chemistry — Analytical Chemistry

การวเคราะหเชงปรมาณสารประกอบหลกในกาแฟดวยเทคนครามาน สเปกโทรสโกปรวมกบการวเคราะหขอมลโดยใชการเรยนรของเครอง บทความนี้นำเสนอวิธีการวิเคราะห์สารคาเฟอีน (Caffeine) ซึ่งเป็นสารประกอบหลักในกาแฟ โดยจะทำการวิเคราะห์เชิงปริมาณของสารเคมีมาตรฐานด้วยเทคนิครามานสเปกโทรสโกปี (Raman Spectroscopy) ร่วมกับการวิเคราะห์ข้อมูลโดยใช้การเรียนรู้ของเครื่อง (Machine Learning) ในการทดลองนี้ได้ทำการเตรียมตัวอย่างคาเฟอีนมาตรฐานที่ความเข้มข้น 500 ppm 1000 ppm 1500 ppm 2000 ppm 3000 ppm และ 4000 ppm หลังจากนั้นจึงนำตัวอย่างมาวัดด้วยเทคนิครามานสเปกโทรสโกปี เพื่อได้ชุดข้อมูลสเปกตรัมรามาน อย่างไรก็ตาม ชุดข้อมูลสเปกตรัมรามานยังมีคุณภาพไม่เพียงพอ จึงจำเป็นต้องเพิ่มคุณภาพให้แก่ชุดข้อมูลรามานโดยการใช้เทคนิคการประมวลผลเบื้องต้น (Pre-Processing) ด้วยวิธีการปรับเส้นฐาน (Baseline Removal), การลบปรากฏการณ์รังสีคอสมิก (Cosmic ray Removal), การลดสัญญาณรบกวน (Smoothing Signal), การลบข้อมูลสเปกตรัมที่มีค่าผิดปกติ (Outlier Removal), และการปรับสัญญาณให้มีค่าอยู่ในช่วงที่เป็นมาตรฐาน (Amplitude Normalization) หลังจากนั้นจึงทำการแบ่งชุดข้อมูลออกเป็น 2 ส่วน ด้วยอัตราส่วน 80:20 ข้อมูลชุดแรกที่มีจำนวน 80% ของจำนวนข้อมูลทั้งหมด (Training Dataset) จะถูกนำมาใช้เพื่อฝึกสอนแบบจำลอง (Model Training) และข้อมูลที่เหลือที่มีจำนวน 20% ของจำนวนข้อมูลทั้งหมด (Validation Dataset) จะถูกใช้ในการทดสอบและปรับพารามิเตอร์ให้แบบจำลองเพื่อเพิ่มประสิทธิภาพในการทำนายปริมาณของสารคาเฟอีน งานวิจัยนี้ได้ทำการเปรียบเทียบประสิทธิภาพของแบบจำลองทั้งหมด 18 แบบจำลอง ซึ่งใช้ ค่าความผิดพลาดเฉลี่ยสมบูรณ์ (Mean Absolute Error: MAE) ค่ารากที่สองเฉลี่ยสมบูรณ์ (Root Mean Square Error: RMSE) และค่าสัมประสิทธิ์การตัดสินใจพหุคุณ (Coefficient of Multiple Determination: R-Square) เป็นตัวชี้วัดในการประเมินประสิทธิภาพของแบบจำลอง โดยแบบจำลองที่มีประสิทธิภาพสูงสุดผ่านตัวชี้วัดนี้คือ Extra Trees Regressor ซึ่งมีค่าความผิดพลาดเฉลี่ยสมบูรณ์ ค่ารากที่สองเฉลี่ยสมบูรณ์ และค่าสัมประสิทธิ์การตัดใจพหุคูณ เป็น 710 ppm 914.05 ppm และ 0.34 ตามลำดับ วิธีการที่ได้จากงานนี้ สามารถนำไปต่อยอดเพื่อใช้ในการหาปริมาณสารคาเฟอีนในกาแฟได้ Mean squared error ; Normalization (sociology) ; Outlier ; Root mean square ; Smoothing ; Raman spectroscopy ; Analytical Chemistry (journal) ; Statistics ; Mathematics ; Pattern recognition (psychology) ; Chemistry ; Artificial intelligence ; Computer science ; Chromatography ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Blockchain Technology in Education and Learning
Authors: Raymond J. Hinton | Jihyun Byun | Dixon Vimalajeewa | Brani Vidaković
Source: arXiv (Cornell University) (preprint, 2024-01-29)
Field: Chemistry — Analytical Chemistry

