Search Results (507)

Electro-optical bunch arrival time measurement is a method to monitor the timing of bunches in predominantly linear electron accelerators to below femtosecond precision. Despite the method being well established, a stable and fully available measurement was reported only recently. DESY’s free-electron lasers FLASH and EuXFEL feature Bunch Arrival Time (BAM) diagnostics that serve as a standard operation data source for the facility’s longitudinal fast and slow stabilization, as well as an instrument available to the users for pump laser alignment and offline analysis. A comprehensive upgrade and R&D effort targeting the performance of DESY’s BAM was carried out in recent years. The complexity of the device poses challenges to its control layer, calibration, drift control, and operation setup. Solving these proved to be essential in reaching operational stability and high availability. We report on the updates to the BAM controls and the development of automation of numerous tasks that contributed a great deal to achieving long-term stability and full run availability. Full article

The persistent challenge of creating stable de Sitter vacua within string theory undermines the observational validity of the $\Lambda$ cold dark matter (CDM) model. This difficulty suggests that the concordance model of cosmology, characterized by a constant dark energy $\Lambda$, may reside in the swampland of inconsistent quantum gravity theories rather than the string landscape of consistent ones. Recent observational data, particularly from the Dark Energy Spectroscopic Instrument (DESI), have significantly challenged $\Lambda$CDM cosmology. Specifically, the combination of DESI baryon acoustic oscillation measurements with cosmological surveys seems to indicate a preference for a dynamic, time-evolving dark energy rather than a constant, with roughly 10% reduction in density over the last several billion years. This review summarizes significant advancements made over the past two years in linking DESI findings to string-inspired scenarios. Full article

The quest for a theoretical framework and ingredients that capture our current understanding of the cosmos has motivated the design of a large number of highly informative experiments, generating an abundant flow of data. Given this quantity of data and the need for thorough analysis, the main aim of this work is to present and assess the Particle Swarm Optimization (PSO) algorithm as a complementary tool to conventional cosmological data analysis techniques. PSO is one of the most representative bio-inspired algorithms, offering good robustness for high-dimensional or complex problems while remaining relatively simple to implement and requiring only a few hyperparameters. In this study, we employ two standard variants of the canonical PSO algorithm—global best and local best—to investigate dark energy models using measurements of Type Ia Supernovae and Baryon Acoustic Oscillations, focusing in particular on the DESI and DESI + Union3 datasets. Our findings demonstrate that PSO effectively recovers the best-fit parameters from observational data and show that, under suitable conditions, PSO can achieve results comparable to those of traditional MCMC techniques, but in a significantly reduced computation time. Moreover, the solutions obtained with PSO can be used as high-quality initial conditions for MCMC analyses, thereby accelerating their convergence. Full article

Digital transformation is increasingly recognized as an important enabler of sustainable development and competitiveness in small- and medium-sized enterprises (SMEs). However, evidence on how different dimensions of digital transformation relate to the achievement of Sustainable Development Goals (SDGs) remains limited. This study explores the relationship between digital transformation and selected Sustainable Development Goals (SDGs) using an explanatory sequential mixed-methods design, in which quantitative findings informed the subsequent qualitative exploration and interpretation of managerial perspectives. The quantitative phase combined data from Eurostat’s ICT Usage Survey (2020–2024), including 60 sustainability-related indicators, with an analysis of the relationship between the Digital Economy and Society Index (DESI) and selected SDG indicators across 27 EU member states using Spearman’s rank correlation. The quantitative analysis suggests that Slovenia performs close to the EU average in overall digitalization, while significant associations were identified between digitalization and SDG 9. The qualitative phase consisted of semi-structured interviews with managers from ten Slovenian SMEs from different sectors. The findings indicate that managers perceive digital technologies, process digitalization, data-driven decision-making, and employee digital competencies as important contributors to sustainability-related outcomes, particularly in relation to SDG 8, SDG 9, SDG 12, and SDG 13. The study contributes to the literature on sustainability-oriented digital transformation in SMEs by integrating quantitative benchmarking with managerial perspectives. The findings highlight the importance of organizational capabilities, digital competencies, and strategic alignment in translating digital transformation initiatives into sustainability-related outcomes. The results provide practical implications for SMEs and policymakers seeking to support sustainable and digitally enabled business development. Full article

