Plot Distribution Research Articles

Predicting Willow Planting Events by Conventional Machine Learning from GPS Data: Accuracy, Generalization Ability, and Potential for Improvement

Willow cultivation is an important activity that can provide greater amounts of cleaner and renewable energy. To support the development of this farming sector, data is required on the spatial distribution of planted plots, as well as on the performance of operations typically required in willow crop management. Unfortunately, this kind of data is largely unavailable, while documenting it is a challenging task. GPS data, which may be feasibly collected during operations, may be a good carrier of information not only to document the spatial location of plots, but also to learn about the frequency of typical events as specific to willow operational management. Based on a GPS dataset characterizing two plots, which was collected during planting operations and labelled manually (8,385 observations), a neural network was used in this study to spatially classify events such as driving (hereafter called D), maneuvering (hereafter called M), planting (hereafter called P), and being stopped (hereafter called S). Three models were trained and validated based on features such as GPS speed (hereafter called model S), GPS speed and leg length (hereafter called model S&L), and GPS speed, leg length, and heading (hereafter called model S&L&H), respectively. Classification performance was found to be impressive, with an overall accuracy of 92.0 (S), 92.1 (S&L), and 93.3% (S&L&H), respectively. The quality of the models was then checked visually using a dataset containing unseen data characterizing two plots of different cardinal orientation, indicating an acceptable generalization ability. The methods described in the paper may be useful when dealing with large datasets and limited resources and expertise in labelling the data manually, as they provide location and event specific data with high accuracy. Improvements in accuracy are possible by integrating the raw data in deep learning, an approach that should be explored further.

Between a rock and a hard place: the privatization or preservation of the commons in Spain in the long 19th century

Abstract This text reviews the transformations of the commons in Spain in the long 19th century based on the notion of “bundles of rights”. The contention is that the process of change was prompted by the clashes between alternative models, beginning with privatization or preservation and culminating in a complex landscape of property rights. In terms of privatization, several alternatives were advocated and eventually implemented, depending on the social groups that promoted them and their balance of power. In stylized form, two options that while not necessarily incompatible stand in opposition: on the one hand, privatization in the form of large property units with the land concentrated in the hands of an elite of creditors and investors, and on the other, small plots involving broader social participation and greater access. In turn, the preservation of communal lands did not rule out the privatization of their use, in some cases in favor of large industrial companies in the timber, resin, and cork sectors, and on other occasions in the service of social inclusion policies through the distribution of plots for their cultivation by the rural proletariat.

Effects of weed management on soil metagenomic composition in cultivated chickpea fields

Abstract Non-chemical methods, including mechanical and manual weed management are important for improving crop yields and preserving soil microbial diversity. In Tunisia, chickpea cultivation uses a combination of these methods to suppress weeds. This study aimed to evaluate the impact of weeding practices on chickpea (Cicer arietinum L. cultivar REBHA) yield and soil microbial diversity. Field experiments were conducted at the Technical Center for Biological Agriculture in Essaida, Tunisia, using six plots with manual and no weeding treatments. Chickpea yield was measured, and soil samples were collected for metagenomic analysis. Floristic surveys identified 13 weed species, with Chenopodium album L., Rumex acetosa L., and Urtica dioica L. being the most dominant. Seed yield ranged from 23.2 to 26.2 qls/ha in non-weeded plots and from 25.1 to 30.1 qls/ha in weeded plots, showing an increase in yield (11.75%) with manual weeding.
Soil metagenomics revealed changes in bacterial community composition between the two treatments. The dominant phylum was Pseudomonadota, whose relative abundance increased from 24.88% in non-weeded plots to 34.76% in weeded plots. Alpha diversity indices showed lower species richness and diversity in weeded soils, with 62000 OTUs in weeded plots compared to 43202 OTUs in non-weeded plots. Betaproteobacteria and Alphaproteobacteria exhibited higher OTU counts in weeded soils. The Simpson diversity index was lower in non-weeded soils (0.025) than in weeded soils (0.075), indicating a more irregular microbial distribution in non-weeded plots. Thus, manual weeding improved chickpea yield and altered the soil bacterial community, increasing diversity in key microbial taxa. This study highlights the complex interaction between weed management practices and soil microbial ecosystems, which may influence crop productivity.

