Background and Objectives: The influence of montelukast (MK), an antagonist of cysLT1 leukotriene receptors, on lung lesions caused by experimental diabetes was studied. Materials and Methods: The study was conducted on four groups of six adult male Wistar rats. Diabetes was produced by administration of streptozotocin 65 mg/kg ip. in a single dose. Before the administration of streptozotocin, after 72 h, and after 8 weeks, the serum values of glucose, SOD, MDA, and total antioxidant capacity (TAS) were determined. After 8 weeks, the animals were anesthetized and sacrificed, and the lungs were harvested and examined by optical microscopy. Pulmonary fibrosis, the extent of lung lesions, and the lung wet-weight/dry-weight ratio were evaluated. Results: The obtained results showed that MK significantly reduced pulmonary fibrosis (3.34 ± 0.41 in the STZ group vs. 1.73 ± 0.24 in the STZ+MK group p < 0.01) and lung lesion scores and also decreased the lung wet-weight/dry-weight (W/D) ratio. SOD and TAS values increased significantly when MK was administered to animals with diabetes (77.2 ± 11 U/mL in the STZ group vs. 95.7 ± 13.3 U/mL in the STZ+MK group, p < 0.05, and 25.52 ± 2.09 Trolox units in the STZ group vs. 33.29 ± 1.64 Trolox units in the STZ+MK group, respectively, p < 0.01), and MDA values decreased. MK administered alone did not significantly alter any of these parameters in normal animals. Conclusions: The obtained data showed that by blocking the action of peptide leukotrienes on cysLT1 receptors, montelukast significantly reduced the lung lesions caused by diabetes. The involvement of these leukotrienes in the pathogenesis of fibrosis and other lung diabetic lesions was also demonstrated. Full article

This study introduces a novel sensitivity analysis approach to assess the resilience and susceptibility of hydrologic systems to the stresses of climate change, moving away from conventional top-down methodologies. By exploring the hydrological sensitivity of the upper Kızılırmak River basin using the Variable Infiltration Capacity (VIC) hydrologic model, we employed a sensitivity-based approach as an alternative to the traditional Global Climate Model (GCM)-based methods, providing more insightful information for water managers. Considering the consistent projections of increasing temperature over this region in GCMs, the hydrologic system was perturbed to examine gradients of a more challenging climate characterized by warming and drying conditions. The sensitivity of streamflow, snow water equivalent, and evapotranspiration to temperature (T) and precipitation (P) variations under each perturbation or “reference” climate was quantified. Results indicate that streamflow responds to T negatively under all warming scenarios. As the reference climates become drier, streamflow sensitivity to P increases, indicating that meteorological drought impacts on water availability could be exacerbated. These results suggest that there will be heightened difficulty in managing water resources in the region if it undergoes both warming and drying due to the following setbacks: (1) water availability will shift away from the summer season of peak water demand due to the warming effects on the snowpack, (2) annual water availability will likely decrease due to a combination of warming and lower precipitation, and (3) streamflow sensitivity to hydroclimatic variability will increase, meaning that there will be more extreme impacts to water availability. Water managers will need to plan for a larger set of extreme conditions. Full article

This study examines the effects of three interactive voice assistant (VA) features (responsiveness, ubiquitous connectivity, and personalization) on consumer happiness. An online survey was administered to 316 VA consumers, and the data were analyzed using structural equation modeling with SmartPLS 4 software. The results indicate that VA responsiveness, ubiquitous connectivity, and personalization have significant effects on consumer happiness. This study also provides evidence that consumer happiness is influenced by VA features through the mediating roles of autonomy and timeliness. Notably, perceived privacy risk has a dual effect, negatively affecting happiness but positively moderating the relationship between autonomy and happiness, suggesting a complex interplay between benefits and concerns in user interactions with VAs. This study highlights the need for VA businesses to consider both the enhancing and mitigating factors of technology for user experiences. Furthermore, our findings have significant implications for VA businesses and executives, suggesting that improved interactions through these VA features can better serve consumers and enhance their experiences. Full article

