Distribution Of Scatterers Research Articles

High-quality agricultural development in the central China: Empirical analysis based on the Dongting Lake area

High-quality agricultural development constitutes the primary point for forthcoming agricultural and rural endeavors. This study aimed to analyze the characteristics and obstacle factors of the high-quality agricultural development in central China, and the Dongting Lake area was taken as a case. Statistical data, land use data, and other data were adopted, and GIS spatial analysis and mapping technologies, obstacle model, and entropy weight method were used. The research results indicated that: 1) The comprehensive index has increased from 0.4290 in 2010 to 0.4717 in 2020. The change rates of the subsystem ranked from the highest to the lowest were as follows: cultural construction (36.25 %), ecological environment (15.18 %), social security (4.42 %), and material output (2.63 %). 2) The composite index has changed from higher in the west and lower in the east to a unconspicuous spatial difference. The material production index has shifted from higher in the north and lower in the south to a scattered distribution. The social security index has changed from higher in the west and lower in the east to higher in the northwest southeast and lower in the centre. The ecological environment index was higher in the west and lower in the east. The cultural construction index was higher in east and west and lower in the centre. 3) The top 4 obstacle factors were the high-quality development platforms, the agricultural driving force of per cultivated land, the number of agricultural geographical indication and the grain yield of per cultivated land. At the same time, the material output was the biggest obstacle. It is recommended to focus on the agricultural cultural resources in the eastern and western parts. This study can provide guidance and methodological references for similar studies, as well as scientific references for the sustainability of agriculture and optimization of related policies.

Mechanism and interaction of alkaline-earth metal migration induced ash transformation and carbon structure evolution for single coal particle high-temperature gasification

The current study focused on alkaline-earth metal migration induced ash transformation and carbon structure evolution for single coal particle high-temperature gasification, with visualization experiments and surface analysis techniques. The alkaline earth metals were found to aggregate to the peripheral reaction surface, while the rest remained in the initial scattered distribution. A migration index was defined and reached an extreme value in the middle reaction stage and increased with temperature, especially for the Ca element and followed by Mg. Raman spectra show the aggregation of Ca on the particle surface disrupted the carbon structure, leading to an increase in the disordered carbon content and improving the char reactivity. The aggregation behavior led to mineral transformation and melting to a liquid slag layer on the particle surface as a eutectic. Finally, a mechanism of the aggregation behavior of ionic Ca on a single particle scale was proposed in this study.

Data Complexity: A New Perspective for Analyzing the Difficulty of Defect Prediction Tasks

Defect prediction is crucial for software quality assurance and has been extensively researched over recent decades. However, prior studies rarely focus on data complexity in defect prediction tasks, and even less on understanding the difficulties of these tasks from the perspective of data complexity. In this article, we conduct an empirical study to estimate the hardness of over 33,000 instances, employing a set of measures to characterize the inherent difficulty of instances and the characteristics of defect datasets. Our findings indicate that: (1) instance hardness in both classes displays a right-skewed distribution, with the defective class exhibiting a more scattered distribution; (2) class overlap is the primary factor influencing instance hardness and can be characterized through feature, structural, and instance-level overlap; (3) no universal preprocessing technique is applicable to all datasets, and it may not consistently reduce data complexity, fortunately, dataset complexity measures can help identify suitable techniques for specific datasets; (4) integrating data complexity information into the learning process can enhance an algorithm’s learning capacity. In summary, this empirical study highlights the crucial role of data complexity in defect prediction tasks, and provides a novel perspective for advancing research in defect prediction techniques.

Evaluation of Scatterer Parameters From Ultrasound Scattering Models Taking Into Account Scattering From Nuclei and Cells of Cell-Pellet Biophantoms and Ex Vivo Tumors.

