Intensity Pattern Research Articles

Reactive Stroma and Acinar Morphology in Prostate Cancer: Implications for Progression and Prognostic Assessment.

Prostate cancer (PC) remains a significant global health concern, with prognostic assessments largely reliant on the Gleason Classification System. While it has proven effective, subjectivity in interpretation persists, prompting the need for complementary approaches. Reactive stroma (RS) has emerged as a potential candidate for enhancing PC characterization, as it reflects intricate interactions among stromal, epithelial, and extracellular matrix components. To shed light on this, we conducted a comprehensive study. Two expert pathologists independently analyzed consecutive prostate biopsies (n = 120 patients), categorized into four groups based on Gleason scores. Four acinar patterns were described, denoted as A, B, C, and D. Our study uncovered a noteworthy presence of RS, predominantly within poorly differentiated tumors. Stromogenic tumors, characterized by high RS content, were particularly associated with Gleason scores of 4 + 3 and ≥ 8. Intriguingly, acinar patterns, including the distinctive B and D patterns, exhibited strong correlations with stromogenic tumors. Incorporating quantitative imaging techniques (Second Harmonic Generation and Two-Photon Excitation Fluorescence Microscopy), we examined collagen fiber density within the stroma. Our analysis revealed a direct relationship between RS intensity and collagen fiber counts, particularly prominent in patterns B and D. These findings suggest that the stromal reaction in PC is closely linked to acinar morphology and collagen deposition. Moreover, rudimentary microacini at the tumor periphery, associated with intense RS and patterns B and D, may signify an unfavorable prognosis. Our study highlights the potential of RS as an additional prognostic factor in PC. It underscores the intricate interplay between acinar patterns, RS intensity, and collagen fiber density, providing valuable insights for future prognostic assessments and therapeutic strategies. Further exploration of these relationships is essential for a comprehensive understanding of PC progression and management.

NIMG-02. DEVELOPING A RADIOMIC HIERARCHICAL GAUSSIAN PROCESS BOOSTING MODEL TO PREDICT PRIMARY TUMOR ORIGIN FROM MULTICENTRIC LONGITUDINAL MRI DATA OF BRAIN METASTASES

Abstract Focal neurologic deficits due to brain metastases might be the initial presentation in patients with cancer. Common approaches to investigate the occult primary malignancy include a whole-body PET-CT, whole-body MRI, studying tumor markers, or histopathological examination. Most of these modalities are expensive, time-consuming, invasive, and delay treatment. The field of radiomics leverages quantitative features extracted from images to improve the decision-making process in clinical practices. Although not easily understandable, these features are proxies for the tumor’s shape, contour, texture, and intensity patterns. They can help understand tumor heterogeneity, predict tumor behavior, and assess treatment response. We propose a robust radiomic workflow using longitudinal MRI data from 914 high-resolution imaging studies from 12 different centers (Ocaña-Tienda et al. (2023), Ramakrishnan et al. (2023), Wang et al. (2023)) to predict the origin of brain metastases from brain MRI scans. After using ensemble feature selection methods, we trained three fixed-effects and one mixed-effects multiclass classification model to account for longitudinal data. Fixed-effects logistic regression and support vector kernel models performed the worst (AUC 0.74 and 0.75, respectively), while the random forest performed better (AUC 0.97). The mixed-effects hierarchical Gaussian process boosting (GPBoost) model performed the best with an accuracy of 85.8%, precision of 85.4%, sensitivity of 85.8%, specificity of 95.7%, and an AUC of 0.98. In one-versus-rest classification, the GPBoost model identified the primary tumor as melanoma with the highest accuracy (96.1%) and non-small cell lung cancer with the lowest accuracy (89.0%). Developing such models holds great promise in reducing patient and institutional costs, improving time to effective treatment, and enhancing overall survival rates through personalized therapy approaches. In the future, we hope that incorporating newer patient data and refining the model to improve external validity would enable more accurate and generalizable predictions, leading to better clinical outcomes across diverse populations.