Impact of Zinnia elegans Cultivation on the Control Efficacy and Distribution of Aphidius colemani Viereck (Hymenoptera: Braconidae) against Aphis gossypii Glover (Hemiptera: Aphididae) in Cucumber Greenhouses.

This study aimed to evaluate the enhancement of A. gossypii control by A. colemani when Z. elegans was planted as a companion crop in cucumber greenhouses. The density and spatial distribution of A. gossypii and parasitized mummies were investigated across three treatment plots: (1) the simultaneous application of A. colemani and cultivation of Z. elegans (parasitoid-zinnia plot); (2) the application of A. colemani alone (parasitoid plot); and (3) a control plot (no application of both). A. gossypii maintained low densities in the parasitoid-zinnia plots, while its densities in the parasitoid plots initially decreased but rapidly increased thereafter. The spatial distribution patterns of A. gossypii and parasitized mummies showed similar trends across treatments. However, the parasitism rate of A. gossypii exhibited random distribution in parasitoid and control plots, while showing uniform distribution in the parasitoid-zinnia treatment. These results supported the idea that cultivating Z. elegans alongside cucumber could enhance the effectiveness of A. colemani as a biocontrol agent against A. gossypii, highlighting the importance of such companion planting in pest management strategies.

Addressing multiple facets of bias and uncertainty in continental scale biodiversity databases

The availability of biodiversity databases is expanding at unprecedented rates. Nevertheless, species occurrence data can be intrinsically biased and contain uncertainties that impact the accuracy and reliability of biodiversity estimates. In this study, we developed a reproducible framework to assess three dimensions of bias—taxonomic, spatial, and temporal—as well as temporal uncertainty associated with data collections. We utilized the vegetation plot data located in Europe, from sPlotOpen, an open-access database, as a case study. The metrics proposed for estimating bias include completeness of the species richness for taxonomic bias, Nearest Neighbor Index for spatial bias, and Pielou’s index for temporal bias. Additionally, we introduced a new method based on a negative exponential curve to model the temporal decay in biodiversity data, aiming to quantify temporal uncertainty. Finally, we assessed the sampling bias considering the influence of various spatial variables (i.e, road density, human population count, Natura 2000 network and topographic roughness). We discovered that the facets of bias and the temporal uncertainty varied throughout Europe, as did the different roles played by spatial variables in determining biases. sPlotOpen showed a clustered distribution of the vegetation plots, and an uneven distribution in sampling completeness, year of sampling and temporal uncertainty. The facets of bias were significantly explained mainly by the presence of Natura 2000 network and marginally by the human population count. These results suggest that employing an efficient procedure to examine biases and uncertainties in data collections can enhance data quality and provide more reliable biodiversity estimates.

On the analysis and deeper properties of the fractional complex physical models pertaining to nonsingular kernels.

This study solves the coupled fractional differential equations defining the massive Thirring model and the Kundu Eckhaus equation using the Natural transform decomposition method. The massive Thirring model is a dynamic component of quantum field theory, consisting of a coupled nonlinear complex differential equations. Initially, we study the suggested equations under the fractional derivative of Caputo-Fabrizio. The Atangana-Baleanu derivative is then used to evaluate the comparable equations. The results are significant and necessary for exploring a range of physical processes. This paper uses modern approach and the fractional operators in this situation to develop satisfactory approximations to the offered problems. The proposed approach combines the natural transform technique with the efficient Adomian decomposition scheme. Obtaining numerical findings in the form of a fast-converge series significantly improves the scheme's accuracy. Some graphical plot distributions are presented to show that the present approach is very simple and straightforward. We performed a fractional order analysis of assumed phenomena to demonstrate and validate the effectiveness of the future technique. The behaviour of the approximate series solution for several fractional orders is shown visually. Additionally, the nature of the derived outcome has been observed for various fractional orders. The derived results demonstrate how simple and efficient the proposed method is to apply for analysing the behaviour of fractionally-order complex nonlinear differential equations that arise in related fields of engineering and science.