The Quantitative Ultrasound backscatter coefficient provides the capability to evaluate tissue microstructure parameters. Tissue-based scatterer parameters are extracted using ultrasound scattering models. It is challenging to correlate ultrasound scatterer parameters of tissue structures from optical-measured histology, possibly because of inappropriate scattering models or the presence of multiple scatterers. The objective of this study is to pursue the quantification of pertinent scatterer parameters with scattering models that consider ultrasound scattering from nuclei and cells. The concentric sphere model (CSM) and the structure factor model adapted for two types of scatterers (SFM2) are evaluated for cell-pellet biophantoms and ex vivo tumors of four cell lines: 4T1, JC, LMTK, and MAT. The structure factor model (SFM) was used for comparison. CSM and SFM2 provided scatterer parameters closer to histology (lower relative errors) for nucleus and cell radii and volume fractions than SFM but were not always accompanied by lower dispersion of the scatterer distribution (lower coefficient of variation). CSM and SFM2 quantified cell and nucleus radius and volume fraction parameters with lower relative error compared to SFM. For tumors, CSM provided better results than SFM2.

Driving Factors and Trade-Offs/Synergies Analysis of the Spatiotemporal Changes of Multiple Ecosystem Services in the Han River Basin, China

Uncovering the trade-offs and synergy relationship of multiple ecosystem services (ESs) is important for scientific ecosystem management and the improvement of ecological service functions. In this study, we investigated the spatiotemporal changes of four typical ES types (i.e., water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ)) from 2001 to 2020 in the Han River Basin (HRB). Meanwhile, the trade-offs and synergies between paired ESs and the socioecological drivers of these ESs were further explored. The results showed that grassland, cropland, and bare land decreased by 12,141.3 km2, 624.09 km2, and 22.1 km2 during the study period, respectively, which can be attributed to their conversion to forests in the HRB. Temporally, the WY, CS, and SC all showed a continuously increasing trend. Spatially, WY and HQ exhibited bipolar clustering characteristics, with WY exhibiting low-value clustering in the upstream and high-value clustering in the downstream, while CS showed the clustering characteristics of a scattered distribution of cold and hot spots from 2001 to 2020. The spatial patterns of aggregation locations in CS and HQ were relatively similar, with clusters of higher ES values mainly distributed in the western and central regions and clusters of lower ES values mainly located in the eastern and southeastern regions, while the aggregation of WY was spatially concentrated. Overall, the CS showed a significant positive correlation with HQ, but a significant negative correlation with WY. Spatially, WY and HQ, CS, and SC showed a substantial trade-off relationship in the northwest and southeast parts of the study area, while HQ, CS, and SC mainly exhibited a synergistic relationship in most parts of the study area. Slope and temperature had high influencing factor coefficients on multiple ESs; the mixed effect of terrain and natural factors was significantly greater than the impact of a single factor on ESs, and terrain factors played an essential role in the changes in ESs. The findings can provide technical and theoretical support for integrated scientific ecosystem management and sustainable development at the local scale.

Propagation of elastic waves in correlated dispersions of resonant scatterers.

The propagation of coherent longitudinal and transverse waves in random distributions of spherical scatterers embedded in an elastic matrix is studied. The investigated frequency range is the vicinity of the resonance frequencies of the translational and rotational motion of the spheres forced by the waves, where strong dispersion and attenuation are predicted. A technique for making samples made of layers of carbide tungsten beads embedded in epoxy resin is presented, which allows control of the scatterers distribution, induce short-range positional correlations, and minimize the anisotropy of samples. Comparison between phase velocity and attenuation measurements and a model based on multiple scattering theory (MST) shows that bulk effective properties accurately described by MST are obtained from three beads layers. Besides, short-range correlations amplify the effect of mechanical resonances on the propagation of longitudinal and transverse coherent waves. As a practical consequence, the use of short-range positional correlations may be used to enhance the attenuation of elastic waves by disordered, locally resonant, elastic metamaterials, and MST globally correctly predicts the effect of short-range positional order on their effective properties.