Immune Response and Transcriptome Analysis of the Head Kidney to Different Concentrations of Aeromonas veronii in Common Carp (Cyprinus carpio)

The common carp (Cyprinus carpio), a major economic freshwater fish, is suffering from a variety of bacterial infectious diseases because of its high-density, factory and intensive farming patterns. Aeromonas veronii is the causative agent of high mortality in common carp, causing severe economic losses in aquaculture. However, the regulatory mechanisms involved in the response of common carp to this bacterial infection remain poorly understood. In this study, we compared mortality, blood serum LZM (Lysozyme) and IgM (Immunoglobulin M) levels and transcriptome patterns of head kidney tissues after infection with different concentrations of Aeromonas veronii. We observed that mortality increased progressively with an increasing pathogen concentration. The concentrations of blood serum LZM and IgM significantly increased after infection. A total of 13 and 925 differentially expressed genes (DEGs) were identified after infection with low (T4) and high (T9) concentrations of bacterial suspension, respectively. KEGG and GO analyses of the DEGs highlighted multiple immune-related signaling pathways. Weighted gene co-expression network analysis (WGCNA) revealed that 136 and 83 hub genes were related to blood serum LZM and IgM, respectively. Finally, the gene expression in the head kidney was validated via RT–qPCR to be consistent with the transcriptome. These results provide insights into the mechanisms of the immune response to infection with different concentrations of Aeromonas veronii and offer useful information for further studies on immune defense mechanisms in common carp.

T1-weighted MRI texture analysis in amyotrophic lateral sclerosis patients stratified by the D50 progression model.

Amyotrophic lateral sclerosis, a progressive neurodegenerative disease, presents challenges in predicting individual disease trajectories due to its heterogeneous nature. This study explores the application of texture analysis on T1-weighted MRI in patients with amyotrophic lateral sclerosis, stratified by the D50 disease progression model. The D50 model, which offers a more nuanced representation of disease progression than traditional linear metrics, calculates the sigmoidal curve of functional decline and provides independent quantifications of disease aggressiveness and accumulation. In this research, a representative cohort of 116 patients with amyotrophic lateral sclerosis was studied using the D50 model and texture analysis on MRI images. Texture analysis, a technique used for quantifying voxel intensity patterns in MRI images, was employed to discern alterations in brain tissue associated with amyotrophic lateral sclerosis. This study examined alterations of the texture feature autocorrelation across sub-groups of patients based on disease accumulation, aggressiveness and the first site of onset, as well as in direct regressions with accumulation/aggressiveness. The findings revealed distinct patterns of the texture-derived autocorrelation in grey and white matter, increase in bilateral corticospinal tract, right hippocampus and left temporal pole as well as widespread decrease within motor and extra-motor brain regions, of patients stratified based on their disease accumulation. Autocorrelation alterations in grey and white matter, in clusters within the left cingulate gyrus white matter, brainstem, left cerebellar tonsil grey matter and right inferior fronto-occipital fasciculus, were also negatively associated with disease accumulation in regression analysis. Otherwise, disease aggressiveness correlated with only two small clusters, within the right superior temporal gyrus and right posterior division of the cingulate gyrus white matter. The findings suggest that texture analysis could serve as a potential biomarker for disease stage in amyotrophic lateral sclerosis, with potential for quick assessment based on using T1-weighted images.

