Yield Distribution Research Articles

Crop rotations and canola yields: Evidence from field‐level data in Western Canada

AbstractCanola (Brassica napus) acreage increased in Western Canada in recent years, leading to rotations with fewer break years between canola plantings. Field trials suggest that frequent plantings of canola reduce canola yields. However, there is considerable disagreement about the magnitude and persistence of these effects. We analyze the effect of rotational practices on canola yields in Saskatchewan using over 20 years of observational data, representing 61% of canola hectares in the province. We examine how the impact of rotations varies across time, soil zone, soil moisture conditions and the distribution of yields. We regress canola yields in Saskatchewan on the share of land that was planted with particular crops in previous years, using a battery of covariates and fixed effects to address potential bias in the model. After including these fixed effects, we cannot reject the hypothesis that there is no sample selection bias. We use an unconditional quantile estimator to investigate how rotations affect different deciles of the yield distribution. Our analysis confirms that crop rotations significantly influence canola yields, albeit more modest than field trials suggest. We find a 7.5% yield reduction when canola follows canola, compared to cereals, with this penalty persisting for 4 years but diminishing in magnitude with each additional year. The adverse effects of consecutive canola plantings are more pronounced in wetter regions and at lower yield deciles. Conversely, canola yields are higher when planted after pulse crops (as opposed to after cereal crops).

Modeling Sediment Yield with Current and Projected Climatic Scenarios in Andit Tid Watershed, Central Highland of Ethiopia

Our ability to engage in long-term land management solutions that will benefit both land and water users is made possible by our understanding of how climate change affects sediment yield. This study aimed to determine the spatiotemporal distribution of sediment yield in the Andit Tid watershed as well as simulate sediment yield under existing and anticipated climate scenarios. SWAT and Arc GIS 10.5 software were used to estimate and map the spatial distribution of sediment yield. The annual average estimated sediment yield of the watershed was found to be 17.9 t ha-1 yr-1. The R2 was found to be 0.62 and 0.72 during calibration and validation of sediment yield. The projected average sediment yield up to 2098 under the wettest scenario is 13.7 t ha-1 in RCP 4.5 and 16.1 t ha-1 in RCP 8.5, respectively. It was discovered that, in comparison to the current average sediment, the near future (2022–2060) sediment was equal to it in RCP 4.5 and decreased by 41% in RCP 8.5, whereas the far future (2061–2098) sediment grew by 20.4% in RCP 8.5 and decreased by 35% in RCP 4.5. Out of the projected 76 years, 21 and 23 years showed positive deviations from the mean of the existing sediment yield under RCP 4.5 and 8.5, respectively. While in the driest scenario, the projected sediment yield was lower than the current rate, which was about 4 t ha-1 in both RCPs. In both current and future climate scenarios, the northeastern, eastern, and western regions were contributing to the higher sediment yield in the watershed. Most of these watershed hotspot regions were situated on farmed land with a slope of more than twenty percent and active gullies. When developing and executing management solutions in the areas that are severely impacted, the watershed community and decision-makers are recommended to make use of the spatial distribution map. It is also necessary to take steps to lessen the likelihood that the emission scenarios that result in RCP 8.5 will occur.

Impact of tensor forces on quasifission product yield distributions

Impact of tensor forces on quasifission product yield distributions

The climatic impacts on rice yield in the Indian state of Odisha: an application of Just-Pope production function and quantile regression.