Ovarian Cancer Diagnostics using Wavelet Packet Scaling Descriptors Detecting early-stage ovarian cancer accurately and efficiently is crucial for timely treatment. Various methods for early diagnosis have been explored, including a focus on features derived from protein mass spectra, but these tend to overlook the complex interplay across protein expression levels. We propose an innovative method to automate the search for diagnostic features in these spectra by analyzing their inherent scaling characteristics. We compare two techniques for estimating the self-similarity in a signal using the scaling behavior of its wavelet packet decomposition. The methods are applied to the mass spectra using a rolling window approach, yielding a collection of self-similarity indexes that capture protein interactions, potentially indicative of ovarian cancer. Then, the most discriminatory scaling descriptors from this collection are selected for use in classification algorithms. To assess their effectiveness for early diagnosis of ovarian cancer, the techniques are applied to two datasets from the American National Cancer Institute. Comparative evaluation against an existing wavelet-based method shows that one wavelet packet-based technique led to improved diagnostic performance for one of the analyzed datasets (95.67% vs. 96.78% test accuracy, respectively). This highlights the potential of wavelet packet-based methods to capture novel diagnostic information related to ovarian cancer. This innovative approach offers promise for better early detection and improved patient outcomes in ovarian cancer. Wavelet ; Scaling ; Computer science ; Ovarian cancer ; Cancer ; Artificial intelligence ; Pattern recognition (psychology) ; Internal medicine ; Medicine ; Mathematics ; Geometry Spectroscopy and Chemometric Analyses
Authors: Abelardo Abad-Giron | Lucero Asmad-Cruz | Angella M. Cordova-Muñoz | César D. Gamarra-Sánchez | Carmen R. Silva-Correa | Víctor E. Villarreal-La Torre
Source: Journal of Applied Pharmaceutical Science (article, 2024-01-01)
Field: Chemistry — Organic Chemistry

In silico design of sitagliptin bioisosteres as new inhibitors of Mpro SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that caused the last major pandemic and has led to multiple efforts being carried out around the world to investigate molecules such as specific chemotherapy drugs against this virus, such as the drug Sitagliptin, which inhibits Mpro, a protease of the virus, by acting on a highly conservative substrate recognition pocket in different coronaviruses. The study aims to develop new compounds under bioisosteric replacement techniques and obtain new SARS-Cov-2 Mpro inhibitors that are more effective than Sitagliptin. For this, 50 bioisosteric derivatives of Sitagliptin were designed, and the pharmacodynamic, pharmacokinetic, and physicochemical properties were analyzed. First, the physicochemical properties of oral absorption were analyzed according to the principles of Lipinski and Veber. The molecular docking was carried out between the protease Mpro (Protein Data Bank Code 7BB2) and the 26 bioisosteres that had the best oral absorption, with the bioisosteres modified in 2,4,5-trifluorophenyl being those that presented a lower affinity energy than that of Sitagliptin. In addition, molecules with pyrrole-pyrazole or similar groups have better pharmacokinetic properties. It is concluded that the pyrrole-pyrazole carboxamide derivative molecule has better energy affinity and ligand efficiency than the other bioisosteres; additionally, it has adequate pharmacokinetic properties, so it would be the best candidate to continue in in vitro or in vivo studies. Sitagliptin ; In silico ; Coronavirus disease 2019 (COVID-19) ; Pharmacology ; Medicine ; Chemistry ; Internal medicine ; Biochemistry ; Infectious disease (medical specialty) Synthesis and biological activity ; Computational Drug Discovery Methods ; Diverse Scientific Research Studies
Authors: Alexander C. Tyner | Alexander V. Balatsky
Source: arXiv (Cornell University) (preprint, 2024-05-13)
Field: Chemistry — Inorganic Chemistry

