jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Niteya Shah | Christine Sweeney | Vinay Ramakrishnaiah | Jeffrey J. Donatelli | Wu-chun Feng
Source:  (article, 2024-05-27)
Field: Materials Science — Surfaces, Coatings and Films

Optimizing and Scaling the 3D Reconstruction of Single-Particle Imaging An X-ray free electron laser (XFEL) facility can produce on the order of 1,000,000 extremely bright X-ray light pulses per second. Using an XFEL to image the atomic structure of a molecule requires fast analysis of an enormous amount of data, estimated to exceed one terabyte per second and requiring petabytes of storage. The SpiniFEL application provides such analysis by determining the 3D structure of proteins from single-particle imaging (SPI) experiments performed using XFELs, but it needs significantly better performance and efficiency to scale and keep up with the terabyte-per-second data production. Thus, this paper addresses the high-performance computing optimizations and scaling needed to improve this 3D reconstruction of SPI data. First, we optimize data movement, memory efficiency, and algorithms to improve the per-node computational efficiency and deliver a 5.28× speedup over the baseline GPU implementation.In addition, we achieved a 485× speedup for the post-analysis reconstruction resolution, which previously took as long as the 3D reconstruction of SPI data. Second, we present a novel distributed shared-memory computational algorithm to hide data latency and load-balance network traffic, thus enabling the processing of 128× more orientations than previously possible. Third, we conduct an exploratory study over the hyperparameter space for the SpiniFEL application to identify the optimal parameters for our underlying target hardware, which ultimately led to an up to 1.25× speedup for the number of streams. Overall, we achieve a 6.6× speedup (i.e., 5.28×1.25) over the previous fastest GPUMPI-based SpiniFEL realization. Scaling ; Computer science ; Iterative reconstruction ; Particle (ecology) ; Computer vision ; Mathematics ; Geology ; Geometry Electron and X-Ray Spectroscopy Techniques
Authors: Dana-Maria Preda | Mircea-Alexandru Comănescu | Victor Voicu | Nelu Grinberg | Andrei Medvedovici
Source: Processes (article, 2024-12-17)
Field: Chemistry — Analytical Chemistry

Peak Spectral Homogeneity in LC/DAD: Exploring Alternatives in Peak Purity Evaluations Spectral peak purity evaluations are often used to control inadequate selectivity issues appearing in liquid chromatography separations coupled with UV-Vis photodiode detection, despite known limitations related to (a) the lack of characteristic absorption bands in UV-Vis for target analytes and overlapping related impurities; (b) increased similarity between the spectral characteristics of co-eluting compounds; (c) large concentration differences between overlapping compounds; (d) perfect co-elution cases. We propose an alternative protocol to evaluate differences between spectra collected over a peak’s elution interval. After normalizing the acquired spectra, linear regression was applied between each pair of spectra, resulting in slope, intercepts, and correlation coefficient sets, from each comparison. The means and standard deviations of each variable are thus computed. An ellipsoid in the 3D Cartesian space illustrates these computations, having the mean coordinates as center and 2 × standard deviations of the variables as the axes. The volume of the ellipsoid should be related to the similarity between the compared spectra; a smaller volume indicates a higher spectral similarity. This approach was evaluated with respect to the (a) concentration of the analytes; (b) spectral acquisition parameters (spectral resolution, spectral frequency acquisition); (c) spectral similarity between overlapping peaks; (d) perfect co-elution situation; (e) influence of spectral processing (derivation, wavelength rationing), using test solutions of carbamazepine (a,b), acetyl cysteine and enalapril maleate (c), or nitrazepam and diazepam (d,e). Homogeneity (statistics) ; Materials science ; Analytical Chemistry (journal) ; Chromatography ; Chemistry ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Statistical Methods and Models
Authors: Savneet Kaur | Jun Watanabe | Eita Uchida | Peng Zhang | Rintaro Hashizume
Source: Neuro-Oncology (article, 2024-06-18)
Field: Materials Science — Biomaterials