Facing the increasingly complex and uncertain external environment, the reasonable control of investment risk is the key to realizing the sound operation and high-quality development of enterprises. Based on the innovation perspective, this paper takes A-share non-financial listed companies from 2007 to 2021 as the research sample to explore the impact of the corporate risk-taking level on the high-quality development of enterprises and examines the transmission mechanism of the relationship between the two from the perspectives of innovation efficiency, innovation input, and innovation output. It is found that enterprise risk-taking significantly inhibits the high-quality development of enterprises, by reducing innovation efficiency; innovation efficiency plays a mediating role in the influence of the relationship between the two, which is mainly due to the fact that enterprise risk-taking increases the innovation inputs of enterprises but reduces the innovation outputs of enterprises, and then reduces the innovation efficiency of enterprises and inhibits the high-quality development of enterprises. This heterogeneity study finds that the inhibitory effect of corporate risk-taking on the high-quality development of firms is more pronounced among manufacturing firms, small-scale firms, and firms with higher capital intensity. The findings of this study provide both guidance to help enterprises to reduce risky investment decision-making behaviors and experience for regulators to effectively promote the formulation of policies related to the high-quality development of the real economy. Full article

Recently, many floating renewable energy platforms have been deployed in coastal regions, where sloping bottoms are an important factor when evaluating their safety. In this article, a simplified method coupling an eigenfunction matching method (EMM) and a finite-depth Green’s function (FDGF) is developed to evaluate floating-body motion responses over a sloping bottom for which bathymetry is homogeneous in the longshore direction. We propose an extended EMM to create an incident wave model over the sloping bottom, thereby obtaining the Froude–Krylov (F–K) force and Neumann data on the wet surfaces of the floating body for the diffraction problem. An equivalent depth is introduced to account for the interaction between the sloping bottom and floating bodies when dealing with the diffraction and radiation problems. The accuracy of the present method is validated through a comprehensive comparison with numerical and/or experiment results for a liquefied natural gas (LNG) ship and a floating hemisphere from the literature. Generally, the present, simplified method can give predictions with sufficient accuracy. Full article

The controlled manufacturing of semiconductor photocatalysts is crucial to their development for drinking water treatment. In this study, TiO₂-coated meltblown nonwoven fabrics prepared via Atomic Layer Deposition (ALD) are applied for the inactivation of Escherichia coli (E. coli). It is observed that in the presence of an ultraviolet light-emitting diode (UV-LED) light source (255 nm), 1.35 log E. coli inactivation is achieved. However, exposure to catalyst-coated fabrics in addition to the light source resulted in >4 log E. coli inactivation, suggesting a much higher rate of hydroxyl radical formation on the surface, leading to cell death. Full article

Despite the end of the pandemic, coronavirus disease 2019 (COVID-19) remains a major public health concern. The first waves of the virus led to a better understanding of its pathogenesis, highlighting the fact that there is a specific pulmonary vascular disorder. Indeed, COVID-19 may predispose patients to thrombotic disease in both venous and arterial circulation, and many cases of severe acute pulmonary embolism have been reported. The demonstrated presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the endothelial cells suggests that direct viral effects, in addition to indirect effects of perivascular inflammation and coagulopathy, may contribute to pulmonary vasculopathy in COVID-19. In this review, we discuss the pathological mechanisms leading to pulmonary vascular damage during acute infection, which appear to be mainly related to thromboembolic events, an impaired coagulation cascade, micro- and macrovascular thrombosis, endotheliitis and hypoxic pulmonary vasoconstriction. As many patients develop post-COVID symptoms, including dyspnea, we also discuss the hypothesis of pulmonary vascular damage and pulmonary hypertension as a sequela of the infection, which may be involved in the pathophysiology of long COVID. Full article