We present a statistical study of low-surface-brightness (LSB) tidal structures in two large samples of edge-on disk galaxies. Our primary sample comprises 5606 galaxies from the Edge-on Galaxies In SDSS (EGIS) catalog, analyzed using imaging from the DESI Legacy Imaging Surveys, supplemented by Hyper Suprime-Cam Subaru Strategic Program (HSCSSP) data and deep Apache Point Observatory (APO) follow-up observations for selected objects. To assess the robustness of our results, we also examine an independent sample of 14,237 galaxies from the Edge-on Galaxies in the Pan-STARRS survey (EGIPS) catalog. All images were processed using a homogeneous procedure optimized for the detection of faint diffuse emission. Tidal structures were identified through visual inspection and classified into established morphological categories, with careful treatment of imaging artifacts and galactic cirrus contamination. We detected tidal features in 324 EGIS galaxies and 690 EGIPS galaxies, corresponding to incidence rates of 5.8% and 4.8%, respectively. Restricting the analysis to completeness-limited subsamples yields consistent fractions of 6.4% and 6.2%. At a typical DESI r-band surface-brightness depth of 28.6 mag arcsec⁻², these values are consistent with previous observational studies but lower than predictions from many cosmological simulations. Recent high-resolution simulations, however, produce incidence rates much closer to those measured here, suggesting that numerical resolution, realistic modeling of observational and instrumental effects, and galaxy formation physics are all critical for accurately predicting the abundance of LSB tidal structures. Full article

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring. Full article

Radial brightness profiles of disk galaxies often exhibit so-called breaks—locations where their exponential-scale length abruptly changes. Some galaxies have downbending (Type II) breaks, where their brightness decays faster in outer regions, while other have upbending (Type III) breaks, resulting in more extended outer disks or envelopes. Disk radial profiles without any breaks (Type I) appear to constitute a minority. The exact fractions of different break types depend on many galactic parameters—such as Hubble type, stellar mass, spatial environment, and bar presence—and vary significantly across different studies. Another source of discrepancy is the orientation of galaxies: projection effects may play an important role in break detectability. In this work, we utilize DESI Legacy DR10 imaging to perform photometric decomposition of a sample of 375 edge-on galaxies and investigate their radial breaks. We find that the vast majority (≈90%) of disks in our sample have Type II breaks, which is a considerably higher fraction than in many previous works (∼50%). We carefully tested our results to check if observed breaks can be a result of flaring or two-disk composition. We showed that a high fraction of Type II breaks can be attributed to projection effects, which enhance the observed surface brightness of breaks in edge-on galaxies. Full article

Urbanization in Northern Nigeria has accelerated the adoption of modern architectural forms that often neglect climatic responsiveness and indigenous cultural values. This study examines how vernacular architectural principles can be integrated into contemporary urban development to enhance climate resilience. Focusing on Sokoto, Katsina, and Kano, the research adopts a mixed-methods approach combining field measurements, simulation modeling, structured interviews, and policy analysis. Findings indicate that traditional Hausa architecture achieves indoor temperature reductions of 4–6 °C compared to ambient outdoor conditions. This is primarily due to courtyard configurations, high thermal mass, and passive ventilation strategies associated with the architecture. Life-cycle assessment reveals that vernacular materials exhibit 60–75% lower embodied energy than modern buildings. Despite these advantages, policy frameworks inadequately support their integration. This study proposes an integrative model combining vernacular strategies with modern technologies and policy reforms. The findings contribute to sustainable urban design discourse and align with global sustainability goals. Full article

We present the EGIDE (Edge-on Galaxies in the DESI survey) project—a catalog of 149,215 edge-on galaxy candidates created using the data of the DESI Legacy Imaging Survey DR10 images. The catalog size is ten times greater than its predecessor and covers more than half of the sky. It is constructed in an automatic way, utilizing the full power of manual annotations from the GalaxyZoo volunteers, implemented in the Zoobot neural model, which was fine-tuned to search for edge-on galaxies specifically. To ensure the credibility of the dataset, subsequent manual supervision was performed. The EGIDE catalog provides homogeneous SExtractor photometry in the $griz$ bands, total stellar mass estimates, redshifts for 98% of the sample, star formation rates, and other information. All of this is publicly available at The Edge-on Galaxy Database site. The preliminary analysis focused on differences between edge-on galaxies in the so-called blue sequence and red cloud populations. These galaxies demonstrate distinct properties: the number of redder galaxies decreases with increasing $a/b$ ratio faster than that of the bluer galaxies; galaxy thickness varies with galaxy color: red sequence galaxies are thicker than blue cloud galaxies; the flattening ratio $q=b/a$ increases significantly with total stellar mass $M_{★}$ only among redder cloud galaxies. It is an intriguing result that the same trend of q increasing at the high-mass end is detected by both the statistical models of figures of revolution and direct observations of edge-on galaxies in EGIDE independently. The full extent of this relationship’s validity can only be determined after properly accounting for the contributions of the bulge and the PSF. Full article