HGG-51. INTRANASAL DELIVERY OF PDGFRA-IMMUNOLIPOSOMAL SN-38 FOR THE TREATMENT OF PEDIATRIC HIGH-GRADE GLIOMAS Abstract INTRODUCTION pHGGs are the most common cause of cancer-related death in children, of which the most malignant and devastating tumors include diffuse midline glioma (DMG). Its anatomical location in the braistem, infiltrative nature, and blood-brain barrier (BBB) limit surgical resection and the distribution of systemically administered drugs. Intranasal delivery (IND) is a noninvasive method that bypasses the BBB, by leveraging the unique anatomic connections of the olfactory and trigeminal nerve pathways with the nasal cavity. We previously demonstrated the efficacy of IND of liposomal (LS) formulation of the active metabolite of the DNA topoisomerase I inhibitor, irinotecan, LS-SN-38, in orthotopic human brainstem xenograft models. The specificity of liposomes can be enhanced by using immunoliposome (iLS) formulation, which are coated with antibodies specific to the tumor cells leading to targeted drug delivery and reduced toxicity to normal cells. Platelet-derived growth factor receptor alpha (PDGFRA) plays a role in DMG oncogenesis and is expressed in as much as 70% of DMG by immunohistochemistry. In this study, we evaluated the specificity of anti-PDGFRA monoclonal antibody conjugated immunoliposome (PDGFRA-iLS) in pHGG cell lines. METHODS PDGFRA signals were assessed in pHGG cells using western blotting. Cells with high and low expression of PDGFRA were treated with rhodamine (Rho) labeled PDGFRA-iLS and imaged with fluorescent microscope. RESULTS DIPG007, SF7761 and KNS42 expressed high levels of PDGFRA, while SF8628 and DIPG36 cells showed low expression. Fluorescence microscopy revealed high PDGFRA-rhodamine (Rho)-iLS expression in DIPG007 cells (PDGFRA high), relative to SF8628 and DIPG36 cells (PDGFRA low). CONCLUSION PDGFRA-Rho-iLS shows increase cellular uptake in DIPG cells. Work is underway to determine the biodistribution, host toxicity, and anti-tumor activity of IND of PDGFRA-iLS-SN- 38 alone and in combination with radiation therapy in pHGG xenograft models. Nasal administration ; PDGFRA ; Medicine ; Oncology ; Internal medicine ; Pharmacology Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery
Authors: Norfadilah Rosle | Mohamad Nur Khairul Hafizi Rohani | Wan Nurul Auni Wan Mohammad | Nor Asiah Muhamad | Mohamad Kamarol Mohd Jamil
Source: Journal of Advanced Research in Applied Sciences and Engineering Technology (article, 2024-04-03)
Field: Materials Science — Materials Chemistry

A Study on Simultaneous Measurement of Partial Discharge in Epoxy Resin Insulator using IMC and Rogowski Coil In practice, field measurement of partial discharge is easily suffered by interferences due to the noisy signal has been mixed with the resulting partial discharge signal. Therefore, the detection and measurement of PD are important to monitor the insulation life in high voltage (HV) power equipment. The paper presents the simultaneous measurement of partial discharge (PD) pulse parameters using the impedance matching circuit and the Rogowski coil sensor to study the features of partial discharge on the epoxy resin insulator. Two different thicknesses of samples were used to observe the PD pulse parameters with the voltage applied vary depending on the thickness of the sample to attain constant electric field intensity for both samples. The step response parameters resulted from the measurement can be used as a time domain features to discriminate various types of PD in HV power equipment. Thus, the PD can be observed clearly, maintenance can be performed, and the performance of the power system can be improved. Rogowski coil ; Epoxy ; Partial discharge ; Materials science ; Electromagnetic coil ; Insulator (electricity) ; Composite material ; Electrical engineering ; Engineering ; Voltage High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission ; Aerosol Filtration and Electrostatic Precipitation
Authors: Zeyu Li | Kangxiang Qin | Yong He | Wang Zhou | Xinsheng Zhang
Source: arXiv (Cornell University) (preprint, 2024-03-12)
Field: Chemistry — Analytical Chemistry