Optical Coherence Tomography (OCT) is a growing family of biophotonic imaging techniques, but in the literature there is a lack of easy-to-use tools to universally directly evaluate a device’s theoretical performance for a given metric. Modern computing tools mean that direct numerical modeling can, from first principles, simulate the performance metrics of a specific device directly without relying on analytical approximations and/or complexities. Here, we present two different direct numerical models, along with the example MATLAB code for the reader to adapt to their own systems. The first model is of photo-electron shot noise at the detector, the primary noise source for OCT. We use this firstly to evaluate the amount of additional noise present (1.5 dB) for an experimental setup. Secondly, we demonstrate how to use it to precisely quantify the expected shot noise SNR limit difference between time-domain and Fourier-domain OCT systems in a given hypothetical experiment. The second model is used to demonstrate how USAF 1951 test chart images should be interpreted for a given lateral PSF shape. Direct numerical modeling is an easy and powerful basic tool for researchers and developers, the wider use of which may improve the rigor of the OCT literature. Full article

Facing the significant challenge of 3D object detection in complex weather conditions and road environments, existing algorithms based on single-frame point cloud data struggle to achieve desirable results. These methods typically focus on spatial relationships within a single frame, overlooking the semantic correlations and spatiotemporal continuity between consecutive frames. This leads to discontinuities and abrupt changes in the detection outcomes. To address this issue, this paper proposes a multi-frame 3D object detection algorithm based on a deformable spatiotemporal Transformer. Specifically, a deformable cross-scale Transformer module is devised, incorporating a multi-scale offset mechanism that non-uniformly samples features at different scales, enhancing the spatial information aggregation capability of the output features. Simultaneously, to address the issue of feature misalignment during multi-frame feature fusion, a deformable cross-frame Transformer module is proposed. This module incorporates independently learnable offset parameters for different frame features, enabling the model to adaptively correlate dynamic features across multiple frames and improve the temporal information utilization of the model. A proposal-aware sampling algorithm is introduced to significantly increase the foreground point recall, further optimizing the efficiency of feature extraction. The obtained multi-scale and multi-frame voxel features are subjected to an adaptive fusion weight extraction module, referred to as the proposed mixed voxel set extraction module. This module allows the model to adaptively obtain mixed features containing both spatial and temporal information. The effectiveness of the proposed algorithm is validated on the KITTI, nuScenes, and self-collected urban datasets. The proposed algorithm achieves an average precision improvement of 2.1% over the latest multi-frame-based algorithms. Full article

The receptor for advanced glycation end-products (RAGE) has a central function in orchestrating inflammatory responses in multiple disease states including chronic obstructive pulmonary disease (COPD). RAGE is a transmembrane pattern recognition receptor with particular interest in lung disease due to its naturally abundant pulmonary expression. Our previous research demonstrated an inflammatory role for RAGE following acute exposure to secondhand smoke (SHS). However, chronic inflammatory mechanisms associated with RAGE remain ambiguous. In this study, we assessed transcriptional outcomes in mice exposed to chronic SHS in the context of RAGE expression. RAGE knockout (RKO) and wild-type (WT) mice were delivered nose-only SHS via an exposure system for six months and compared to control mice exposed to room air (RA). We specifically compared WT + RA, WT + SHS, RKO + RA, and RKO + SHS. Analysis of gene expression data from WT + RA vs. WT + SHS showed FEZ1, Slpi, and Msln as significant at the three-month time point; while RKO + SHS vs. WT + SHS identified cytochrome p450 1a1 and Slc26a4 as significant at multiple time points; and the RKO + SHS vs. WT + RA revealed Tmem151A as significant at the three-month time point as well as Gprc5a and Dynlt1b as significant at the three- and six-month time points. Notable gene clusters were functionally analyzed and discovered to be specific to cytoskeletal elements, inflammatory signaling, lipogenesis, and ciliogenesis. We found gene ontologies (GO) demonstrated significant biological pathways differentially impacted by the presence of RAGE. We also observed evidence that the PI3K-Akt and NF-κB signaling pathways were significantly enriched in DEGs across multiple comparisons. These data collectively identify several opportunities to further dissect RAGE signaling in the context of SHS exposure and foreshadow possible therapeutic modalities. Full article