Design and Application of a Gas Diffusion Electrode (GDE) Cell for Operando and In Situ Studies.

Presented here is an electrochemical three-electrode Gas Diffusion Electrode (GDE) cell tailored for operandoand in situ investigations of electrocatalytic processes, with a particular focus on X-ray scattering studies. The optimized cell is engineered to accommodate the minimal sample-detector distances requisite for comprehensive X-ray total scattering investigations. An in-depth understanding of catalytic processes requires their study under 'working' conditions. Configured as a flow-cell, the setup therefore enables the examination of electrocatalysts under high current densities and associated gas evolution phenomena, particularly pertinent for reactions like the oxygen evolution reaction (OER). Notably, its transparency simplifies cell alignment, troubleshooting, and facilitates scans through the catalyst layer, crucial for background corrections. Demonstrating its versatility, we showcase its utility through Small Angle X-ray Scattering (SAXS), X-ray Diffraction (XRD), and X-ray Pair Distribution Function (PDF) analyses of total scattering data.

Scaling of the linear viscoelasticity of entangled poly(ethylene oxide) aqueous solutions

The dynamic modulus of polymer solutions and melts can be expressed as a universal function of reduced frequency when the modulus is scaled by a characteristic value according to the scaling theory of polymer physics. Although the plot of the scaled modulus as a function of the scaled frequency supports the theory, it suffers from considerable scattered distribution of data points around the hypothetical master curve. Compared with the master curve of the time–temperature superposition (TTS) of polymer melts, the master curve of polymer solutions has poor quality. Furthermore, the scale factors of polymer solutions may not show a clear dependency on molecular weight and concentrations. Experimental errors and molecular weight distribution appear to enhance the inaccuracy of the master curve. Therefore, we apply a global optimization for the superposition of the viscoelastic data of polymer solutions with various molecular weights and concentrations. The global optimization resulted in the superposition of data as accurate as that of TTS. Furthermore, the numerically determined shift factors, which were relative scale factors, showed clear dependences on molecular weight and concentrations. We compared our global optimization with previous scaling methodologies.

Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions

Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60–80 W, 1–3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.

Integrating daylight with solar thermal modeling: A dynamic calculation method for complex fenestration systems

This study developed a mathematical model named the DL-E model, which links annual dynamic daylight and solar heat gain calculations for Complex Fenestration Systems (CFSs). The DL-E model utilizes the Klems Bidirectional Scattering Distribution Function (BSDF) to characterize CFSs and can consider the shading effect of obstacles, as well as solar radiation reflected from obstacles and the ground. The DL-E model uses the Perez all-weather model to calculate transmitted solar radiation contributed by diffuse solar radiation, rather than the simplified sky model used in EnergyPlus. Results calculated with the DL-E were compared with those computed with EnergyPlus, and it was found that for most of the results, the both methods yielded closely aligned outcomes. However, for the diffuse transmitted solar radiations, reflected solar radiation from the ground in the case with a vertical obstacle, and the reflected solar radiations from the obstacle, the values calculated with DL-E showed significant differences compared to those calculated with EnergyPlus due to the use of the simplified sky model in EnergyPlus. In contrast, the values calculated with the DL-E model which used the Perez all weather sky model displayed very small difference compared to those calculated with Radiance, which means the values derived with EnergyPlus may produce significant errors. Additionally, a new workflow has been developed for calculating building load and energy for CFSs to avoid the manual conversion of the BSDF files.