Characterizing the Wildfire Patterns in the Marromeu Complex Using Remote Sensing Data

Objective: To caraterize the wildfire regime in the Marromeu Complex between 2002 and 2019. Method: Data from the MOD14 Collection 6 sensor, pertaining to thermal anomalies (MCD14ML, MCD64A1) corresponding to hot spots and burned areas, were used on a monthly basis. Only pixels with a reliability of 80% or higher were considered. Patterns of hot spots, burned area, density, intensity, frequency, and seasonality of fires were analyzed. Data processing was conducted using ArcGIS 10.8. Results and Discussion: A total of 12,227 hot spots were identified, covering 73% of the burned area. The annual average burned area was 24%, with densities ranging from moderate to very high. The fires showed low intensity across most of the Complex, with an average fire frequency of 2 to 3 times per year, and the highest fire records were observed in September. These findings are analyzed within the theoretical framework, emphasizing the implications of temporal and spatial variations in fires and their potential causes and environmental impacts. Implications of the Research: This study offers insights into wildfire management and emphasizes the necessity of fire management strategies in the Marromeu Complex. The implications include enhancing management plans and mitigating environmental impacts associated with fires. Originality/Value: This study contributes to the literature by providing a detailed characterization of the fire regime in the Marromeu Complex. The research is relevant as it offers new information on fire dynamics and their variations over time, which could impact management practices and environmental policies.

Prediction and Evaluation of Industrial Land Intensive Use: Adding Policy Impact to System Dynamics Model

Nowadays, urban development prioritizes improving quality over mere quantitative expansion, which requires a shift in land use from previous extensive use patterns to a more refined and efficient intensive use pattern. The intensive use of industrial land (IUIL) is a resource-utilization strategy for industrial land that aims at maximizing the dual growth of ecological and economic benefits by minimizing resource consumption and factor costs. In this research, IUIL is deconstructed into four aspects: input intensity, utilization intensity, economic benefits, and environmental benefits. Grounded in a qualitative analysis of the interconnected casual feedback among the various factors influencing IUIL, a system dynamics model with 36 indicators for IUIL evaluation and prediction is constructed. Policy impacts on IUIL from the supply side, utilization side, and supervision side are analyzed and embedded for a scenario simulation based on the theory of the entire life cycle of land use. The simulation shows its efficiency in reporting the variation tendency of industrial land use with varied policy impact strength. The results reveal a dynamic understanding of the evolving patterns of land intensification and present different characteristics of IUIL. This study further proposes policy recommendations to provide experience and references for the authorities to promote high-quality urbanization development in practice.

Who is sufficient, and why? A mixed-methods approach to the social determinants of sufficiency lifestyles in the pursuit of decarbonisation

Sufficiency consists of less materially intensive consumption patterns that focus on wellbeing rather than material wealth. Such consumption patterns are commonly referred to as sufficiency lifestyles and are increasingly seen as a key driver for achieving decarbonisation. However, while research finds that sustainable consumption and environmental behaviour are often associated with high social status, lower carbon footprints and lower consumption more broadly are associated in the literature with poverty and deprivation. This article aims to investigate whether a combination of low carbon footprint and high wellbeing exists, what socio-demographic characteristics are associated with it, and to explore the actual experiences of people engaged in sufficiency lifestyles through initiatives and their characteristics. We use a mixed-methods design with data from demographically representative surveys in Denmark, Germany, Italy and Latvia (N=5,080), and in-depth interviews with participants from sufficiency-oriented intentional communities (N=90). We find that sufficiency lifestyles are linked to a stronger inclination towards sufficiency orientation or a heightened stronger environmental identity, accompanied by a negative correlation with social deprivation aspects. Drawing on the interviews, we find that individuals engaged in sufficiency-oriented practices tend to benefit from economic, social and cultural resources that allow them to overcome energy dependency and constraints, and that their motivations are not limited to pro-environmental behaviour. Based on these empirical findings, we explore potential avenues for the diffusion of sufficiency-oriented lifestyles, including the establishment of binding rules through a democratic process that curb overconsumption while providing attractive low-carbon lifestyles for all.