This paper presents an overview of the status and future prospects of fuel-cell electric vehicles (FC-EVs). As global concerns about emissions escalate, FC-EVs have emerged as a promising substitute for traditional internal combustion engine vehicles. This paper discusses the fundamentals of fuel-cell technology considering the major types of fuel cells that have been researched and delves into the most suitable fuel cells for FC-EV applications, including comparisons with mainstream vehicle technologies. The present state of FC-EVs, ongoing research, and the challenges and opportunities that need to be accounted for are discussed. Furthermore, the comparison between promising proton-exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) technologies used in EVs provides valuable insights into their respective strengths and challenges. By synthesizing these aspects, the paper aims to provide a comprehensive understanding and facilitate decision-making for future advancements in sustainable FC-EV transportation, thereby contributing to the realization of a cleaner, greener, and more environmentally friendly future. Full article

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to match natural cloud shapes. This model is intended to run quickly, and it can run in about 700 ms per cloud type. This model generates clouds that appear to match large-scale satellite imagery, and it reproduces natural small-scale shapes. This should enable future versions of ASSET to generate scenarios where the same scene is consistently viewed from both GEO and LEO satellites from multiple perspectives. Full article

A lithium-ion battery–ultracapacitor hybrid energy storage system (HESS) has been recognized as a viable solution to address the limitations of single battery energy sources in electric vehicles (EVs), especially in urban driving conditions, owing to its complementary energy features. However, an energy management strategy (EMS) is required for the optimal performance of the HESS. In this paper, an EMS based on the particle swarm optimization (PSO) of the fuzzy logic controller (FLC) is proposed. It aims to minimize battery current and power peak fluctuations, thereby enhancing its capacity and lifespan, by optimizing the weights of formulated FLC rules using the PSO algorithm. This paper utilizes the battery temperature as the cost function in the optimization problem of the PSO due to the sensitivity of lithium-ion batteries (LIBs) to operating temperature variations compared to ultracapacitors (UCs). An evaluation of optimized FLC using PSO and a developed EV model is conducted under the Urban Dynamometer Driving Schedule (UDDS) and compared with the unoptimized FLC. The result shows that 5.4% of the battery’s capacity was conserved at 25.5 ${}^{\circ }$C, which is the highest operating temperature attained under the proposed strategy. Full article

This study presents an optimization of the process parameters for the effect of copper (Cu) donor material percentage on the friction stir welding (FSW) of AA6061-T6 alloy. Extensive factorial experiments were conducted to determine the significance of the rotational speed (ω), the transverse speed (v), the interface coefficient of friction (μ), and the Cu donor material percentage in the plunge, left, right, and downstream zones. Design Expert 13 software was used to identify the number of simulation experiments to be conducted using the Abaqus simulation software. From Design Expert 13, which is a thorough multi-objective optimization analysis software, we were able to identify ideal welding parameters such as a rotational speed of 1222 rpm, transverse speed of 1.1 mm/s, the coefficient of friction of 0.9, and a 19% donor material percentage for the plunge zone. Significant findings demonstrate that increasing the Cu donor material substantially reduced the temperature from 502 °C to 134 °C when the Cu content is increased from 0% to 50%. This integrated modeling and optimization approach provides a practical procedure to identify the best experimental parameters for the process and a new understanding to guide advances for high-quality FSW of aluminum alloys. This work offers a methodology for optimizing the FSW parameters aligned with multifaceted thermomechanical physics. Full article

With the increasing warming of the Arctic, the summertime ice-free period in the coastal Arctic becomes longer and the water exchange between arctic lagoons and coastal Beaufort Sea becomes more important for land–ocean interaction. This study examined the dynamics of water exchange between the arctic lagoons and the Arctic Ocean under the influence of weather systems (the transient arctic cyclones and hovering Beaufort High pressure system). We implemented rare observations, numerical modeling with the Finite Volume Community Ocean Model (FVCOM), and a forcing-response Empirical Orthogonal Function (fr-EOF) analysis to determine the weather-driven flow patterns and characteristics in the micro-tidal arctic lagoon (Elson Lagoon) with little freshwater discharge. The results were validated for both tidal and subtidal currents with in situ data. The inlets of the lagoon were significantly impacted by wind associated with the weather systems and the flows through the inlets were highly correlated with each other. The fr-EOF analysis for the 1.5-month FVCOM output indicated three significant modes of wind-driven flow. In the deepest (~16 m) northwestern-most inlet, a counter-wind flow occurred more than 96% of the time due to setup and set down of water level inside the lagoon and the vorticity balance related to the wind stress and water depth. For about 60–80% of the time, the exchange flow was out of the lagoon through the northwestern-most and deepest inlet due to the strong easterly winds dictated by the Beaufort High; this dominant flow is mainly caused by the persistent easterly wind as a limb of the Beaufort High pressure system, modified by the transient arctic cyclones with a westerly wind and inward flows at the westernmost inlet of Elson Lagoon. This study shows that the alternating influence from the cyclone-anticyclone weather systems produces a meteorological tide in the subtidal spectrum which dominates the water exchange in the region through the multiple inlets. With the observed increase in cyclone strength and frequency under the warming trend, this may imply a greater contribution from the westerly wind because of the increased cyclonic activities. If this is the case, the inward flow might increase and have an effect on sediment, larval, and nutrient transports through this system. Full article

