jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ioana-Ancuta Halmaciu | Ioana Ionel | Maria- Cristina Miutescu
Source: Preprints.org (preprint, 2024-02-19)
Field: Materials Science — Materials Chemistry

Influence upon Biogas Production of the C/N Ratio and the Heavy Metal Incidence in the Manure Composition The article presents comparative results from 5 categories of animals (4 samples originating from pigs, 2 from cows, 1 from chicken, 1 from ostriches, 1 from horses, samples quantified with A, B, C, D, E, F, G, H, I). These samples were collected from large, medium and small (family) farms. The results were validated by the biogas production generated by the respective samples, using the Automatic Methane Potential Test System (AMPTS II) bio-processor. The largest amounts of biogas (2,464.5 Nml, 2,262.0 Nml) were recorded for the samples from pig farms (Sample B and Sample D), whereas the lowest values were obtained in the case of Sample A (414.1 Nml) and Sample C (558.3 Nml). The heavy metals analyzed in the article are Zn, Cu, Fe, Mn, Ca, K, As. The results corroborate that the C/N ratio can also vary to values lower than 20-30, without affecting the biogas production process, and the heavy metal content must be known especially for the full management of the wastes. All final data presented in the article are based on repeated, triplicate experiments, with less as 2% deviation between data. Biogas ; Biogas production ; Manure ; Heavy metals ; Composition (language) ; Metal ; Methane ; Chemistry ; Sample (material) ; Animal science ; Mathematics ; Environmental science ; Pulp and paper industry ; Environmental chemistry ; Agronomy ; Waste management ; Biology ; Anaerobic digestion ; Chromatography ; Engineering Metallurgy and Material Science
Authors: Mengxue Song | Ce Liu | Liqing Chen | Lichao Liu | Jingming Ning | Chuanyang Yu
Source: International journal of agricultural and biological engineering (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Recognition of tea buds based on an improved YOLOv7 model The traditional recognition algorithm is prone to miss detection targets in the complex tea garden environment, and it is difficult to satisfy the requirement for tea bud recognition accuracy and efficiency. In this study, the YOLOv7 model was developed to improve tea bud recognition accuracy for some extreme tea garden scenarios. In the improved model, a lightweight MobileNetV3 network is adopted to replace the original backbone network, which reduces the size of the model and improves detection efficiency. The convolutional block attention module is introduced to enhance the attention to the features of small and occluded tea buds, suppressing the interference of the complex tea garden environment on tea bud recognition and strengthening the feature extraction capability of the recognition model. Moreover, to further improve recognition accuracy for dense and occlusive scenarios, the soft non-maximum suppression strategy is integrated into the recognition model. Experimental results show that the improved YOLOv7 model has the precision, recall, and mean average precision (mAP) values of 88.3%, 87.4%, and 88.5%, respectively. Compared with the Faster R-CNN, SSD, and original YOLOv7 algorithms, the mAP of the improved YOLOv7 model is increased by 7.4, 7.9, and 3.9 percentage points, respectively, and its recognition speed is also promoted by 94.9%, 46.2%, and 16.9%. The proposed model can rapidly and accurately identify the tea buds in multiple complex tea garden scenarios - such as dense distribution, being close to the background color, and mutual occlusion - with high generalization and robustness, which can provide theoretical and technical support for the recognition of tea-picking robots. Keywords: tea bud recognition, YOLOv7, lightweight MobileNetV3 network, CBAM DOI: 10.25165/j.ijabe.20241706.9095 Citation: Song M X, Liu C, Chen L Q, Liu L C, Ning J M, Yu C Y. Recognition of tea buds based on an improved YOLOv7 model. Int J Agric & Biol Eng, 2024; 17(6): 238–244. Horticulture ; Mathematics ; Biology Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Smart Agriculture and AI
Authors: Mingming Chen | Yan Song | Yanlong Li | Xin-Yue Sun | Feng Zuo | Lili Qian
Source: Foods (article, 2024-10-11)
Field: Chemistry — Analytical Chemistry