Screening the organic materials database for superconducting metal-organic frameworks The increasing financial and environmental cost of many inorganic materials has motivated study into organic and "green" alternatives. However, most organic compounds contain a large number of atoms in the primitive unit cell, posing a significant barrier to high-throughput screening for functional properties. In this work, we attempt to overcome this challenge and identify superconducting candidates among the metal-organic-frameworks in the organic materials database using a recently proposed proxy for the electron-phonon coupling. We then isolate the most promising candidate for in-depth analysis, C$_{9}$H$_{8}$Mn$_{2}$O$_{11}$, providing evidence for superconductivity below $100$mK. Metal-organic framework ; Superconductivity ; Materials science ; Database ; Environmental chemistry ; Computer science ; Chemistry ; Organic chemistry ; Condensed matter physics ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Geoffrey Beausoleil
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2024-09-19)
Field: Materials Science — Materials Chemistry

Standardized Irradiation Testing and Multi-Modal Characterization for Advanced Nuclear Materials Summary of activities from NMDQi/AMMT to be presented to the annual AMMT program integration meeting Characterization (materials science) ; Modal ; Nuclear material ; Nuclear engineering ; Materials science ; Reliability engineering ; Composite material ; Engineering ; Chemistry ; Nuclear chemistry ; Nanotechnology Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Graphite, nuclear technology, radiation studies
Authors: Enrico Santangelo | Angelo Del Giudice | Simone Figorilli | Simona Violino | Corrado Costa | Marco Bascietto | Simone Bergonzoli | Claudio Beni
Source: Agriculture (article, 2024-01-16)
Field: Chemistry — Analytical Chemistry

Autonecrotic Tomato (Solanum lycopersicum L.) Line as a Potential Model for Applications in Proximal Sensing of Biotic and Abiotic Stress The autonecrotic tomato line V20368 (working code IGSV) spontaneously develops necrotic lesions with acropetal progression in response to an increase in temperature and light irradiation. The process is associated with the interaction between tomato and Cladosporium fulvum, the fungal agent of leaf mold. The contemporary presence of an in-house allele encoding the Rcr3lyc protein and the resistance gene Cf-2pim (from Solanum pimpinellifolium) causes auto-necrosis on the leaves even in the absence of the pathogen (hybrid necrosis). The aim of the work was (i) to examine the potential value of the necrotic genotype as a model system for setting up theoretical guidance for monitoring the phytosanitary status of tomato plants and (ii) to develop a predictive model for the early detection of pathogens (or other stresses) in the tomato or other species. Eighteen IGSV tomato individuals at the 4–5th true-leaf stage were grown in three rows (six plants per row) considered to be replicates. The healthy control was the F1 hybrid Elisir (Olter). A second mutant line (SA410) deriving from a cross between the necrotic mutant and a mutant line of the lutescent (l) gene was used during foliar analysis via microspectrometry. The leaves of the mutants and normal plants were monitored through a portable VIS/NIR spectrometer SCIOTM (Consumer Physics, Tel Aviv, Israel) covering a spectral range between 740 and 1070 nm. Two months after the transplant, the acropetal progression of the autonecrosis showed three symptomatic areas (basal, median, apical) on each IGSV plant: necrotic, partially damaged, and green, respectively. Significantly lower chlorophyll content was found in the basal and median areas of IGSV compared with the control (Elisir). A supervised classification/modelling method (SIMCA) was used. Applying the SIMCA model to the dataset of 162 tomato samples led to the identification of the boundary between the healthy and damaged samples (translational critical distance). Two 10 nm wavelength ranges centred at 865 nm and 1055 nm exhibited a stronger link between symptomatology and spectral reflectance. Studies on specific highly informative mutants of the type described may allow for the development of predictive models for the early detection of pathogens (or other stresses) via proximal sensing. Solanum ; Biology ; Mutant ; Abiotic component ; Abiotic stress ; Horticulture ; Biotic stress ; Botany ; Gene ; Genetics ; Ecology Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity ; Insect and Pesticide Research
Authors: Sofie Dierickx | Siska Genbrugge | Hans Beeckman | Wannes Hubau | Pierre Kibleur | Jan Van den Bulcke
Source: Research Square (preprint, 2024-03-14)
Field: Chemistry — Organic Chemistry