Identification of key factors and mechanism determining arsenic mobilization in paddy soil-porewater-rice system

Arsenic (As) mobilization in paddy fields poses significant health risks, necessitating a thorough understanding of the controlling factors and mechanisms to safeguard human health. We conducted a comprehensive investigation of the soil-porewater-rice system throughout the rice life cycle, focusing on monitoring arsenic distribution and porewater characteristics in typical paddy field plots. Soil pH ranged from 4.79 to 7.98, while porewater pH was weakly alkaline, varying from 7.2 to 7.47. Total arsenic content in paddy soils ranged from 6.8 to 17.2 mg/kg, with arsenic concentrations in porewater during rice growth ranging from 2.97 to 14.85 μg/L. Specifically, arsenite concentrations in porewater ranged from 0.48 to 7.91 μg/L, and arsenate concentrations ranged from 0.73 to 5.83 μg/L. Through principal component analysis (PCA) and analysis of redox factors, we identified that arsenic concentration in porewater is predominantly influenced by the interplay of reduction and desorption processes, contributing 43.5 % collectively. Specifically, the reductive dissolution of iron oxides associated with organic carbon accounted for 23.3 % of arsenic concentration dynamics in porewater. Additionally, arsenic release from the soil followed a sequence starting with nitrate reduction, followed by ferric ion reduction, and subsequently sulfate reduction. Our findings provide valuable insights into the mechanisms governing arsenic mobilization within the paddy soil-porewater-rice system. These insights could inform strategies for irrigation management aimed at mitigating arsenic toxicity and associated health risks.

Assessing the strategic role of urban green spaces for habitat connectivity in multi-family residential plots

Urban green spaces are key for maintaining and restoring habitat connectivity within cities. Despite substantial investigations on the contribution to connectivity of different types of urban green spaces, the specific contribution of green spaces located in multifamily residential (MFR) plots has yet to be assessed. Estimating this contribution is crucial given the multiple roles fulfilled by these green spaces in urban planning. To achieve this goal, we focused on four taxa: the European hedgehog (Erinaceus europaeus), the Red squirrel (Sciurus vulgaris), forest passerine birds and moths. We assessed the potential habitat connectivity for each taxon across the metropolitan urban area of Lyon (France), with landscape graphs built using 1-metre resolution land cover maps. Considering the current state as a reference, we then designed five land cover change scenarios affecting habitat distribution in the MFR plots: (i) maximum and (ii) minimum theoretical connectivity (references), (iii) improve quality of existing green spaces, (iv) improve quantity of green spaces with sub-optimal quality and, (v) maximum restoration (management scenarios). The taxon- and scenario-specific impacts highlight the crucial contribution of private spaces to habitat connectivity. For all taxa, while the MFR only cover 8 % of the study area, connectivity would increase by up to 60 % if these plots were greened. In contrast, sealing these plots could reduce overall connectivity by up to 40 %. The interpolation of local connectivity metrics for each habitat patch and each MFR plot allowed us to identify the most relevant plots for urban greening. Because our approach can improve habitat connectivity at different scales, from neighbourhoods to entire urban areas, it could prove useful for landscape planning in most urban settings.