The impacts of climate change on Indian agriculture are well documented. However, there is a dearth of research addressing the inter-regional diversities in the impacts. Furthermore, existing studies are mostly restricted to the impacts on mean agricultural yield, overlooking the impacts on yield variability. This study investigates climatic impacts on rice yield in Odisha, a coastal Indian state, employing district-level panel data from 1995 to 2017. This study uses the Feasible Generalized Least Squares (FGLS) and quantile regression approaches to estimate how climatic impacts are realized on mean yield, yield variability, and conditional quantiles of yield distribution. The use of the agro-climatic zone level dummies empowers the study to account for local weather and soil conditions. The results reveal substantial heterogeneity in the climatic impacts across agro-climatic zones. A marginal increase in the maximum temperature reduces rice yield by 279-325kg/ha across different agro-climatic zones, largely constituting the state's coastal region, but increases yield by 340-766kg/ha across the zones lying in the western region. Conversely, an increase in minimum temperature increases rice yield by around 211kg/ha in the coastal region, but reduces by 333-744kg/ha in the western region. In addition, an increase in precipitation reduces yield by 0.318 kg/ha in some parts of the coastal region, but increases yield by 0.268 0.881 kg/ha across other regions. Similar heterogeneity is also identified across conditional quantiles of yield distribution. The heterogeneous impacts call for strategic policy intervention specific to zones and quantiles.

Exploring Fission Dynamics through Fission Fragment Spectroscopy

Abstract Fission Fragment Spectroscopy (FFS) measurement technique has been utilized to measure the relative isotopic yield distributions of the even-even correlated fission fragment nuclei produced from 236U* at two different values of excitation energies (E ex ). The fissioning compound nucleus, 236U* was populated at E ex = 6.5 and 21.5 MeV through two different sets of experiments by using the reactions, 235U(n th ,f) and 232Th(α,f), respectively. The experimentally measured relative isotopic yield distributions were further used to obtain the corresponding mass yield distributions. The extracted mass yield distributions of 236U* indicates the transition from asymmetric distribution to bimodal distribution with increase in the values of E ex from 6.5 to 21.5 MeV. The experimental mass yield distribution pattern for the reaction, 232Th(α,f) at E ex = 21.5 MeV could be fitted well through three Gaussian fits as per the prescription based on the Multimodal Random-Neck Rupture Model (MM-RNRM).

Solar Wind Ion Sputtering from Airless Planetary Bodies: New Insights into the Surface Binding Energies for Elements in Plagioclase Feldspars

Our understanding of the ion-sputtering contribution to the formation of exospheres on airless bodies has been hindered by the lack of accurate surface binding energies (SBEs) of the elements in the various mineral and amorphous compounds expected to be on the surfaces of these bodies. The SBE for a given element controls the predicted sputtering yield and energy distribution of the ejecta. Here, we use molecular dynamics computations to provide SBE data for the range of elements sputtered from plagioclase feldspar crystalline end members, albite and anorthite, which are expected to be important mineral components on the surfaces of the Moon and Mercury. Results show that the SBE is dependent on the crystal orientation and the element’s coordination, meaning multiple SBEs are possible for a given element. Variation in the SBEs among the different surface positions has a significant effect on the predicted yield and energy distribution of the ejecta. We then consider sputtering by H, He, and a solar wind mixture of 96% H and 4% He. For each of these cases, we derive best-fit elemental SBE values to predict the ejecta energy distribution from each of the (001), (010), and (011) cleavage planes. We demonstrate that the He contribution to the sputtering yield cannot be accounted for by multiplying the 100% H results by some factor. Lastly, we average our results over all three possible lattice orientations and provide best-fit elemental SBE values that can be easily incorporated into sputtering yield models.

Co-pyrolysis of coal-derived sludge and low-rank coal: Thermal behaviour and char yield prediction

Coal-derived sludge, a solid waste produced by the coal industry, offers potential opportunities for resource recovery due to its high organic matter. However, its products face challenges related to low utilization efficiency and economic value. Effective and clean treatment of coal-derived sludge is essential for sustainable development. Herein, we studied the co-pyrolysis treatment of coal-derived sludge and low-rank coal at different temperatures (500 °C−900 °C) and pretreatment methods (mechanical mixing and hydrothermal co-treatment). The co-pyrolysis of sludge and coal could increase the pyrolysis char yield and H2 yield, as well as reduce CO2 emissions. The hydrothermal co-treatment significantly improved the cleanliness of the co-pyrolysis treatment. Then we conducted a comprehensive analysis of the properties of the pyrolysis char using different characterization techniques. In order to better evaluate the distribution of co-pyrolysis product yield, six machine learning models were developed to predice co-pyrolysis char yield. The best model-predicted values showed excellent predictive performance when compared to the experimental values at high pyrolysis temperatures (≥700 °C). This study provided a new perspective on the resource utilization of coal-derived sludge and low-rank coal.