Bark beetle outbreaks damage forests and kill trees worldwide, but many aspects of their dynamics remain unexplained. Our aim was to identify predictors for individual tree deaths within the small (0.7 km²) Plešné Lake catchment in the Šumava National Park in southwestern Czechia. Within this area, >60,000 trees were geo-referenced and categorized from ten aerial images (20 cm spatial resolution) between 2000 and 2015. For each year for which aerial images were available, we calculated tree densities of different categories and diameters. Tree height was evaluated by means of LiDAR in two terrestrial campaigns (2010 and 2011). A machine learning technique was then used to evaluate the most important variables. The resulting relationships were largely nonlinear and differed among years; however, individual trait tree height proved to be the most influential variable in each year. Higher trees were more likely to have died during either the undisturbed phase (2000 and 2003), the disturbed phase (2005–2011), or the recovery phase (2013). Our results indicate that salvage logging may not be the most effective measure for protecting trees in small catchments. Full article

The accuracy of passive hyperbolic localization applications using Time Difference of Arrival (TDOA) measurements can be severely compromised in non-line-of-sight (NLOS) situations. Consensus functions have been successfully used to provide robust and accurate location estimates in such challenging situations. In this paper, a fast branch-and-bound computational method for finding the global maximum of consensus functions is proposed and the global convergence property of the algorithm is mathematically proven. The performance of the method is illustrated by simulation experiments and real measurements. Full article

Assessing urban service locations is a key issue within city planning, integral to promoting the well-being of citizens, and ensuring effective urban development. However, many current approaches emphasize spatial analysis focused solely on physical attributes, neglecting the equally vital social dimensions essential for enhancing inhabitants’ comfort and quality of life. When social factors are considered, they tend to operate at smaller scales. This paper addresses this gap by prioritizing integrating social factors alongside spatial analysis at the community level. By employing space syntax theory, this study investigates urban service suitability in Hajjah, a Palestinian urban community, presenting a novel approach in the literature. The research identifies good spots for essential governmental facilities like health clinics and fire stations using axial map analysis. It also suggests reallocation for some schools. Additionally, it shows ways to improve the placement of community amenities, finding ideal park locations but suboptimal mosque placements. Commercial services also exhibit areas for enhancement including gas stations and shops. The insights from this research can offer policymakers and planners insights to create more efficient, equitable, and accessible cities. The research approach incorporates social behavior dynamics into spatial analysis, promoting inclusive urban planning. Full article

The Mediterranean diet (MD), rich in minimally processed plant foods and in monounsaturated fats but low in saturated fats, meat, and dairy products, represents one of the most studied diets for cardiovascular health. It has been shown, from both observational and randomized controlled trials, that MD reduces body weight, improves cardiovascular disease surrogates such as waist-to-hip ratios, lipids, and inflammation markers, and even prevents the development of fatal and nonfatal cardiovascular disease, diabetes, obesity, and other diseases. However, it is unclear whether it offers cardiovascular benefits from its individual components or as a whole. Furthermore, limitations in the methodology of studies and meta-analyses have raised some concerns over its potential cardiovascular benefits. MD is also associated with characteristic changes in the intestinal microbiota, mediated through its constituents. These include increased growth of species producing short-chain fatty acids, such as Clostridium leptum and Eubacterium rectale, increased growth of Bifidobacteria, Bacteroides, and Faecalibacterium prausnitzii species, and reduced growth of Firmicutes and Blautia species. Such changes are known to be favorably associated with inflammation, oxidative status, and overall metabolic health. This review will focus on the effects of MD on cardiovascular health through its action on gut microbiota. Full article