Knowledge Transfer across Multiple Principal Component Analysis Studies Transfer learning has aroused great interest in the statistical community. In this article, we focus on knowledge transfer for unsupervised learning tasks in contrast to the supervised learning tasks in the literature. Given the transferable source populations, we propose a two-step transfer learning algorithm to extract useful information from multiple source principal component analysis (PCA) studies, thereby enhancing estimation accuracy for the target PCA task. In the first step, we integrate the shared subspace information across multiple studies by a proposed method named as Grassmannian barycenter, instead of directly performing PCA on the pooled dataset. The proposed Grassmannian barycenter method enjoys robustness and computational advantages in more general cases. Then the resulting estimator for the shared subspace from the first step is further utilized to estimate the target private subspace in the second step. Our theoretical analysis credits the gain of knowledge transfer between PCA studies to the enlarged eigenvalue gap, which is different from the existing supervised transfer learning tasks where sparsity plays the central role. In addition, we prove that the bilinear forms of the empirical spectral projectors have asymptotic normality under weaker eigenvalue gap conditions after knowledge transfer. When the set of informativesources is unknown, we endow our algorithm with the capability of useful dataset selection by solving a rectified optimization problem on the Grassmann manifold, which in turn leads to a computationally friendly rectified Grassmannian K-means procedure. In the end, extensive numerical simulation results and a real data case concerning activity recognition are reported to support our theoretical claims and to illustrate the empirical usefulness of the proposed transfer learning methods. Principal component analysis ; Component (thermodynamics) ; Computer science ; Knowledge transfer ; Principal (computer security) ; Knowledge management ; Artificial intelligence ; Computer security ; Physics Spectroscopy and Chemometric Analyses
Authors: 梁莹 Liang Ying | 马琨 Ma Kun | 张馨予 Zhang Xinyu | 杨啟富 Yang Qifu | 吴加权 Wu Jiaquan
Source: Laser & Optoelectronics Progress (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

基于近红外光谱和随机森林的烟叶病害种类识别 使用手持近红外光谱仪采集受到不同种类病害烟叶样本的光谱数据，利用Savitzky-Golay（SG）平滑滤波和一阶导数对原始光谱数据进行预处理，结合随机森林（RF）算法建立不同病害类别的训练模型，并进行了样本测试。同时，与传统分类算法支持向量机（SVM）、反向传播（BP）神经网络和偏最小二乘判别（PLS-DA）进行了对比研究。实验结果表明，RF算法的分类准确率、灵敏度、特异度值均高于SVM、BP神经网络和PLS-DA算法，且RF算法的二级评价指标F1分数和曲线下的面积（AUC）也均高于SVM、BP神经网络和PLS-DA算法。研究结果表明所采用的RF算法分类预测准确率较高，模型整体性能也较为优异。所提出的基于手持式近红外光谱仪和RF算法的快速检测方法能够高效、无损、快速、准确地识别出烟叶病害种类，为烟叶病害种类检测与识别提供了一种新的技术参考。 Computer science Spectroscopy and Chemometric Analyses
Authors: Debatri Chattopadhyay | S. Al-Shammari | Fabio Antonini | S. Fairhurst | Benjamin Miles | V. Raymond
Source: arXiv (Cornell University) (preprint, 2024-07-11)
Field: Materials Science — Materials Chemistry

The Impact of Astrophysical Priors on Parameter Inference for GW230529 We investigate the effects of prior selection on the inferred mass and spin parameters of the neutron star-black hole merger GW230529\_181500. Specifically, we explore models motivated by astrophysical considerations, including massive binary and pulsar evolution. We examine mass and spin distributions of neutron stars constrained by radio pulsar observations, alongside black hole spin observations from previous gravitational wave detections. We show that the inferred mass distribution highly depends upon the spin prior. Specifically, under the most restrictive, binary stellar evolution models, we obtain narrower distributions of masses with a black hole mass of $4.3^{+0.1}_{-0.1}\,M_{\odot}$and neutron star mass of $1.3^{+0.03}_{-0.03}\,M_{\odot}$ where, somewhat surprisingly, it is the prior on component spins which has the greatest impact on the inferred mass distributions. Re-weighting using neutron star mass and spin priors from observations of radio pulsars, with black hole spins from observations of gravitational waves, yields the black hole and the neutron star masses to be $3.8^{+0.5}_{-0.6} \,M_\odot$ and $1.4^{+0.2}_{-0.1} \,M_\odot$ respectively. The sequence of compact object formation -- whether the neutron star or the black hole formed first -- cannot be determined at the observed signal-to-noise ratio. However, there is no evidence that the black hole was tidally spun up. Prior probability ; Inference ; Econometrics ; Computer science ; Mathematics ; Statistics ; Artificial intelligence ; Bayesian probability Solid-state spectroscopy and crystallography
Authors: Hye‐Young Seo | Eun Ji Suh | Eun Bin Choi | Mi‐Ja Lee | Han Gyeol Lee | Woo Duck Seo | Jung In Kim | Seung-Yeob Song
Source: Korean Journal of Breeding Science (article, 2024-03-01)
Field: Chemistry — Analytical Chemistry