Anomalous thresholds in B → (P, V)γ* form factors

We study the effects of anomalous thresholds on the non-local form factors describing the hadronization of the light-quark contribution to B → (P, V)γ* transitions. Starting from a comprehensive discussion of anomalous thresholds in the triangle loop function for different mass configurations, we detail how the dispersion relation for ππ intermediate states is affected by contour deformations mandated by the anomalous branch points. Phenomenological estimates of the size of the anomalous contributions to the form factors are provided with couplings determined from measured branching fractions and Dalitz plot distributions. Our key finding is that anomalous effects are suppressed on the ρ(770) resonance, while off-peak the effects can become as large as O\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{O} $$\\end{document}(10%) of the full (light-quark-loop induced) non-local form factors. We comment on future generalizations towards higher intermediate states and the charm loop, outlining how the dispersive framework established in this work could help improve the non-local form factors needed as input for a robust interpretation of B → (P, V)ℓ+ℓ− decays.

Gamma-rays and X-rays spectrometries applied to evaluate soil redistribution

This work responds to the growing global demand for food, which requires improvements in agricultural production and sustainable management of natural resources. The focus is on soil erosion as a critical element in preserving agricultural productivity. From this perspective, the levels of radionuclides and chemical elements present in the soil, quantified through Gamma-Rays Spectrometry (GRS) and Energy Dispersive X-ray Fluorescence (EDXRF), were used to investigate soil redistribution over time. 27 soil samples ranging from 0 to 30 cm in depth were collected in an agricultural plot located in southern Brazil. Quantitative analysis indicated high mean concentrations of Fe (161 ± 7 gkg−1), Al (110 ± 17 gkg−1), Ca (2.6 ± 0.5 gkg−1), Mn (2.4 ± 0.3 gkg−1) and K (543 ± 165 mgkg−1) in comparison with the other detected elements. The quantification of 137Cs provided a mean inventory of 27 ± 17 Bqm−2. Using the proportional model, an estimated gross erosion rate of 28.2 tonha−1year−1 and a net soil deposition of 6.6 tonha−1year−1 were calculated. Therefore, a net soil loss of 21.6 tonha−1year−1 was experienced within the agricultural plot studied. The data set combination of both techniques with Principal Component Analysis (PCA) revealed correlations between the variables studied and the soil erosion dynamics. The PCA showed a tendency to separate the samples according to their sampling depth. Moreover, 137Cs behavior in soil proved to be similar to the behavior of elements found in fertilizers, like K. On the other hand, the individual influence of 137Cs was not enough to cause significant changes in the samples distribution in the scores plot, highlighting EDXRF as a promising technique to complement soil erosion studies.

Three-body unitary coupled-channel approach to radiative J/ψ decays and η(1405/1475)

Recent BESIII data on radiative J/ψ decays from ∼1010 J/ψ samples should significantly advance our understanding of the controversial nature of η(1405/1475). This motivates us to develop a three-body unitary coupled-channel model for radiative J/ψ decays to three-meson final states of any partial wave (JPC). Basic building blocks of the model are bare resonance states such as η(1405/1475) and f1(1420), and πK, KK¯, and πη two-body interactions that generate resonances such as K*(892), K0*(700), and a0(980). This model reasonably fits KSKSπ0 Dalitz plot pseudodata generated from the BESIII’s JPC=0−+ amplitude for J/ψ→γKSKSπ0. The experimental branching ratios of η(1405/1475)→ηππ and η(1405/1475)→γρ relative to that of η(1405/1475)→KK¯π are simultaneously fitted. Our 0−+ amplitude is analytically continued to find three poles, two of which correspond to η(1405) on different Riemann sheets of the K*K¯ channel, and the third one for η(1475). This is the first pole determination of η(1405/1475) and, furthermore, the first-ever pole determination from analyzing experimental Dalitz plot distributions with a manifestly three-body unitary coupled-channel framework. Process-dependent ηππ, γπ+π−, and πππ lineshapes of J/ψ→γ(0−+)→γ(ηππ), γ(γρ), and γ(πππ) are predicted, and are in reasonable agreement with data. A triangle singularity is shown to play a crucial role to cause the large isospin violation of J/ψ→γ(πππ). Published by the American Physical Society 2024

Influence of micro-addition of lanthanum on grain characteristics, mechanical properties, and corrosion behavior of CuAlNiMnLa shape memory alloy