Yaks are the main pillar of plateau animal husbandry and the material basis of local herdsmen’s survival. The level of mineral elements in the body is closely related to the production performance of yaks. In this study, we performed a comprehensive analysis of rumen epithelial morphology, transcriptomics and metagenomics to explore the dynamics of rumen functions, microbial colonization and functional interactions in yaks from birth to adulthood. Bacteria, eukaryotes, archaea and viruses colonized the rumen of yaks from birth to adulthood, with bacteria being the majority. Bacteroidetes and Firmicutes were the dominant phyla in five developmental stages, and the abundance of genus Lactobacillus and Fusobacterium significantly decreased with age. Glycoside hydrolase (GH) genes were the most highly represented in five different developmental stages, followed by glycosyltransferases (GTs) and carbohydrate-binding modules (CBMs), where the proportion of genes coding for CBMs increased with age. Integrating host transcriptome and microbial metagenome revealed 30 gene modules related to age, muscle layer thickness, nipple length and width of yaks. Among these, the MEmagenta and MEturquoise were positively correlated with these phenotypic traits. Twenty-two host genes involved in transcriptional regulation related to metal ion binding (including potassium, sodium, calcium, zinc, iron) were positively correlated with a rumen bacterial cluster 1 composed of Alloprevotella, Paludibacter, Arcobacter, Lactobacillus, Bilophila, etc. Therefore, these studies help us to understand the interaction between rumen host and microorganisms in yaks at different ages, and further provide a reliable theoretical basis for the development of feed and mineral element supplementation for yaks at different ages. Full article

The forest–atmosphere exchange of carbon and water is regulated by meteorological conditions as well as canopy properties such as leaf area index (LAI, m² m⁻²), photosynthetic capacity (PC μmol m⁻² s⁻¹), or surface conductance in optimal conditions (G_{s, opt}, mmol m⁻² s⁻¹), which can vary seasonally and inter-annually. This variability is well understood for deciduous species but is poorly characterized in evergreen forests. Here, we quantify the seasonal dynamics of a temperate evergreen eucalypt forest with estimates of LAI, litterfall, carbon and water fluxes, and meteorological conditions from measurements and model simulations. We merged MODIS Enhanced Vegetation Index (EVI) values with site-based LAI measurements to establish a 17-year sequence of monthly LAI. We ran the Community Atmosphere Biosphere Land Exchange model (CABLE-POP (version r5046)) with constant and varying LAI for our site to quantify the influence of seasonal canopy dynamics on carbon and water fluxes. We observed that the peak of LAI occurred in late summer–early autumn, with a higher and earlier peak occurring in years when summer rainfall was greater. Seasonality in litterfall and allocation of net primary productivity (F_NPP) to leaf growth (a_f, 0–1) drove this pattern, suggesting a complete renewal of the canopy before the timing of peak LAI. Litterfall peaked in spring, followed by a high a_f in summer, at the end of which LAI peaked, and PC and G_s,opt reached their maximum values in autumn, resulting from a combination of high LAI and efficient mature leaves. These canopy dynamics helped explain observations of maximum gross ecosystem production (F_GEP) in spring and autumn and net ecosystem carbon loss in summer at our site. Inter-annual variability in LAI was positively correlated with Net Ecosystem Production (F_NEP). It would be valuable to apply a similar approach to other temperate evergreen forests to identify broad patterns of seasonality in leaf growth and turnover. Because incorporating dynamic LAI was insufficient to fully capture the dynamics of F_GEP, observations of seasonal variation in photosynthetic capacity, such as from solar-induced fluorescence, should be incorporated in land surface models to improve ecosystem flux estimates in evergreen forests. Full article

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO${}_2$ integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed. Full article