Measurement of fission product yields in the quasi-mono-energetic neutron-induced fission of 238U

The cumulative yield of the fission products within the mass range of 83–117 and 123–153 have been measured in the 6.61and 10.92 MeV quasi-mono-energetic neutron-induced fission of 238U by using an off-line γ-ray spectrometric technique. The neutron beams were obtained from the 7Li(p,n) reactions with the proton energies of 11 and 18.8 MeV. The mass chain yields were obtained from the cumulative yields by using charge distribution correction. The peak-to-valley (P/V) ratio, the average value of light mass (⟨AL⟩), heavy mass (⟨AH⟩) and the average number of neutrons (<ν>) were obtained from the mass yield data. The data in the 238U(n, f) reaction from the present work and literature at various energies were compared with the similar data in the 238U(γ, f) reaction and following observations were obtained. (i) In both the reactions, the mass yield distributions are double humped. (ii) The yield of fission products for A = 133–134, A = 138–139, and A = 143–144 and their complementary products are higher than those of other fission products due to the nuclear structure effect. (iii) The yield of symmetric product increases and thus the peak-to-valley (P/V) ratio decreases with excitation energy. (iv) With the increase of excitation energy, the <ν> vale increases in a similar way in both the reactions. (v) The changing trend of ⟨AL⟩ and ⟨AH⟩ values with the increase of excitation energy are entirely different in between the two reactions.

Understanding cold stress response mechanisms in plants: an overview.

Low-temperature stress significantly impacts plant growth, development, yield, and geographical distribution. However, during the long-term process of evolution, plants have evolved complicated mechanisms to resist low-temperature stress. The cold tolerance trait is regulated by multiple pathways, such as the Ca2+ signaling cascade, mitogen-activated protein kinase (MAPK) cascade, inducer of CBF expression 1 (ICE1)-C-repeat binding factor (CBF)-cold-reulated gene (COR) transcriptional cascade, reactive oxygen species (ROS) homeostasis regulation, and plant hormone signaling. However, the specific responses of these pathways to cold stress and their interactions are not fully understood. This review summarizes the response mechanisms of plants to cold stress from four aspects, including cold signal perception and transduction, ICE1-CBF-COR transcription cascade regulation, ROS homeostasis regulation and plant hormone signal regulation. It also elucidates the mechanism of cold stress perception and Ca2+ signal transduction in plants, and proposes the important roles of transcription factors (TFs), post-translational modifications (PTMs), light signals, circadian clock factors, and interaction proteins in the ICE1-CBF-COR transcription cascade. Additionally, we analyze the importance of ROS homeostasis and plant hormone signaling pathways in plant cold stress response, and explore the cross interconnections among the ICE1-CBF-COR cascade, ROS homeostasis, and plant hormone signaling. This comprehensive review enhances our understanding of the mechanism of plant cold tolerance and provides a molecular basis for genetic strategies to improve plant cold tolerance.

Hydrothermal co-carbonization of medium-density fiberboard with N-rich compounds to produce N-containing compounds and N-doped biochar: Product distribution, nitrogen transformation pathway and electrochemical performance