Diamond-like carbon conversion surfaces for space applications

We present diamond-like carbon (DLC) conversion surfaces to detect particles with energy below 2 keV. Conversion surfaces have been widely applied in measurements of low-energy particles by instruments onboard planetary and heliophysics missions. Their effectiveness is characterized by the efficiency in changing the charge state of the incident particles while maintaining a narrow angular distribution for the reflected particles. DLC as a conversion surface coating material has high conversion efficiency. We developed a conversion surface production process that provides ultra-smooth and ultra-thin DLC conversion surfaces. The process includes substrate preparation through precision cleaning, plasma immersion ion deposition of the DLC film, and diagnostics of the film parameters. The latter includes the measurement of the coating thickness, surface roughness, and the conversion efficiency for ion beams with energy below 2 keV. The process we developed provides the DLC conversion surface coating of repeatable parameters with a mean surface roughness of 3.4 ± 0.2 Å and a mean film thickness of 46.7 ± 0.8 nm uniform across the sample area. Ion beam measurements showed a negative ion yield of 1%–2% for hydrogen atoms and 8%–15% for oxygen atoms with an angular scatter distribution of 10°–20° at full width of half maximum. These results agree with those of other conversion surface coatings in the literature. The DLC conversion surfaces presented here are implemented in the conversion surface subsystem of the Interstellar Mapping and Acceleration Probe (IMAP)-Lo instrument of the IMAP mission scheduled for launch in 2025.

2D Analytical Modelling for Ultrasonic Inspection of Concrete Structures: Effects of Scatterers Position Correlation

Ultrasonic Non-Destructive Testing (NDT) simulation plays an important role in designing inspections of concrete structures. The concrete structural complexity (presence of different heterogeneities: aggregates, porosities, microcracks …) leads to dispersion and attenuation of the ultrasonic waves, which requires an accurate modelling of the waves scattered from heterogeneities. For that purpose, studying the mean coherent wave characterized by its attenuation and phase velocity is of great interest. Two major approaches (numerical or analytical) exist for modelling the coherent wave. Numerical methods are more efficient but still limited in the 3D case by their computation time. Therefore, semi-analytical homogenization methods are considered a practical solution for a fast 3D simulation. Nevertheless, they may encounter several limitations in estimating the attenuation in dense heterogeneous materials such as concrete. Our goal is to explain and handle these prediction errors. Since the scattered ultrasonic field depends strongly on the obstacles’ positions in concrete, a particular focus is put on the pair correlation function describing the radial distribution of scatterers’ positions around a fixed scatterer (mean concentration at a distance r from this scatterer). Existing homogenization models are employed for simulating coherent wave propagation in concrete use by simplification of a uniform distribution. In order to improve the analytical models, the effects of scatterers’ positions correlation are investigated. In the present work, we propose to evaluate precisely the existing homogenization model that is the most suitable for high scatterers concentration. A comparison between this model and a 2D finite element code under development in the CIVA NDT simulation software is presented.

Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights

Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment.

Spatial identification and priority conservation areas determination of wilderness in China

In the context of an increasingly severe ecological crisis and accelerating ecological civilization construction, the specific regional differences as well as the natural environment of China restrict the uniform population distribution and the social economy's spatial layout, forming a large and widely distributed wilderness. The post-2020 Global Biodiversity Framework (GBF) takes the protection of wilderness areas as one of the key conservation goals and brings new opportunities for wilderness protection. Objective and accurate identification of the spatial range of wilderness and the determination of the focus of wilderness protection are significant for carrying out resource and environmental carrying capacity evaluations, biodiversity conservation, and national park system construction. At present, fewer studies pay attention to wilderness area identification and protection in China. In this study, we used the MaxEnt and Marxan models to establish a framework to identify the spatial distribution and conservation priorities of China's wilderness as well as guide wilderness conservation. The wilderness areas in China show a large-scale, concentrated distribution in space and a small, scattered distribution. From 2000 to 2020, the wilderness area decreased from 3.6323 million km2 in 2000 to 2.9142 million km2 in 2020, and the wilderness area reduction rate from 2000 to 2010 was greater than that in 2010–2020. From 2000 to 2020, the center of gravity of the wilderness area shifted 893.5 km to the southwest. Wilderness center of gravity relocated from Pingluo County, Ningxia Hui Autonomous Region to Delingha City, Qinghai Province. Considering conservation objectives and conservation costs, we determined that the wilderness area in urgent need of protection is 55,100 km2, accounting for 1.8 % of the total wilderness area. It is mainly distributed in Xinjiang Uygur Autonomous Region (13,000 km2), Yunnan Province (12,000 km2), and Sichuan Province (5300 km2). This methodological framework can provide an important reference for governments in dealing with global climate change, maintaining biodiversity and ecosystem diversity, and promoting sustainable human development.