The study investigated the grain size criteria, mechanical characteristics, and corrosion behavior of Cu-14Al-4.5Ni-0.7Mn shape memory alloy (SMA) with the micro-addition of 0.06 wt% Lanthanum (La). Using standard melting and casting procedures, the alloy compositions were melted at 1300 ℃ in an arc furnace with an argon atmosphere. The cast compositions without thermal treatment were machined and tested for physical properties including density and percentage porosity, corrosion behavior, and mechanical properties like hardness, ultimate tensile strength, yield strength, fracture strain, percentage elongation, specific strength, and fracture toughness. The average grain size, profile plot, and grain size distribution were all determined using ImageJ software. The microstructural observations revealed the presence of α-phase, β-phase, and intermetallic phases, including the coarse α+γ2 phase, which contributed to the improved characteristics. The inclusion of lanthanum resulted in a drop in the average grain size of the parent alloy from 9.25 μm to 6.08 μm, indicating a clear correlation between property improvement and microstructure refinement. The composition's tensile strength and yield strength increased with the La micro-addition by 22.14% and 20.31% respectively while the hardness value increased by 17.3%. The fracture strain of the modified composition increased by 20% compared to the unmodified composition while the percentage elongation increased by 7.7% and a 22.5% increase in fracture toughness was achieved. The modified CuAlNiMn SMA also showed a significant improvement in corrosion resistance to NaCl solutions which was so evident at 144 hours of the study for 0.5 M of NaCl solution and at 96 hours for 1.0 M of NaCl solution. The results showed that CuAlNiMn SMA with micro-addition of La had better physical, corrosion, and mechanical characteristics than unmodified CuAlNiMn alloys

Computer vision-based instantaneous speed tracking system for measuring the subtask speed in the 100-meter sprinter: Development and concurrent validity study

The 100-m sprint is one of the track events, and the pace of the runner can be measured using a variety of tools, such as a hand stopwatch, timing gate, laser device, radar device, photocell timing, etc. The data measured is the mean travel time. Nonetheless, monitoring an individual sprinter's instantaneous speed tracking is essential for assisting staff trainers in developing an appropriate training schedule for the individual sprinter. The purpose of this study was to construct a computer vision-based system for assessing the sprinting speed of the 100-m subtasks and also to investigate the concurrent validity of video analysis software among athletes. Five athletes participated in the research to determine its validity. Over the course of two trials, the sprinting pace of each participant's subtasks (a 100-m split to 10 m for each subtask) was measured. The application of the computer vision-based system to video analysis software was validated using the Pearson correlation coefficient. The agreement between the two measurement systems was quantified using Bland-Altman plots. The results revealed a significant relationship between the two systems and all 100-m subtask sprinting speeds (r = 0.961–1.000, p 0.0001). The Bland-Altman analyses indicated that the mean differences in 100-m subtask speeds were consistently close to zero, falling within the 95 % limits of agreement. The scatter plot distribution showed symmetry. The computer vision-based system proved to be a valid tool, suggesting its potential value in measuring and monitoring the 100-m subtask sprinting speed of athletes.

Statistical inference for microstate distribution in recurrence plots

Recurrence is an important property to unveil patterns in dynamical systems. The recurrence plot (RP) is a matrix that summarizes recurrence information from data sequences. Recently, a new approach to the RP have been developed to generalize the standard absence or occurrence of recurrences in the RP. The microstate concept was introduced to statistically characterize samples of any size in the RP. We explore in this paper the relation between microstates of different sizes in the RP. We distinguish two approaches: the top-bottom and the down-up analysis. In the first we have information from larger microstates to make inference about smaller ones, in the second the opposite. We establish analytical results that statistically estimate the microstate probabilities between different sample sizes. The analytical results for the normalized entropy were tested using two time series: a simple white noise case and a series from a logistic equation in the chaotic scenario. For both cases, the top-bottom and the down-up analytical relations were tested with good results. To depict the actual probability distributions, we used the Lorenz oscillator for both, the top-down and the bottom-up strategies, showcasing the limitations and perspectives for future works. We believe our results can open new theoretical paths in the RP analysis.