Non-destructive wood identification using X-ray µCT scanning: which resolution do we need? <title>Abstract</title> Background Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1µm, 3µm, 8µm and 15µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features. Results For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3µm, the scans at 1µm and 8µm were successful in more than half of the studied cases, and even the 15µm resolution showed a high potential for 40% of the samples. Conclusions The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species. Identification (biology) ; Resolution (logic) ; X-ray ; Materials science ; Computer science ; Artificial intelligence ; Physics ; Optics ; Biology ; Botany Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection ; Remote Sensing and LiDAR Applications
Authors: Joséphine Pazem | Marius Krumm | Alexander Q. Vining | Lukas J. Fiderer | Hans J. Briegel
Source: arXiv (Cornell University) (preprint, 2024-11-22)
Field: Materials Science — Materials Chemistry

Free Energy Projective Simulation (FEPS): Active inference with interpretability In the last decade, the free energy principle (FEP) and active inference (AIF) have achieved many successes connecting conceptual models of learning and cognition to mathematical models of perception and action. This effort is driven by a multidisciplinary interest in understanding aspects of self-organizing complex adaptive systems, including elements of agency. Various reinforcement learning (RL) models performing active inference have been proposed and trained on standard RL tasks using deep neural networks. Recent work has focused on improving such agents' performance in complex environments by incorporating the latest machine learning techniques. In this paper, we take an alternative approach. Within the constraints imposed by the FEP and AIF, we attempt to model agents in an interpretable way without deep neural networks by introducing Free Energy Projective Simulation (FEPS). Using internal rewards only, FEPS agents build a representation of their partially observable environments with which they interact. Following AIF, the policy to achieve a given task is derived from this world model by minimizing the expected free energy. Leveraging the interpretability of the model, techniques are introduced to deal with long-term goals and reduce prediction errors caused by erroneous hidden state estimation. We test the FEPS model on two RL environments inspired from behavioral biology: a timed response task and a navigation task in a partially observable grid. Our results show that FEPS agents fully resolve the ambiguity of both environments by appropriately contextualizing their observations based on prediction accuracy only. In addition, they infer optimal policies flexibly for any target observation in the environment. Interpretability ; Inference ; Projective test ; Energy (signal processing) ; Computer science ; Psychology ; Mathematics ; Artificial intelligence ; Pure mathematics ; Statistics Machine Learning in Materials Science ; Scientific Computing and Data Management
Authors: Sriwan Khamtree | Chatree Homkhiew | Chainarong Sriva | Thanate Ratanawilai | Surasit Rawangwong
Source: Research Square (preprint, 2024-01-12)
Field: Materials Science — Polymers and Plastics

Optimal Formulation of Hybrid Polypropylene Composites Reinforced Crab Shell Flour and Rubberwood Sawdust after Immersing in Different Water Conditions for Applications in Tropical Countries <title>Abstract</title> Hybrid recycled polypropylene (rPP) composites reinforced with crab shell (CS) waste and rubberwood sawdust (RWS) were developed for applications in tropical countries. The D-optimal mixture design was applied in experiments, to determine the effects of the three main fractions including rPP, RWS, and CS on the mechanical properties after immersing in distilled water and seawater. Response Surface Methodology (RSM) was used to identify the optimal formulation that maximizes the mechanical properties of the hybrid composites. The results indicated that the mechanical properties fit best with the quadratic models. Statistical analysis revealed that all the models had a less <italic>p</italic>-value than 0.05 (<italic>α</italic> = 0.05) and could accurately predict the mechanical properties. Moreover, these factors negatively affected the mechanical properties whereas the CS had the highest coefficient of all the models. The mechanical properties of the hybrid composites immersed in seawater decreased significantly compared to those immersed in distilled water. Therefore, an optimal formulation of overall mechanical properties was 55.1 wt% rPP, 32.5 wt% RWS, 6.9 wt% CS, 4.0 wt% maleic anhydride-grafted polypropylene, 0.5 wt% ultraviolet stabilizer, and 1.0 wt% lubricant with a desirability score of 0.976. Finally, the optimal formulation of the hybrid composites has been presented and is expected to be applied for applications and waste management from natural materials. <bold>Keywork</bold>: Hybrid composites, Crab shell, Rubberwood sawdust, Mechanical Properties, Optimal formulation Materials science ; Polypropylene ; Sawdust ; Composite material ; Response surface methodology ; Distilled water ; Maleic anhydride ; Pulp and paper industry ; Mathematics ; Chemistry ; Polymer ; Chromatography ; Copolymer Natural Fiber Reinforced Composites ; Polymer Nanocomposites and Properties ; biodegradable polymer synthesis and properties
Authors: Xiaoyue Gao | Zhuohui Liu | Bo Han | Xiaowen Zhang | R. Le Van Mao | Ruochen Shi | Ruixue Zhu | Jiangbo Lu | Tao Wang | Ge Chen | Peng Gao
Source: arXiv (Cornell University) (preprint, 2024-09-19)
Field: Materials Science — Materials Chemistry