Compositions and Microstructures of Carbonated Geopolymers with Different Precursors.

It is thought that geopolymers are easy to carbonate, especially when they are cured in ambient temperatures. Matrix gel's composition and microstructure, and new products of geopolymers (GPs) after carbonation were investigated in this study on the basis of XRD and SEM-EDS measurements and ternary diagram analysis, which were prepared from low-lime fly ash (FA) and ground granulated blast-furnace slag (GGBS) alone or a blend, as a precursor. The specimens were hardened in a 20 °C environment with alkali activator solution (S/N = 1.1 in mole), followed by storage under sealing or accelerated carbonation. XRD patterns show that carbonation products were nahcolite for the sole FA-based GP and calcite for the GPs using GGBS alone or as a blend. The SEM images of carbonated samples show that there were cube-shaped calcite and small calcite particles in the GGBS-based GP, but hail-like particles in the FA/GGBS blend-based GP. The hail-like particles were complexes of calcite and C-A-S-H gels determined by ternary diagram analysis, and were found to plug the top of the pores of the spongy C-A-S-H gels. We also confirmed that combined ternary diagram analysis of S-(C + M + N)-A and A-(C + M)-N are very effective in determining the gel type of a geopolymer, as well as the products and compositional changes after carbonation, in which oxide components of gels are determined by SEM-EDS. In the former diagram, C-A-S-H gels were plotted linearly along the (C + M + N)-albite (Ab) join, while N-A-S-H gels showed a scattered distribution. In the latter diagram, the plots for N-A-S-H and C-A-S-H gels are distributed in different zones. N = Na2O, C = CaO, M = MgO, A = Al2O3, S = SiO2, H = H2O.

First Record of the Exotic Ant Hypoponera ergatandria in Italy: Indoor Alate Swarms and Stinging Queens

Until recently, Hypoponera ergatandria was commonly misidentified as H. punctatissima, both of which are widespread tramp ant species. Today, H. ergatandria has been recorded in eleven European countries, while most existing H. punctatissima records are doubtful. Its geographic origins, like in the case of H. punctatissima, remain unclear. Here, we present the first record of H. ergatandria in Italy, which also hosts H. punctatissima. We report on a large swarm of alate queens from the basement of a building in the city of Teramo, Central Italy. As reported in Florida under the name H. punctatissima, the species seems capable of producing surprisingly large alate swarms, and alate queens can become a nuisance due to their stinging ability against humans. However, Hypoponera stings are not known to pose any public health threat. Furthermore, H. ergatandria and H. punctatissima are not known to have any ecological impact and are usually confined to a very scattered distribution in Europe.

Interoperator reproducibility of quantitative ultrasound analysis of hepatic steatosis in participants with suspected MASLD: A prospective study