The Impact of Sample Quantity, Traceability Scale, and Shelf Life on the Determination of the Near-Infrared Origin Traceability of Mung Beans This study aims to address the gap in understanding of the impact of the sample quantity, traceability range, and shelf life on the accuracy of mung bean origin traceability models based on near-infrared spectroscopy. Mung beans from Baicheng City, Jilin Province, Dorbod Mongol Autonomous, Tailai County, Heilongjiang Province, and Sishui County, Shandong Province, China, were used. Through near-infrared spectral acquisition (12,000-4000 cm<sup>-1</sup>) and preprocessing (Standardization, Savitzky-Golay, Standard Normal Variate, and Multiplicative Scatter Correction) of the mung bean samples, the total cumulative variance contribution rate of the first three principal components was determined to be 98.16% by using principal component analysis, and the overall discriminatory correctness of its four origins combined with the K-nearest neighbor method was 98.67%. We further investigated how varying sample quantities, traceability ranges, and shelf lives influenced the discrimination accuracy. Our results indicated a 4% increase in the overall correct discrimination rate. Specifically, larger traceability ranges (Tailai-Sishui) improved the accuracy by over 2%, and multiple shelf lives (90-180-270-360 d) enhanced the accuracy by 7.85%. These findings underscore the critical role of sample quantity and diversity in traceability studies, suggesting that broader traceability ranges and comprehensive sample collections across different shelf lives can significantly improve the accuracy of origin discrimination models. Traceability ; Shelf life ; Scale (ratio) ; Sample (material) ; Mung bean ; Environmental science ; Infrared ; Food science ; Chemistry ; Mathematics ; Geography ; Statistics ; Chromatography ; Physics ; Cartography Spectroscopy and Chemometric Analyses ; Listeria monocytogenes in Food Safety ; Food composition and properties
Authors: A. J. Dimoff | C. J. Hansen | Richard J. Stancliffe | B. Kubátová | И. Статева | A. Kučinskas | V. Dobrovolskas
Source: Astronomy and Astrophysics (article, 2024-10-03)
Field: Materials Science — Materials Chemistry

<i>S</i>-process nucleosynthesis in chemically peculiar binaries Context. Around half of the heavy elements in the Universe are formed through the slow neutron capture (s-) process, which takes place in thermally pulsing asymptotic giant branch (AGB) stars with masses of 1 − 6 M ⊙ . The nucleosynthetic imprint of the s -process can be studied by observing the material on the surface of binary barium (Ba), carbon (C), CH, and carbon-enhanced metal-poor (CEMP) stars. Aims. We study the s -process by observing the luminous components of binary systems polluted by a previous AGB companion. Our radial velocity (RV) monitoring program establishes an ongoing collection of binary stars exhibiting enrichment in s -process material for the study of elemental abundances, the production of s -process material, and binary mass transfer. Methods. From high-resolution optical spectra, we measured RVs for 350 stars and derived stellar parameters for approximately 150 stars using ATHOS. For a subsample of 24 chemically interesting stars, we refined our atmospheric parameters using ionization and excitation balance with the Xiru program. We used the MOOG code to compute one-dimensional local thermodynamic equilibrium (1D-LTE) abundances of carbon, magnesium, s -process elements (Sr, Y, Zr, Mo, Ba, La, Ce, Nd, Pb), and Eu to investigate neutron capture events and stellar chemical composition. We estimated dynamical stellar masses via orbital optimization using Markov chain Monte Carlo techniques in the ELC program, and we compared our results with low-mass AGB models in the FUll-Network Repository of Updated Isotopic Tables &amp; Yields (FRUITY) database. Results. In our abundance subsample, we find enhancements in s -process material in spectroscopic binaries, a signature of AGB mass transfer. We add the element Mo to the abundance patterns, and for 12 stars we add Pb detections or upper limits, as these are not known in the literature. Computed abundances are in general agreement with the literature. Comparing our abundances to dilution-modified FRUITY yields, we find correlations in s -process enrichment and AGB mass, which are supported by dynamical modeling from RVs. Conclusions. From our high-resolution observations, we expand heavy element abundance patterns and highlight binarity in our chemically interesting systems. We find trends in s -process element enhancement from AGB stars, and agreement between theoretical and dynamically modeled masses. We investigate evolutionary stages for a small subset of our stars. Physics ; Nucleosynthesis ; Astrophysics ; Stellar nucleosynthesis ; r-process ; Astronomy ; s-process ; Stars X-ray Diffraction in Crystallography ; DNA and Nucleic Acid Chemistry ; Titanium Alloys Microstructure and Properties
Authors: Michael P. Hennessey | Finnegan Wilson | Grace I. Rabinowitz | Max J. Sevcik | Kadyn J. Tucker | Dylan J. Kline | David K. Amondson | H. Keo Springer | Kyle T. Sullivan | Veronica Eliasson | Jonathan L. Belof
Source: arXiv (Cornell University) (preprint, 2024-04-09)
Field: Materials Science — Materials Chemistry