Fractional-order hybridly polarized vector beams: generation, focusing, propagation, and spatial self-phase modulation

As a class of integer-order vector beams, hybridly polarized vector beams (HPVBs) are widely used in focus shaping, femtosecond laser filamentation, linear and nonlinear polarization evolution, etc. Recently, fractional-order vector beams have gained widespread interest due to their more control parameters, rich photophysical properties, and novel nonlinear optical phenomena. In this work, we report the experimental generation, focusing and propagation characteristics, and spatial self-phase modulation (SSPM) phenomenon of fractional-order HPVBs. It is shown that during the focusing and propagation processes, the intensity pattern of fractional-order HPVBs develops from a near-Gaussian structure in the incident plane to an asymmetric structure in both the focal field and the far field. Meanwhile, their distributions of state of polarization (SoP) also evolve, although it remains a hybrid polarization distribution overall. When the focused fractional-order HPVBs pass through the nonlinear optical sample, the far-field self-diffraction intensity pattern displays an irregular concentric multi-ring structure with a hybrid polarization distribution. It is found that the nonlinear medium not only modulates the far-field intensity pattern of fractional-order HPVBs but also controls their SoP distribution. This symmetric breaking HPVB has potential application prospects in optical micro-manipulation, light-matter interaction, optical spin-orbit conversion, etc.

Dynamically variable intensity patterns projected using an optofluidic phase-shifter array

We present a concept for the dynamically variable definition of arbitrary intensity distributions using an array of optofluidic phase-shifters. These components consist of cylindrical fluidic surfaces whose interface may be controllably shaped using electrowetting-on-dielectrics actuation. Key to the generation of defined intensity distributions is the ability to calculate the required shape for this phase-shifting interface and to this end we present a novel procedure, to our knowledge, that combines a real-time optimization algorithm with an influence matrix approach to generate the required surface. We illustrate the effectiveness of this approach by reconstructing arbitrary surface profiles with one optofluidic phase-shifting component that is then used to project a desired two-dimensional intensity distribution. Using this approach, we further demonstrate the capability of a two-dimensional phase-shifter array to generate larger dynamically programmable intensity patterns by combining individual intensity distributions.

Spatiotemporal responses of ungulates to hunting in a fenced multi-use area

Context Human activities, such as tourism and hunting, affect the spatiotemporal behaviour of wildlife. For example, it is well documented that ungulates change their spatiotemporal behaviour as a response to hunting pressure, but less is known about ungulate responses to hunting in areas where human activity is common throughout the year and ungulates are constrained by fences. Aims In this camera-trap study, we analysed the change in spatiotemporal behaviour of wild ungulates (elk, Cervus canadensis (3519 events), moose, Alces alces (1153 events), and white-tailed deer, Odocoileus virginianus (2708 events)) in response to the hunting period in a recreational and fenced park, the Cooking Lake–Blackfoot Provincial Area, Canada. Methods We used general linear models to compare species-specific patterns of intensity of use, calculated as events per week, in response to changes in the nature of human disturbance, namely a shift from recreation to hunting activity. In particular, we compared intensity of use in and out of the hunting season to determine whether species engaged in spatial patterns of avoidance with respect to hunting. We used daily and seasonal patterns of activity to determine how ungulates shifted their temporal use in response to hunting activity and whether they became more nocturnal as a result. Key results We found that ungulates responded temporally to the hunting period by generally shifting their activity to more nocturnal hours, with white-tailed deer showing the biggest temporal shift, suggesting that the ungulates distinguish between consumptive and non-consumptive human activities. Nevertheless, temporal overlap between humans and all ungulate species increased during the hunting period as humans targeted times of increased ungulate activity. Spatially, the response was less distinctive and was species-specific. Elk showed little change in spatial behaviour in response to the hunting period. In contrast, moose decreased the use of trail areas and other areas frequented by humans, whereas deer, counterintuitively, increased the use of trail areas, albeit their use became much more nocturnal. Conclusions We have shown that responses of ungulates to hunting exceed those to non-consumptive recreational use, and whereas temporal responses (increased nocturnality) were consistent across ungulate species, spatial responses were species-specific. Implications Management in small fenced multi-use areas needs to account for shifts in the intensity of disturbance resulting from a change in human disturbance from recreational activity to hunting. Providing spatial opportunities for avoidance of humans is key for most species if hours of operation in these areas already limit the timing of human activity.