Precise structure and polarization determination of Hf0.5Zr0.5O2 with electron ptychography Hf0.5Zr0.5O2 (HZO) is a promising candidate for next generation ferroelectric memories and transistors. However, its ferroelectricity origin is still under debate due to the complex of its phase and microstructure in practical samples. In this study, we investigate the atomic structure of substrate-free HZO freestanding film with multislice electron ptychography, for which the ultra-high space resolution (up to ~25 pm) and capability to simultaneously image the cation and oxygen allow us to precisely determine the intrinsic atomic structures of different phases and reveal subtle changes among them. We clarify that the orthorhombic phase is ferroelectric with spontaneous polarization ~34{\pm}4 μC/cm2 (corresponding to 56{\pm}6 pm in displacement) that is accurately measured through statistical analysis. Significant polarization suppression is observed near the grain boundary, while no distinguishable structural changes are detected near the 180° ferroelectric domain walls. Through the direct oxygen imaging of orthorhombic phase from the [111] zone axis, we quantify a substantial number of oxygen vacancies with a preferential distribution, which influences the polarization direction and strength. These findings provide fundamentals for HZO research, and thus lay a foundation for the design of high-performance ferroelectric devices. Electron ; Ptychography ; Polarization (electrochemistry) ; Physics ; Optics ; Chemistry ; Diffraction ; Nuclear physics Electronic and Structural Properties of Oxides ; Ferroelectric and Negative Capacitance Devices ; Semiconductor materials and devices
Authors: Jiagang Zhang | Ting Zhang
Source: arXiv (Cornell University) (preprint, 2024-04-06)
Field: Materials Science — Materials Chemistry

Ferroelectric metals in van der Waals bilayers The combination of metallicity and ferroelectricity breaks traditional boundaries, paving new avenues for innovative electronic materials and devices. This breakthrough is particularly notable, as metallicity and ferroelectricity have traditionally been considered mutually exclusive physical properties. In this work, starting with non-polar metallic single layers, we propose a general scheme for designing 2D ferroelectric metals (FEMs) based on van der Waals interaction. By first-principles calculations, we further substantiate the feasibility of the design scheme in real materials such as FeSe and H-MnTe2. Notably, this scheme unveils unique metallic ferroelectricity, characterized by reversing polarization through interlayer sliding. Furthermore, the combination of inherent magnetism with sliding ferroelectricity leads to multiferroicity. The investigated design scheme and observed phenomena have broad applicability across 2D materials. Our results not only pave the way for research in 2D FEMs but also offer promising prospects for foundational studies of coupled physical phenomena in 2D lattices. van der Waals force ; Materials science ; Ferroelectricity ; Condensed matter physics ; Chemical physics ; Nanotechnology ; Physics ; Optoelectronics ; Dielectric ; Quantum mechanics ; Molecule Ferroelectric and Piezoelectric Materials ; Advanced Sensor and Energy Harvesting Materials ; Advanced MEMS and NEMS Technologies