Modification of Jet Velocities in an Explosively Loaded Copper Target with a Conical Defect In this work, the design and execution of an experiment with the goal of demonstrating control over the evolution of a copper jet is described. Simulations show that when using simple multi-material buffers placed between a copper target with a conical defect and a cylinder of high-explosive, a variety of jetting behaviors occur based on material placement, including both jet velocity augmentation and mitigation. A parameter sweep was performed to determine optimal buffer designs in two configurations. Experiments using the optimal buffer designs verified the effectiveness of the buffer and validated the modeling. Conical surface ; Jet (fluid) ; Copper ; Explosive material ; Mechanics ; Cylinder ; Materials science ; Buffer (optical fiber) ; Work (physics) ; Mechanical engineering ; Computer science ; Structural engineering ; Composite material ; Physics ; Engineering ; Metallurgy ; Chemistry High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Structural Response to Dynamic Loads
Authors: Alyssa A Nitz | Ansima R Mongane | Luke Squires | Samuel Payne
Source: Journal of the American Society for Mass Spectrometry (article, 2024-08-30)
Field: Chemistry — Spectroscopy

Attracting Computational Researchers to Proteomics License ; Library science ; Citation ; Scholarship ; History ; Political science ; Computer science ; Law Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Jonas Winklmann | Andrea Alberti | Martin Schulz
Source:  (article, 2024-09-15)
Field: Materials Science — Materials Chemistry

Comparison of Atom Detection Algorithms for Neutral Atom Quantum Computing In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some comparable metric is estimated and used to predict the presence or absence of an atom. Across different setups, we can see a vast number of different approaches used to analyze these images. Often, the choice of detection algorithm is either not mentioned at all or it is not justified. We investigate several different algorithms and compare their performance in terms of both precision and execution run time. To do so, we rely on a set of synthetic images across different simulated exposure times with known occupancy states, which we generated using a previously validated imaging simulation. Since the use of simulation provides us with the ground truth of atom site occupancy, we can easily state precise error rates and variances of the reconstructed property. However, knowing the relative performance of these algorithms is not sufficient to justify their use, since better ones can exist that were not compared. To investigate this possibility, we calculated the Cramer-Rao bound in order to establish an upper limit that even a perfect estimator cannot outperform. As the metric of choice, we used the number of photonelectrons that can be contributed to a specific atom site. Every estimator that reconstructs a different property can simply be scaled accordingly. Since the bound depends on the occupancy of neighboring sites, we provide the best and worst cases, as well as a half filled one, which should represent an averaged bound best. Our comparison shows that of our tested algorithms, a global nonlinear least-squares solver that uses the optical system's point spread function (PSF) to return a global bias and each sites' number of photoelectrons performed the best, on average crossing the worst-case bound for longer exposure times. Its main drawback is its huge computational complexity and, thus, required calculation time. We manage to somewhat reduce this problem, suggesting that its use may be viable, leading us to a novel group of algorithms that present a compromise between speed and precision. However, our study also shows that for cases where utmost speed is required, simple algorithms, like summing up pixel values around atom sites, may be preferable. Algorithm ; Upper and lower bounds ; Atom (system on chip) ; Computer science ; Metric (unit) ; Estimator ; Mathematics ; Statistics Electronic and Structural Properties of Oxides ; Quantum Information and Cryptography ; Quantum Computing Algorithms and Architecture
Authors: Mohammed Laid Tlili | Roukia Hammoudi | S. Touati | A. Belimi | S. Lamoudi
Source: Učënye zapiski Kazanskogo universiteta. Seriâ  Estestvennye nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Estestvennye nauki/Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Estestvennye nauki (article, 2024-09-21)
Field: Chemistry — Organic Chemistry