Determination of Production Year Using Multivariate Statistical Analysis from FTIR Spectrum Data of Perilla Leaves This study used perilla seeds produced in 2019, 2020, and 2021 to determine the year of production using multivariate statistical analysis of Fourier-transform infrared (FTIR) spectral data of perilla leaves.Spectral analysis based on multivariate statistical analysis of whole-cell extracts was used to distinguish the perilla leaves at the metabolic level.FT-IR spectral data of the leaves were analyzed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA).The FTIR spectrum identified spectral differences between the frequency regions of 1,700 to 1,500, 1,500 to 1,300, and 1,100 to 950 cm -1 .This spectral region reflects quantitative and qualitative changes in amides I, II in amino acids and proteins (1,700-1,500 cm -1 ), phosphodiester groups from nucleic acids and phospholipids (1,500-1,300 cm -1 ), and carbohydrate compounds (1,100-950 cm -1 ).PCA revealed separate clusters corresponding to production traceability relationships.Therefore, PCA can be used to distinguish between production in 2019, 2020, and 2021 based on different metabolite contents.PLS-DA showed a similar production traceability classification for the perilla seeds.In addition, this metabolic identification system can be used to rapidly select and classify useful perilla seed varieties. Multivariate analysis ; Biology ; Perilla ; Multivariate statistics ; Fourier transform infrared spectroscopy ; Production (economics) ; Horticulture ; Statistics ; Mathematics ; Physics Spectroscopy and Chemometric Analyses ; Natural Products and Biological Research
Authors: Timo Joas
Source: arXiv (Cornell University) (preprint, 2024-06-06)
Field: Materials Science — Materials Chemistry

High-Fidelity Electron Spin Gates for Scaling Diamond Quantum Register All data plots in the paper as vector graphics (.svg), together with their data (stored as .csv). An example Python jupyter notebook to load the data is included. Register (sociolinguistics) ; Scalability ; Spin (aerodynamics) ; Diamond ; Physics ; Fidelity ; Register file ; Electron ; High fidelity ; Computer science ; Materials science ; Quantum mechanics ; Telecommunications Diamond and Carbon-based Materials Research ; Quantum and electron transport phenomena ; Advancements in Semiconductor Devices and Circuit Design
Authors: Denis Turcu | Abigail N Zadina | L. F. Abbott | Nathaniel B. Sawtell
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-10-22)
Field: Chemistry — Electrochemistry

An end-to-end model of active electrosensation Weakly electric fish localize and identify objects by sensing distortions in a self-generated electric field. Fish can determine the resistance and capacitance of an object, for example, even though the field distortions being sensed are small and highly-dependent on object distance and size. Here we construct a model of the responses of the fish's electroreceptors on the basis of experimental data, and we develop a model of the electric fields generated by the fish and the distortions due to objects of different resistances and capacitances. This provides us with an accurate and efficient method for generating large artificial data sets simulating fish interacting with a wide variety of objects. Using these sets, we train an artificial neural network (ANN), representing brain areas downstream of electroreceptors, to extract the 3D location, size, and electrical properties of objects. The model performs best if the ANN operates in two stages: first estimating object distance and size and then using this information to extract electrical properties. This suggests a specific form of modularity in the electrosensory system that can be tested experimentally and highlights the potential of end-to-end modeling for studies of sensory processing. End-to-end principle ; End of history ; Computer science ; Computer network ; Political science Electrochemical Analysis and Applications ; Water Quality Monitoring Technologies ; Advanced Memory and Neural Computing
Source: PLANT ARCHIVES (article, 2024-10-11)
Field: Chemistry — Analytical Chemistry