High-value utilization of waste resources has received widespread attention. In this study, N- containing chemicals (NCCs) and nitrogen-enriched hydrochars were prepared by co-hydrothermal carbonization (Co-HTC) of waste medium-density fiberboard (MDF) and various nitrogen carriers. The influence of the nitrogen carrier type (chitosan, urea, or melamine) and the MDF: nitrogen carrier mass ratio on yield and production distribution were investigated. The formation mechanism and possible reaction pathways of NCCs in bio-oil and N-doped biochar were elucidated, and the electrochemical performance of N-rich hydrochar as a precursor for supercapacitor materials was explored. The results indicated that the introduction of an ammonia source during hydrothermal carbonization obviously increased the NCC content via the Maillard reaction and decreased the hydrochar yield, resulting in structures disordered and poor microporosity. The introduction of chitosan significantly promoted pyridine (35.50 %) and hydrochar (36.95 %) generation owing to the nitrogen fixation effect (N: 6.27 ∼ 15.56 %). Urea addition facilitated the formation of NCCs (89.92 %) and imidazoles/pyrazines (39.46 %). The addition of melamine, which has the most amino functional groups, significantly increased aniline compound formation. Moreover, the activated hydrochar derived from the ammonia source Co-HTC exhibited great electrochemical performance, and the prepared electrode material derived from MDF: chitosan = 1:5 achieved highest reversible specific capacitance of 174.5F/g at 0.5 A/g and 96.46 % initial capacitance retention after 10,000 cycles at 10 A/g due to developed mesoporosity, high specific surface area and enriched N/O functional groups. This study provides a novel sustainable strategy for the efficient and high-value utilization of waste MDF and improved the economic viability of MDF biorefineries.

Long-term rice cultivation enhances root development and yields by improving the structural properties of soil aggregates in saline–alkaline environments

Rice cultivation has the ability to improve saline soils. However, the effects of long-term rice cultivation on saline soil chemistry, salt ions, root characteristics, and aggregate formation remain unclear. In this study, the impact of different planting durations (1, 3, 5, 8, and 10 years) on the spatial and temporal transport of soil salts, soil chemical properties, distribution and stability of aggregates, root characteristics, and yields, were assessed. Long-term rice cultivation reduced soil pH, exchangeable sodium percentage (ESP), and EC in the 0-60cm soil layer compared to 1Y (5.45%, 61.57%, and 81.87% reduction in topsoil (0-20cm) and 8.54%, 72.82%, and 71.94 in subsoil (20-60cm), respectively). However, the soil organic matter (OM), alkaline nitrogen (AN), phosphorus (AP), and potassium (AK) increased (217.09%, 90.18%, 89.23%, and 179.18% increase in topsoil and 223.72%, 81.24%, 174.28%, and 172.57% increase in subsoil, respectively). Additionally, the Cl-, K+, and Na+ in the soil gradually leached downward with the increase in the duration of rice cultivation (55.87%、36.08%、59.80%). Simultaneously, the increased duration markedly elevated the soil macroaggregate content (11.43%-20.04% by dry-sieving and 53.48%-288.09% by wet-sieving), clayey grain content (59.17%-198.33%), and soil aggregate stability, especially for 8Y and 10Y. The improved soil structure and root characteristic under long-term rice cultivation conditions increased the yield (28.89-54.81%). Partial least squares path model displayed that rice cultivation affected the aggregate stability, root characteristics, and rice yield via the corresponding chemical properties (pH, EC, and ESP), nutrient contents (AN, AP, AK, and SOM), and salt ion contents (Cl-, K+, and Na+). These findings are critical to understanding aggregate formation in saline soils.

Harvesting Light: The Interrelation of Spectrum, Plant Density, Secondary Metabolites, and Cannabis sativa L. Yield

The approaching legalisation and associated increasing demand for medicinal and recreational Cannabis sativa L. will lead to a growing relevance for lighting systems designed for Cannabis sativa L. The interplay between plant density, light spectrum, light distribution, yield, and secondary metabolite distribution within the plant has not yet been studied. To fill this knowledge gap, a CBD-dominant Cannabis sativa L. strain was grown in a greenhouse experiment with two plant densities (2.66 and 12 plants −1 m−2) under two different light spectra. The chosen light spectra were two LED fixtures, Solray385 (SOL) and AP67, with an R: FR ratio of 12.9 and 3.7, respectively. The results indicated that light-induced effects on individual plants can be transferred to the plant stock. A low R: FR ratio induced a 16% increase in dry flower yield in the last ten days of flowering, while a change in the light spectrum could increase the potential maximum plant density per square metre. The two spectra did not affect (CBD + CBDA) yield, as a lower flower yield compensated for a higher concentration. CBDA concentration was not significantly affected by plant density. In contrast, the higher density led to an increased total cannabidiol concentration (CBD + CBDA) and altered the distribution of terpenes. Here, the light distribution over the plant stock is particularly decisive, as a more homogenous illumination led to an increased terpene concentration of up to 41%. A Photon Conversion Efficacy (PCE) of 0.05 g mol−1 under SOL and 0.06 g mol−1 under AP67 was achieved. Plants in the centre under the highest light intensity of 1200 PAR showed up to 48% reduced efficacy. These results strongly suggest that light intensity needs to be fine-tuned to the cultivation system to prevent a reduction in efficacy, resulting in yield and quality losses.