Antioxidant and Antidiabetic Properties of the Water Extract from Sigoise Olive Cultivar (Olea europaea L.), El Oued Region (Algeria) Olive tree leaves ( Olea europaea L.) have been widely used in Mediterranean traditional medicine to prevent and treat various ailments. This study investigated the effects of consuming a water extract of Sigoise olive leaves on antioxidant levels and type II diabetes. The extract was prepared by steeping 10 g of dried olive leaves in 500 mL of boiling water and then given to 20 Algerian volunteers (10 diabetic subjects and 10 healthy controls), who consumed it twice a day for a month. The volunteers were screened by biochemical blood tests before and by the end of the experiment. The antioxidant activity was assessed using DPPH (2,2-diphenyl-1-picrylhydrazyl-based assay, 35.3 ± 0.5 mg/mL) and FRAP assays (ferric reducing antioxidant power assay, 8.3 ± 0.1 mg/mL). The quantitative analysis revealed high contents of total polyphenols (41.8 ± 0.8 mg gallic acid equivalent per 1 g of extract) and total flavonoids (14.3 ± 0.8 mg rutin equivalent per 1 g of extract). The hypoglycemic effect of the extract was shown, thus confirming that it helps improve renal function and prevents cardiovascular disorders in type II diabetic patients. No toxic effects on kidney or liver function were observed. Despite clear health-boosting benefits, further research is needed to fully validate them clinically. Olea ; Cultivar ; Antioxidant ; Oleaceae ; Horticulture ; Biology ; Botany ; Traditional medicine ; Medicine ; Biochemistry Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities ; Botanical Research and Applications
Authors: Neha M Arolkar | C. Ortíz | Nikita Dapurkar | Carlos Blanes | Pablo Gonzalez-Planells
Source: Preprints.org (preprint, 2024-07-04)
Field: Chemistry — Analytical Chemistry

Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing Okra, a widely grown vegetable in many regions, often suffers from freshness loss during transportation, causing significant waste. Factors like variety, environment, maturity, and handling affect its quality. Current methods for checking okra tenderness are slow and prone to mistakes, so we need a better, non-damaging method. This study aims to use a device on a robot arm to assess okra freshness and tenderness. We tested 120 okra pods, storing some in a cold chamber for 24 hours (considered tender) and others at room temperature for two days before moving them to a cold environment for five more days (considered not tender). We used a force sensor on a robot arm to measure okra hardness without damaging it, then did tenderness tests. We found that certain sensor data, like the first slope (S1) and the difference between the maximum value and the first overshoot (Os), were good predictors of tenderness, with an accuracy rate of nearly 80%. We also validated this non-damaging method with weight loss, compression, and puncture tests, achieving a 95.5% accuracy rate in distinguishing between tender and non-tender okra pods. Tenderness ; Compression (physics) ; Computer science ; Robotic arm ; Overshoot (microwave communication) ; Simulation ; Medicine ; Mathematics ; Agricultural engineering ; Biomedical engineering ; Surgery ; Materials science ; Composite material ; Engineering ; Artificial intelligence ; Telecommunications Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Advanced Chemical Sensor Technologies
Authors: P. Monti-Guarnieri | L. Bandiera | Canale, Nicola | S. Carsi | De Salvador, Davide | Guidi, Vincenzo | Viktar Haurylavets | Lezzani, Giulia | Francesco Longo | Malagutti, Lorenzo | Mangiacavalli, Sofia | A. Mazzolari | M. Moulson | Negrello, Riccardo | G. Paternò | Perna, Leonardo | Petroselli, Christian | M. Prest | Romagnoni, Marco | Saibene, Giosuè | A. Selmi | Sgarbossa, Francesco | M. Soldani | Alexei Sytov | Victor V. Tikhomirov | E. Vallazza
Source: arXiv (Cornell University) (preprint, 2024-05-18)
Field: Chemistry — Physical and Theoretical Chemistry