ObjectivesTo evaluate the reproducibility of tissue attenuation imaging (TAI) and tissue scatter distribution imaging (TSI) measurements in adults with suspected metabolic dysfunction-associated steatotic liver disease (MASLD) between radiologists with varying experience. Materials and methodsParticipants with suspected MASLD were prospectively recruited. TAI and TSI were performed for each participant by two radiologists with different levels of experience. Interoperability reliability was assessed on the basis of Bland-Altman analysis and intraclass correlation coefficients (ICCs). The study determined and compared the diagnostic performance of TAI and TSI with clinical prediction models using proton magnetic resonance spectroscopy (1H-MRS) as a reference. ResultsA total of 180 participants (women, n = 56; men, n = 124, mean age, 46.98 ± 14.92 years; mean BMI, 25.81 ± 4.47) were enrolled from August 2022 to September 2022. Bland-Altman plots showed only slight deviation in the TAI and TSI results of the two radiologists; there was good interoperator reproducibility for TAI (ICC = 0.92) and TSI (ICC = 0.86). Senior and junior radiologists performed examinations labeled as TAI-1 and TSI-1, and TAI-2 and TSI-2, respectively. The areas under the curves (AUCs) of TAI-1, TAI-2, TSI-1, and TAI-2 for the detection of ≥5 % hepatic steatosis were 0.90, 0.96, 0.91 and 0.96, respectively. According to ROC analysis, the diagnostic performance of both radiologists for TAI and TSI was statistically similar and superior to that of the clinical prediction model. ConclusionsTAI and TSI have good reproducibility between radiologists with different levels of experience. Meanwhile, both TAI and TSI demonstrated good diagnostic performance for hepatic steatosis (≥5%), surpassing that of clinical prediction models.

Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization

Mine operational safety is an important aspect of maintaining the operational continuity of a mining area. In this study, we used the InSAR time series to analyze land surface changes using the ICOPS (improved combined scatterers with optimized point scatters) method. This ICOPS method combines persistent scatterers (PS) with distributed scatterers (DS) to increase surface deformation analysis’s spatial coverage and quality. One of the improvements of this study is the use of machine learning in postprocessing, based on convolutional neural networks, to increase the reliability of results. This study used data from the Sentinel-1 SAR C-band satellite during the 2016–2022 observation period at the Musan mine, North Korea. In the InSAR surface deformation time analysis, the maximum average rate of land subsidence was approximately > 15.00 cm per year, with total surface deformation of 170 cm and 70 cm for the eastern dumping area and the western dumping area, respectively. Analyzing the mechanism of land surface changes also involved evaluating the geological conditions in the Musan mining area. Our research findings show that combining machine learning and statistical methods has great potential to enhance the understanding of mine surface deformation.

Assessing the Impact of Preprocessing and Conversion Technologies on the Sustainable Aviation Fuel Supply from Forest Residues in the Southeast U.S.A.

Forest residues have been suggested as potential feedstock for sustainable aviation fuel (SAF) production through different pathways. However, the bulky density and scatter distribution require efficient size-reduction processes to enhance the feedstock supply. Thus, this study analyzes the impact of alternative preprocessing and conversion technologies on the SAF supply chains from logging residues (the predominant share of forest residues) using a two-stage mixed-integer linear programming model. The model determines the optimal location of biomass preprocessing depots, conversion facilities, and airports receiving SAF by minimizing the net present value of the total supply chain cost over 10 years. Using high-resolution spatial data in the Southeast U.S.A. as a case study, the results show that the technology and scale of the facilities heavily influenced the SAF’s breakeven cost and maximum supply quantity. The most economically efficient system that adopts a rotary shear milling system and pyrolysis conversion process could generate up to 650 million gallons of SAF from logging residues in the region, with nearly 62% of the SAF being produced from hardwood residues. Also, the most efficient system has an estimated breakeven cost of US$5.51 per gallon of SAF.

Random laser emission from dye-doped gain media with optically trapped scattering particles

In this study, an optical trapping technique is employed to manipulate the scatterer distribution within a random laser medium. By focusing the trapping beams into small regions within the three-dimensional scattering medium, the scattering particles around them are concentrated in those regions, resulting in an inhomogeneous scatterer distribution. The experimental results show that optical trapping increases the maximum spike intensity in the emission spectrum. Furthermore, the spectral spike intensity depends on the power of the trap spots. The relationship between the maximum and average spike intensities in the emission spectra exhibits a characteristic observed in other random lasers with inhomogeneous scatterer distributions.