Winter Wheat Yield Estimation by Fusing CNN–MALSTM Deep Learning with Remote Sensing Indices

A rapid and accurate determination of large-scale winter wheat yield is significant for food security and policy formulation. In this study, meteorological data and enhanced vegetation index (EVI) were used to estimate the winter wheat yield in Henan Province, China, by constructing a deep learning model. The deep learning model combines CNN feature extraction and makes full use of the sequence data processing capability of the LSTM and a multi-head attention mechanism to develop a novel CNN–MALSTM estimation model, which can capture the information of input sequences in different feature subspaces to enhance the expressiveness of the model. A CNN–LSTM baseline model was also constructed for comparison. Compared with the baseline model (R2 = 0.75, RMSE = 646.53 kg/ha, and MAPE = 8.82%), the proposed CNN–MALSTM model (R2 = 0.79, RMSE = 576.01 kg/ha, MAPE = 7.29%) could more accurately estimate the yield. Based on the cross-validation with one year of left-out data and the input of the fertility period by fertility period to explore the sensitivity of the model to data from different fertility periods to the final yield, an annual yield distribution map of Henan Province was constructed. Through cross-validation, the stability of the model in different years was assessed. The results showed that the model could obtain the best prediction of the yield approximately 20 days in advance. In terms of the spatial distribution of the yield in Henan Province on a yearly basis, the estimated yield showed an overall uptrend from west to east, consistent with the trend in the statistical yearbook of the yield for Henan Province. Thus, it can be concluded that the proposed CNN–MALSTM model can provide stable yield estimation results.

Development of a novel computational technique to create DNA and cell geometrical models for Geant4-DNA

BackgroundThis study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve. MethodsA Python-based tool named “complexDNA” was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the “molecularDNA” Geant4-DNA example. ResultsSimulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results. ConclusionsThis work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The “complexDNA” tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model’s accuracy.

Validation of QTLs associated with corn borer resistance and grain yield: implications in maize breeding.

Validations of previously detected quantitative trait loci (QTLs) to assess their reliability are crucial before implementing breeding programs. The objective of this study was to determine the reliability and practical usefulness of previously reported QTLs for resistance to stem tunneling by the Mediterranean stem borer (MSB) and yield. These authors used approximately 600 recombinant inbred lines (RILs) from a multiparent advanced generation intercross (MAGIC) population to map QTL using a genome-wide association study (GWAS) approach. We identified RILs situated at the extremes of resistance and yield distributions within the whole MAGIC, and those QTLs were evaluated per se and crossed to a tester (A638) using lattice designs. In each set, a significant single-nucleotide polymorphism (SNP) was considered validated if (1) the same SNP was associated with the trait with a p-value < 0.02, or (2) within a ±2-Mbp interval, an SNP associated with the trait exhibited a p-value < 0.02 and demonstrated linkage disequilibrium (r2 > 0.2) with the SNPs previously reported. The novel QTL validation approach was implemented using improved experimental designs that led to higher heritability estimates for both traits compared to those estimated with the whole MAGIC population. The procedure used allowed us to jointly validate several QTL and to ascertain their possible contribution to hybrid improvement. Specifically, nearly three-quarters of the QTLs for tunnel length were confirmed. Notably, QTLs located in the genomic region 6.05-6.07 were consistently validated across different sets and have been previously linked to resistance against stalk tunneling in various mapping populations. For grain yield, approximately 10 out of 16 QTLs were validated. The validation rate for yield was lower than for tunnel length, likely due to the influence of dominance and/or epistatic effects. Overall, 9 out of 21 QTLs for tunnel length and 6 out of 17 QTLs for grain yield identified in our previous research were validated across both validation sets, indicating a moderate genetic correlation between per se and testcross performance of inbred lines. These findings offer insights into the reliability of QTL and genomic predictions, both derived from assessments conducted on the entire MAGIC population. Genomic predictions for tunnel length based on inbred line evaluations could be useful to develop more resistant hybrids; meanwhile, genomic prediction for yield could only be valid in a homozygous background.