Unraveling the global economic and mortality effects of rising urban heat island intensity

The increasing severity of urban heat island (UHI) effects poses a significant concern in cities, where to over half of the world's population lives. We examine the pattern of surface UHI intensity (SUHII) and its effect on urban economic productivity and mortality across 171 countries from 2003 to 2018. Countries with heavy industrial/manufacturing bases and higher income levels face more significant economic repercussions from SUHII. Males experience higher mortality rates under comparable SUHII conditions. A unit increase in GNI correlates to a 23.2 % rise in SUHII's effect on GDP and a 5.5 % increase in its effect on mortality rate. A higher Socio-Demographic Index mitigates SUHII's impact on urban GDP. Moreover, the Gini index directly impacts SUHII more than it affects SUHII-related mortality through inequality. Reducing income inequality by one unit will increase the enhancing effect of SUHII on the mortality rate by 11.8 %. Our findings reveal a significant link between wealth disparity and amplified health risks associated with SUHII, potentially leading to new forms of urban inequality. The study highlights the importance of development status and economic composition in facing UHI-related challenges and recommends equitable strategies for policymakers and urban planners to mitigate UHI effects in diverse developmental contexts.

Biosynthesis of antimicrobial nanoparticle from Swertia spp. (Chirayita) against bacterial pathogens of poultry- A way forward to green nanotechnology and nano-medicines

The increasing prevalence of multidrug-resistant microorganisms in poultry has led to a rise in bacterial infections, causing significant economic loss. Green nanotechnology, such as silver nanoparticles (AgNPs), has the potential to address this issue by providing potent antifungal, antiviral, and antibacterial properties. This study explored the combined potential of AgNPs and the local herb Swertia chirayita against established poultry pathogens, employing a non-factorial Central Composite Design (CCD) to evaluate the factors affecting the production of nanoparticles induced by silver nitrate from the selected herb. The optimal values for temperature, wavelength, silver nitrate concentration, incubation duration, and pH were found to produce the highest nanoparticles. The functional groups in Swertia chirayita stimulated nanoparticles were confirmed using FTIR spectroscopy, and the stability of ScNPs was elucidated using zeta potential. The crystalline structure of ScNPs was confirmed using diffraction intensity patterns. Silver nanoparticles demonstrated antibacterial activity against Salmonella spp. and Escherichia coli (E.coli), both known as significant poultry pathogens, using the agar well diffusion method, with inhibition zones of 25.0 mm and 35.0 mm, respectively.This study explored the green manufacturing of silver nanoparticles by using plants and microorganisms, focusing on their antibacterial properties. The exact mechanism of synthesis and action in AgNPs is still poorly understood. Researchers should prioritize the use of accessible, easy-to-extract plants or bacteria, especially non-pathogenic and fast-growing microorganisms for safe handling. Analyzing biomolecules in plant extract, microbial biomass, or culture supernatants, including probiotic bacteria, is crucial for creating and stabilizing AgNPs, which could be effective synthetic agents. It is crucial to optimize conditions for rapid, stable, and large-scale synthesis. Based on this research, Sc-NPs may be proposed as nanomedicine for treating infections in poultry caused by E. coli and Salmonella spp.

Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types

This study quantifies the influences of anthropogenic forcing to date on precipitation over Aotearoa New Zealand (ANZ). Large ensembles of simulations from the weather@home regional climate model experiments are analysed under two scenarios, a natural (NAT) or counter-factual scenario which excludes human-induced changes to the climate system and an anthropogenic (ANT) or factual scenario. The impacts of anthropogenic forcing on precipitation are analysed in the context of large-scale circulation types characterized using an existing Self Organizing Map classification. The combined effect of both thermodynamics and dynamics are compared with values expected from the Clausius–Clapeyron (C–C) relation. Changes in the precipitation intensity due to greenhouse gas-forced temperature rise are lower than the expected C–C value. However extreme precipitation changes approach the C–C value for some circulation types. Specifically westerly flows enhance precipitation change across ANZ relative to the C–C rate, particularly over the West Coast. Conversely, northwesterly flows reduce the change over the North Island relative to the C–C value. Moreover, the wet day frequency generally reduces in the ANT scenario relative to NAT, reductions are largest on the West Coast of the South Island for westerly flows. Additionally, the frequency of days with extreme precipitation rises over ANZ for most circulation patterns, except in Northland and for northwesterly flows. This underscores the combined influence of dynamics and thermodynamics in shaping both precipitation intensity and frequency patterns across ANZ.