Reference range of placental growth factors at 11–14 weeks’ gestation in Indonesia

ObjectivesTo develop a reference chart for placental growth factor (PLGF) value during 11–14 weeks’ gestation in Indonesian population. MethodsThis was an observational study observing women in their first trimester. Maternal characteristics, biophysical tests, and serum PLGF levels were collected during the visit. PLGF Multiple of Median (MoM) was adjusted for maternal characteristics including age, parity, smoking habits, diabetes mellitus, weight, height, body mass index, gestational age, and crown-rump length (CRL) utilizing the linear regression analysis. Plot distributions of PLGF level and PLGF MoM adjusted to CRL were developed using logistic regression technique. ResultsOut of 2.062 consecutive women undergoing 11–14 weeks’ gestation ultrasound screening, the median of PLGF level and PLGF MoM were 50.38 pg/ml (1.09–265.20 pg/ml) and 1.00 (0.02–4.80), respectively. In the multivariate analysis, PLGF MoM was not significantly influenced by maternal factors such as age, parity, smoking habit, diabetes mellitus, height, weight, and BMI. The adjusted PLGF MoM reference chart according to the CRL was developed using quadratic linear regression. ConclusionPLGF levels at 11–14 weeks’ gestation were notably influenced by CRL but not by maternal characteristics. The usefulness of this parameter in combining with other established markers as a screening tool for the Indonesian population basis requires further investigation.

Sunflower inspired urban city pattern to improve solar energy utilization in low solar radiation countries

Cities consume a huge amount of energy to satisfy people’s necessities. Most of the existing city patterns do not consider passive energy solutions when planning. This study investigates the maximum available sunny areas for the buildings’ surfaces (rooftops and facades) generated in low solar radiation with long shadow length locations. This has been done by studying the orientation and distribution of the residential plots in the different urban panning patterns. For investigative purposes, a city model is planned according to the most common urban planning patterns, which are grid and radial patterns in addition to a newly proposed and novel sunflower urban planning pattern that mimics Mother Nature. The alternating distribution in the sunflower pattern allows the sun to reach every building in this pattern equally. Warsaw was selected as an example of low solar radiation and long shadow length city. The results show that the proposed sunflower pattern outperforms the grid and radial patterns by a percentage of 4% for the available sunny rooftop areas and a percentage of 12% for the available sunny facade areas.

The Tool for Assessing the Effectiveness of Land Consolidation

The main aim of the study was to develop a tool that automatically calculates the basic parameters describing the efficiency of land consolidation work, especially consolidation projects and analysis of the optimal location of parcels. Efficiency is usually determined by basic spatial parameters such as size, number and dispersion of plots. To calculate the spatial dispersion of parcels in a registration unit, the use of a convex envelope (convex hull) is proposed. This is one of the basic functions of a Geographical Information System (GIS). It provides a simple way to estimate the dispersion of land, taking into account its area and its belonging to a particular registration unit. The ModelBuilder application available in ArcGIS software was used to build the efficiency assessment tool. The tool was tested on three consolidation areas – Ilkowice, Rajsko-Niedzieliska-Szczurowa and Łukowa. The best results in terms of optimal distribution of plots were obtained on the Rajsko-Niedzieliska-Szczurowa site. In this case, the average area of plots increased more than threefold. The number of parcels in the entire site and in the registration units has more than threefold decreased. The average dispersion of plots in the units decreased here by almost four times. The other two sites did not score as well, but the analysis of the parameters indicates that there has been an improvement in the distribution of plots compared to the initial state. The average area of plots in Ilkowice increased by about 25% and in Lukowa by about 48%. The number of plots decreased in Ilkowice by about 25% and in Lukowa by about 48%. The average dispersion of plots in the units decreased in Ilkowice by 20% and in Lukowa by about 22%. It should be mentioned here that the Rajsko- -Niedzielska-Szczurowa site consisted exclusively of agricultural plots, so it was definitely easier to achieve such good results. The Ilkowice and Łukowa sites also contained developed plots, which were not consolidated.

RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification

When radar receives target echoes to form plots, it is inevitably affected by clutter, which brings a lot of imprecise and uncertain information to target recognition. Traditional radar plot recognition algorithms often have poor performance in dealing with imprecise and uncertain information. To solve this problem, a radar plot recognition algorithm based on adaptive evidence classification (RPREC) is proposed in this paper. The RPREC can be considered as the evidence classification version under the belief functions. First, the recognition framework based on the belief functions for target, clutter, and uncertainty is created, and a deep neural network model classifier that can give the class of radar plots is also designed. Secondly, according to the classification results of each iteration round, the decision pieces of evidence are constructed and fused. Before being fused, evidence will be corrected based on the distribution of radar plots. Finally, based on the global fusion results, the class labels of all radar plots are updated, and the classifier is retrained and updated so as to iterate until all the class labels of radar plots are no longer changed. The performance of the RPREC is verified and analyzed based on the real radar plot datasets by comparison with other related methods.

Volatile compound dynamics in oats solid-state fermentation: A comparative study of Saccharomyces cerevisiae A3, Lactococcus lactis 4355, and Lactobacillus plantarum 2329 inoculations

Fermentation is a longstanding method that enhances food quality and finds extensive food processing and preservation applications. This study comprehensively studied the impact of oats fermentation by Saccharomyces cerevisiae A3 and Lactococcus lactis 4355 (T1), Saccharomyces cerevisiae A3, and Lactobacillus plantarum 2329 (T2) on volatile-compounds using UHPLC-MS/MS. A total of 74 volatile compounds were found in control samples (YM), 81 in T1 samples, and 60 in T2 samples. T2 samples showed the highest hydrocarbons, esters, and phenols (25.7%, 2.26%, and 0.32%) compared with T1 (21.6%, 1.29%, and 0.19%) and YM samples (18.6%, 1.86%, and 0), respectively. Moreover, volcano, Z-score scatter plot distributions, and KEGG-path analysis indicated that different metabolic pathways in YM-T1 and YM-T2 models, where glycerophospholipid-metabolic pathways were the dominant in T1, while ABC transporters-pathways were the prominent in T2. These findings offer valuable insights for future advancements of novel oat products with enhanced functionality.

Research and application of Big data encryption technology based on quantum lightweight image encryption

Given the limitations of current classic image encryption algorithms and the unconditional security characteristics of quantum key distribution protocols, the author proposes an image encryption method based on quantum key distribution and pixel scrambling. The author first analyzed the security issues of quantum image encryption algorithms based on image scrambling methods, namely that image scrambling methods have periodicity, which can ensure that the image can be restored after scrambling. If an image cannot be guaranteed to return to its original state after performing scrambling operations, legitimate users cannot obtain the secret information in the original image, and image scrambling loses its original meaning; However, the periodicity of image scrambling methods not only ensures that legitimate users can decrypt images, but also provides convenience for attackers to steal original image information. Secondly, it is pointed out that when evaluating and analyzing quantum image encryption algorithms, the evaluation indicators should include two parts: One is performance analysis, which is the analysis of the network complexity of quantum circuits. In quantum computing, the network complexity of quantum circuits is usually represented by the number of quantum basic logic gates. The second is security analysis, which mainly includes key analysis (including key space size and key sensitivity analysis), statistical analysis (including pixel correlation, histogram analysis, information fusion, and scatter plot distribution density analysis). Finally, experimental simulations have shown that the NPCR values of the plaintext and ciphertext images of the three images tend to 100%. The encrypted image histogram is evenly distributed, with very weak pixel correlation and high pixel change rate and information entropy.