MONITORING MANGO SURFACE VARIATIONS USING NON-DESTRUCTIVE THERMAL IMAGING Infrared thermal imaging is a powerful tool used to monitor the quality and safety of various agricultural products.In this study, infrared thermal imaging was used to study the temperature variation of mango during storage.In this study, an E76 thermal camera (FLIR systems) with a thermal sensitivity of <0.04C was used to evaluate the surface temperature profiles of mango fruits.Thermal images of mangoes of the variety Dasheri were captured under heated and dark conditions and analyzed.The maximum temperature difference between healthy and deteriorated mangoes during storage was observed to be 10.97 .This temperature difference is likely due to changes in the internal structure and physicochemical properties of the mangoes as they deteriorate.The findings suggest that infrared thermal imaging is feasible for non-destructive detection of deterioration caused by physiological changes in Dasheri mangoes is possible using active thermography for monitoring the fruit quality which could enhance the operation and postharvest handling of mango under storage. Environmental science ; Mineralogy ; Remote sensing ; Biology ; Botany ; Geology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Date Palm Research Studies
Authors: Feng Liu | Yansheng Shi | Shuainan Zhang | Wei Wang
Source: Photonics (article, 2024-08-29)
Field: Materials Science — Materials Chemistry

Study on the Detection of Single and Dual Partial Discharge Sources in Transformers Using Fiber-Optic Ultrasonic Sensors Partial discharge is a fault that occurs at the site of insulation defects within a transformer. Dual instances of partial discharge origination discharging simultaneously embody a more intricate form of discharge, where the interaction between the discharge sources leads to more intricate and unpredictable insulation damage. Conventional piezoelectric transducers are magnetically affixed to the exterior metal tank of transformers. The ultrasonic signals emanating from partial discharge undergo deflection and reverberation upon traversing the windings, insulation paperboards, and the outer shell, resulting in signal attenuation and thus making it difficult to detect such faults. Furthermore, it is challenging to distinguish between simultaneous discharges from dual partial discharge sources and continuous discharges from a single source, often leading to missed detection and repairs of fault points, which increase the maintenance difficulty and cost of power equipment. With the advancement of MEMS (Micro-Electro-Mechanical System) technology, fiber-optic ultrasonic sensors have surfaced as an innovative technique for optically detecting partial discharges. These sensors are distinguished by their minute dimensions, heightened sensitivity, and robust immunity to electromagnetic disturbances. and excellent insulation properties, allowing for internal installation within power equipment for partial discharge monitoring. In this study, we developed an EFPI (Extrinsic Fabry Perot Interferometer) optical fiber ultrasonic sensor that can be installed inside transformers. Based on this sensor array, we also created a partial discharge ultrasonic detection system that estimates the directional information of single and dual partial discharge sources using the received signals from the sensor array. By utilizing the DOA (Direction of Arrival) as a feature recognition parameter, our system can effectively detect both simultaneous discharges from dual partial discharge sources and continuous discharges from a single source within transformer oil tanks, meeting practical application requirements. The detection methodology presented in this paper introduces an original strategy and resolution for pinpointing the types of partial discharges occurring under intricate conditions within power apparatus, effectively distinguishing between discharges from single and dual partial discharge sources. Partial discharge ; Ultrasonic sensor ; Acoustics ; Transformer ; Optical fiber ; Acoustic emission ; Electromagnetic coil ; Materials science ; Interferometry ; Nondestructive testing ; Electrical engineering ; Computer science ; Optics ; Voltage ; Engineering ; Telecommunications ; Physics High voltage insulation and dielectric phenomena ; Advanced Fiber Optic Sensors ; Analytical Chemistry and Sensors
Authors: Zeeshan Ali Haq | Zainul Abdin Jaffery | Shabana Mehfuz
Source: Traitement du signal (article, 2024-12-31)
Field: Chemistry — Analytical Chemistry

Integrated Approach for Defect Detection and Grading of Apples: Thermal Imaging and Adaptive Neuro-Fuzzy Inference System for Enhanced Quality Assessment Adaptive neuro fuzzy inference system ; Computer science ; Fuzzy inference system ; Artificial intelligence ; Neuro-fuzzy ; Inference ; Grading (engineering) ; Fuzzy inference ; Machine learning ; Fuzzy logic ; Fuzzy control system ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Date Palm Research Studies