Extreme rainfall and soil water consumption differences increase yield shedding at lower fruiting branches, reducing cotton water productivity under different sowing dates

Improvement of cultivated cotton adaptability to extreme climate events under climate change promotes sustainable cotton production. Extreme rainfall leads to a significant decrease in cotton yield, which may be related to changes in soil water consumption (SWC) and the vertical distribution of yield, but relevant research is still scarce. Here, a two-year cotton sowing date experiment was conducted in which geostatistics, sensor technology, the spatial grid method, and principal component analysis were combined to analyze cotton utilization of soil water during extreme rainfall (2021) and normal (2022) years. The reasons for cotton yield reduction under extreme rainfall and strategies to improve cotton production adaptability to extreme rainfall were discussed. Under extreme rainfall, the morphogenesis and reproductive organ development of cotton were inhibited. The accumulation of SWC and its relationship with the biomass accumulation of cotton on different sowing dates under extreme rainfall exhibited nearly opposite characteristics to those in a normal year. Simultaneously, the two-year yield showed the opposite trend with the change in sowing date. There existed a trade-off strategy for the vertical distribution (i.e., on the upper, middle and lower fruiting branches) of cotton yield. Extreme rainfall reduced the yield at lower fruiting branches and increased the boll-forming rate of the upper fruiting branches, which was closely related to seed cotton yield, lint yield and water productivity (WP). Optimizing the cotton sowing date (early sowing should be appropriate in this study) may improve the adaptability of cotton production under extreme rainfall, but further long-term studies are needed. This study highlights the critical practice of climate-smart agriculture and has reference value for the sustainable development of cotton production.

Investigations on the effect of kaolin catalyst on the yield of various products obtained from pyrolysis of low-density polyethylene (LDPE) wastes and reaction kinetics.

The pyrolysis characteristics of low-density polyethylene (LDPE) wastes were investigated in a batch pyrolyzer in the temperature range of 550-650°C for a varying heating rate (5, 10, 15, 20, and 25°C/min) alone and using kaolin catalyst (10, 15, and 20% w/w). The yield distribution of various products under varying operating conditions was investigated, and the corresponding favourable conditions for maximum yield of pyrolytic oil (PO) were identified. The possible effect of the catalyst on pyrolysis kinetics was explored by extracting activation energies from the TGA experiments. The various model-free iso-conversion methods estimated the activation energy of 162-166kJ/mol during thermal degradation of LDPE, while it shifted to a lower range (138-145kJ/mol) on catalytic treatment. The catalytic pyrolysis with a 20% (by mass) catalyst in a batch pyrolyzer provided the maximum PO yield with the least solid residue at 600°C using a heating rate of 20°C/min, while the temperature of 600°C with 10% catalyst showed the least liquid product with more solid residue. The presence of a catalyst improved the oil quality with transparency and lower viscosity due to lighter hydrocarbons and higher aromatic content. The FTIR analysis detected various organic groups-alkanes, alkenes, cyclic, and aromatics in the oil. GC tests of gaseous products confirmed the gases like hydrogen, propane, butane, and propylene. The present study aims to provide technical know-how for the effective utilization of LDPE wastes towards clean energy sources and create a plastic-free green environment.