Quantitative phase imaging with two in-line holograms.

Quantitative phase imaging (QPI) has emerged as a practical technique for acquiring structural information from phase objects. Digital holography can realize phase detection, but it is limited by a spatial bandwidth product or affected by the overlap of conjugate images. The phase retrieval algorithm serves as an effective tool for QPI dealing with intensity patterns. Traditional phase retrieval algorithms heavily rely on strong support constraints or high data redundancy to accurately reconstruct the sample image. However, in single-frame phase retrieval algorithms, the precise acquisition of support constraints is notably challenging. The multiple-measurement spends much time on data acquisition and is unsuitable for dynamic sample observation. In this paper, we propose a novel, to the best of our knowledge, quantitative phase imaging method that utilizes only two in-line holograms. We have developed a phase retrieval algorithm based on ptychography, which eliminates twin-image and separates illumination background. The proposed method achieves high data utilization efficiency and can be employed for dynamic imaging.

Photoluminescence studies of Sr3P4O13: Eu3+ phosphor prepared by wet chemical method: Structural properties, charge compensation via alkali metal ions and Judd-Ofelt analysis

The Sr3P4O13:Eu3+ phosphors co-doped with alkali metal ions (A+ = Li+, Na+ and K+) were prepared by wet chemical method. The comparison with standard JCPDS data confirmed the formation of a triclinic crystalline phase with P-1(2) space group for the Eu3+ doped Sr3P4O13 phosphor and co-doped with alkali metal ions. The Li+ co-doped Sr3P4O13:Eu3+ phosphor has comparatively sharp and intense XRD patterns. The scanning electron microstructural analysis confirmed the formation of the particles size of 5 -50 μm. The comparative study of photoluminescence properties depicted that the peak positions were similar for all the prepared samples. The photoluminescence analysis of Sr3P4O13:Eu3+ phosphors show the emission in the red-orange region under the excitation of 394 nm (7F0→5L6) wavelength. Further, the charge compensation using alkali metal ions shows the larger photoluminescence intensity observed in the case of the Li+ co-doped Sr3P4O13:Eu3+ phosphors suggesting that the Li+ ion is better charge compensator among the studied alkali metal ions. Further, Judd-Ofelt (J-O) parameters were estimated for the Sr3P4O13:Eu3+ phosphors and co-doped with alkali metal ions in a series of samples. The comparison of Sr3P4O13:Eu3+ phosphors co-doped with alkali metal ions alongwith the J-O estimated parameters have been presented in the article.

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Research on burnup depth measurement of spent fuel board based on thermal neutron imaging technology

The detection equipment for measuring the burnup depth in spent fuel rods is a vital component of the spent fuel management system. which can determine the burnup depth of spent fuel board and plays a crucial role in safeguarding the safety, economic efficiency, and structural integrity of the fuel assembly. This study introduces an innovative technical approach for assessing the burnup depth of spent fuel veneers, utilizing transmitted thermal neutron imaging technology. We have significantly enhanced the design of a thermal neutron moderator collimator, leading to remarkable improvements in the quality of the thermal neutron beam. Following moderation by the collimator, the ultimate thermal neutron injection rate at the designated sample location exceeds 103 n/cm2, with thermal neutrons comprising over 74% of the collimated neutron beam. This advanced measurement system enables us to obtain a detailed two-dimensional distribution map of thermal neutrons transmitted through spent fuel boards with varying burnup depths. By analyzing the grayscale intensity patterns in these maps, we can accurately evaluate the burnup degree within the simulated spent fuel plate. Furthermore, we establish a correlation between the transmitted thermal neutron count in the imaging field and the burnup depth of the spent fuel veneer. This allows for precise determination of burnup depth through the analysis of the two-dimensional distribution of transmission thermal neutron intensity. Our findings demonstrate the feasibility of a scheme for detecting the burnup depth in spent fuel boards based on transmission thermal neutron imaging technology, and obtained a linear relationship between the neutron transmission count and the burnup depth of the spent fuel plate, laying a solid theoretical foundation for future research and development of testing equipment to assess burnup in spent fuel veneers.