Particle identification capability of a homogeneous calorimeter composed of oriented crystals Recent studies have shown that the electromagnetic shower induced by a high-energy electron, positron or photon incident along the axis of an oriented crystal develops in a space more compact than the ordinary. On the other hand, the properties of the hadronic interactions are not affected by the lattice structure. This means that, inside an oriented crystal, the natural difference between the hadronic and the electromagnetic shower profile is strongly accentuated. Thus, a calorimeter composed of oriented crystals could be intrinsically capable of identifying more accurately the nature of the incident particles, with respect to a detector composed only of non-aligned crystals. Since no oriented calorimeter has ever been developed, this possibility remains largely unexplored and can be investigated only by mean of numerical simulations. In this work, we report the first quantitative evaluation of the particle identification capability of such a calorimeter, focusing on the case of neutron-gamma discrimination. We demonstrate through Geant4 simulations that the use of oriented crystals significantly improves the performance of a Random Forest classifier trained on the detector data. This work is a proof that oriented calorimeters could be a viable option for all the environments where particle identification must be performed with a very high accuracy, such as future high-intensity particle physics experiments and satellite-based gamma-ray telescopes. Calorimeter (particle physics) ; Homogeneous ; Identification (biology) ; Particle identification ; Particle (ecology) ; Materials science ; Nuclear physics ; Physics ; Optics ; Statistical physics ; Detector ; Geology ; Botany thermodynamics and calorimetric analyses ; Insect and Arachnid Ecology and Behavior
Authors: Bilian Cheng | Gaoming Jiang | Fang‐Lue Zhang | Ailan Wan | Haisang Liu | Bingxian Li | Leili Gao
Source: Autex Research Journal (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Drape test of fully formed knitted flared skirts based on 3D-printed human body posture Abstract This study proposes a novel drape test method for fully formed knitted flared skirts, specifically tailored to account for the three-dimensional (3D) morphology of the human body. The objective is to accurately assess the drape characteristics of such skirts by developing a comprehensive testing approach. First, a 3D human body model in multiple postures was created using 3ds-Max modeling software and then printed with a 3D printer to serve as a customized test stand. The design and knitting principles for the fully formed flared skirt were examined, and samples were produced using a Shima Seiki four-needle bed computerized flat knitting machine. After fitting the skirt samples onto the 3D-printed human model, drape characteristics were measured with a YG811 drape tester. Using 18 sample skirts, the drape data were analyzed with SPSS26.0 software, revealing that the 3D-printed human model method allows for precise measurement of the drape in fully formed knitted fabrics. This approach offers a more realistic and accurate assessment of drapes, contributing valuable insights for textile design and evaluation in knitted garment production. 3d printed ; Engineering ; Engineering drawing ; Test (biology) ; Human body ; Materials science ; Computer science ; Biomedical engineering ; Geology ; Artificial intelligence Textile materials and evaluations ; 3D Shape Modeling and Analysis ; Optical measurement and interference techniques
Authors: Christian Joel Lazo | Emmanuel Jerusalem | Gabriel Angelo Coñejos | John Ace Malabanan | Marianito Gallego
Source: BIO Web of Conferences (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Consumer quality preferences: Parameters to accelerate bell pepper imaging and classification technology Marketability of fresh produce is highly dependent on consumer preferences. When consumers’ standards are not met, this will lead to food wastage in the long run. Manual sorting should be replaced with IoT technology that can classify fresh products based on different parameters. However, it is a difficult task and can sometimes be inaccurate. In this study, the authors aim to (1) understand the key quality parameters of bell pepper, (2) establish quality control measures from planting to consuming, and (3) understand and determine the technology features and parameters in terms of hardware preference and characteristics. The study gathered three groups of respondents namely the farmers, retailers, and household consumers. The paper concludes consumer preferences within the bell pepper industry and underscores the necessity of quality control measures to uphold standards and minimize losses such as temperature-controlled storage and sorting processes through computer vision. Pepper ; Quality (philosophy) ; Computer science ; Physics ; Computer security Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Sensory Analysis and Statistical Methods