Production of Ag nanowires with high yield and narrow size distribution by promoting nucleation through hot injection and their application to disposable paper electrodes

The polyol method has been the most commonly used technique for fabricating silver nanowires (Ag NWs), wherein additive reagents facilitate precise control over their morphology. In this work, we introduced a straightforward approach to synthesize Ag NWs with minimal impurities and uniform diameter by using hot injection method. The underlying mechanism and final product are evaluated, and the scalable process was optimized to achieve a high yield (∼87.8 %). It was found that the hot injection of a Ag precursor at 170 °C significantly accelerated the reduction of Ag ions. The issue of the uniformity of Ag NWs was addressed by adding an organic halide to control the nucleation rate of Ag. The resulting Ag NWs solution was used to impregnated cellulose paper, forming an enhanced electrical network compared to other substrates. Given the low commercial cost of paper, this approach holds significant potential for widespread use in disposable electrodes. Furthermore, after subjecting the fabricated paper electrodes to various forms of damage, the connected LED bulbs consistently maintained their brightness. This demonstrates the network stability and suitability of these electrodes for flexible applications.

Understanding scale effects and differentiation mechanisms of ecosystem services tradeoffs and synergies relationship: A case study of the Lishui River Basin, China

Understanding the scale effect of relationships among ecosystem services (ESs) and the factors influencing these relationships, is vital for sustainable management of ESs. Previous research has focused less on multiple scale units, and the driving mechanisms behind ESs interactions remain unclear. Therefore, in this study, we assessed the spatial distribution of water yield (WY), water purification (WP), and soil conservation (SC) across four spatial scales (3 km × 3 km grid, 5 km × 5 km grid, sub-watershed, and county scales) in the Lishui River Basin of China during 2020. Using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, geographical weighted regression, and Pearson correlation analysis, we examined tradeoffs and synergies among these ESs at various scales. Additionally, we employed a geographic detector to analyze the reactions and scale effects among these tradeoffs/synergies and social-ecological factors. Our findings revealed the following: (1) Significant spatial heterogeneity in ESs was observed in the basin. The WY decreased from west (2511.65 mm) to east (890.06 mm), with high WP values concentrated in the eastern part, and high SC values (8.30 × 105 t/hm2) found in densely forested and grassland areas surrounding water bodies. Forested and cultivated lands were key contributors to ESs in the basin. (2) Across the four investigated scales, tradeoffs or synergies between the same ESs becoming more pronounced as the scale increased. Notably, most ES relationships displayed their strongest synergies at the county scale, with certain spatial areas demonstrating change in interaction directions. (3) The explanatory power of single- or double-factor interactions increased with scale. ESs interactions were found to be closely linked to climatic factors, as well as topographic features (including slope gradient and elevation), with precipitation exhibiting relatively high explanatory power. The interaction of natural and social factors significantly outweighed the combined interaction of dual social factors. This indicated that socio-ecological factors, especially climate and topography, jointly influenced the intensity and direction of ES tradeoffs/synergies. Scale effects arose from the “peak cutting and valley filling” phenomenon during scale transitions. These insights hold significant value for guiding hierarchical management strategies for regional ESs and informing decisions regarding resource allocation.

Post-Neutron Mass Yield Distribution in the Epi-Cadmium Neutron-Induced Fission of 235U

Cumulative and independent yields of various fission products within the mass ranges of 78 to 117 and 123 to 155 have been measured in the epi-cadmium reactor neutron-induced fission of 235U by using an off-line gamma-ray spectrometric technique. The average neutron energy <En> of the epi-cadmium reactor spectrum is 1.9 MeV. From the cumulative yields, post-neutron mass chain yields were obtained by applying the charge distribution correction. In the mass yield distribution, values of the full-width at tenth-maximum of light and heavy mass wings, average light mass <AL> and heavy mass <AH>, and average number of neutrons <ν> were obtained. The peak-to-valley ratio in the epi-cadmium neutron-induced fission of 235U was obtained for the first time. The present data in the 235U(n,f) reaction were compared with the literature data in the 235U(nth,f) reaction to examine the role of excitation energy on the mass yield distribution parameters and nuclear structure effect. The role of the standard I and standard II asymmetric modes of fission was also discussed.