Talbot-effect-based multiplication of Laguerre–Gaussian beams with non-zero radial indices: From theory to experimental realization

We present a Talbot self-imaging inspired method for multiplying Laguerre-Gaussian (LG) beams of non-zero radial indices. We explore theoretically and experimentally the LG beam diffraction from two-dimensional (2D) periodic structures. In particular, we determine near-field LG diffraction patterns from a 2D binary grating of a small opening ratio (OR). We demonstrate that incident LG beam intensity patterns are reproduced as images of individual square apertures of the grating in certain Talbot planes. We also investigate the impact of the number of fractional-Talbot and Talbot planes on the quality of the generated 2D array of multiplexed LG modes. Our theoretical predictions are in good agreement with our experiments. Our method can find applications in optical communication, optical tweezing, multi-particle trapping, screening, and micro-manipulation.

Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web.

Stable isotope tracing is a crucial technique for understanding the metabolic wiring of biological systems, determining metabolic flux through pathways of interest, and detecting novel metabolites and pathways. Despite the potential insights provided by this technique, its application remains limited to a small number of targeted molecules and pathways. Because previous software tools usually require chemical formulas to find relevant features, and the data are highly complex, especially in untargeted metabolomics and when the downstream reactions and metabolites are poorly characterized. We report here Khipu version 2 and its new user-friendly web application. New functions are added to enhance analyzing stable isotope tracing data including metrics that evaluate peak enrichment in labeled samples, scoring methods to facilitate robust detection of intensity patterns and integrated natural abundance correction. We demonstrate that this approach can be applied to untargeted metabolomics to systematically extract isotope-labeled compounds and annotate the unidentified metabolites.

Vertical farming goes dynamic: optimizing resource use efficiency, product quality, and energy costs

Vertical farming is considered to be a key enabler for transforming agrifood systems, especially in or nearby urbanized areas. Vertical farming systems (VFS) are advanced indoor cropping systems that allow for highly intensified and standardized plant production. The close control of environmental parameters makes crop production stable and repeatable, ensuring year-round uniform product quality and quantity irrespective of location. However, due to continuous changes in plant physiology and development, as well as frequent changes in electricity prices, the optimum conditions for crop production and its associated costs can change within days or even minutes. This makes it beneficial to dynamically adjust setpoints for light (intensity, spectrum, pattern, and daylength), CO2, temperature, humidity, air flow, and water and nutrient availability. In this review, we highlight the beneficial effects that dynamic growth conditions can have on key plant processes, including improvements in photosynthetic gas exchange, transpiration, organ growth, development, light interception, flowering, and product quality. Our novel findings based on modeling and experimentation demonstrate that a dynamic daily light intensity pattern that responds to frequent changes in electricity prices can save costs without reducing biomass. Further, we argue that a smart, dynamic VFS climate management requires feedback mechanisms: several mobile and immobile sensors could work in combination to continuously monitor the crop, generating data that feeds into crop growth models, which, in turn, generate climate setpoints. In addition, we posit that breeding for the VFS environment is at a very early stage and highlight traits for breeding for this specialized environment. We envision a continuous feedback loop between dynamic crop management, crop monitoring, and trait selection for genotypes that are specialized for these conditions.