Background: Recent technology improvements have enabled desorption electrospray ionisation (DESI) mass spectrometry imaging to achieve down to 5 µm (pixel) image resolution. However, operating at this resolution introduces challenges, particularly regarding increased total analysis time and the need for sufficient instrument sensitivity to detect analytes from very small tissue areas. Methods: High mass and image resolution DESI imaging was performed on rat brain tissue using a Xevo™ MRT benchtop mass spectrometer equipped with a multi-reflecting time-of-flight mass analyser and a DESI XS source. Data acquisition was conducted at speeds of up to 100 Hz. Sensitivity was assessed using a dilution series of five Active Pharmaceutical Ingredients (APIs) spotted onto porcine liver tissue. Signal detection limits were evaluated using extracted ion chromatograms (XICs) with signal-to-noise (S/N) calculations against blank samples. Additionally, enhanced duty cycle (EDC) was applied to evaluate improvements in analyte signal intensity across specific mass ranges in both positive and negative ionisation modes. Results: At acquisition speeds of up to 100 Hz, excellent data quality was achieved, with signal intensity remaining suitable for analytical applications. All five tested APIs were detectable at concentrations of 25 pg/mm². Three of the five compounds were further detected at concentrations as low as 2.5 pg/mm², with signal-to-noise ratios greater than 5. The application of EDC resulted in a significant increase in analyte signal intensity within the targeted mass ranges, particularly for small molecule endogenous metabolites and lipids, in both ionisation modes. Furthermore, the system demonstrated substantially improved spectral quality, achieving mass resolution up to 100,000 FWHM. This enabled the resolution of previously indistinguishable analytes with significantly improved mass accuracy compared to systems operating at approximately 30,000 FWHM. Conclusions: The Xevo™ MRT mass spectrometer with DESI XS source enables high-resolution DESI imaging at speeds up to 100 Hz without compromising data quality or sensitivity. The system demonstrates excellent detection limits for pharmaceutical compounds and improved performance through enhanced duty cycle operation. Overall, the combination of high spatial resolution, increased mass resolution, and improved spectral quality allows for more accurate analyte differentiation, representing a significant advancement over lower-resolution systems. Full article

Psilocybin, a psychedelic drug with reported anxiolytic and antidepressant potential, is rapidly metabolized to its active metabolite psilocin. However, a lack of adequate toxicity studies and tissue distribution studies currently restricts its development and application. This study combined behavioral assays in zebrafish with desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to systematically evaluate the acute neurotoxicity of psilocybin and characterize the in vivo spatial distribution of its active metabolite, psilocin. The novel tank test was used to evaluate zebrafish following a 4 h exposure to psilocybin at three different doses (20, 40, and 80 μM; n = 6 per group). Statistical analysis of the data was performed using ANOVA. Behavioral analyses revealed that exposure to psilocybin induced pronounced neurobehavioral alterations, including hyperactivity and disrupted swimming patterns, as evidenced by significant increases in the number of zone transitions and shuttle frequency. We established a DESI-MSI-based method for quantitative mapping and visualization of psilocin in zebrafish tissues. Methodological validation indicated that a linear relationship between ion intensity, spotted amount (R² = 0.9947), and reproducibility (RSD < 15%) is suitable for quantitative analysis of psilocin in zebrafish tissues. Spatial distribution maps showed that following continuous exposure for 4 h, psilocin was widely distributed across multiple tissues, such as the eye, brain, heart, liver, and kidney, with marked accumulation in the brain and the periportal regions of the liver. Relative psilocin signal intensity revealed a dose-dependent increase in tissue drug levels. The dose-dependent increase in both behavioral hyperactivity and brain psilocin levels points to a consistent relationship, in line with a central site of action. Collectively, these findings demonstrate that DESI-MSI provides a visual and efficient strategy for studying drug distribution in biological tissues from exposed animals. The neurobehavioral toxicity phenotypes and distinct tissue distribution patterns of psilocin uncovered in this study offer critical insights into the biological effects and potential risks of this psychoactive substance. Full article

We consider a two-field chiral cosmological model of inflation connected with induced gravity. It is shown that the constructed inflationary model does not contradict recent observational data from the Atacama Cosmology Telescope (ACT) and the Dark Energy Spectroscopic Instrument (DESI). The corresponding values of the model parameters are determined. This model is suitable for the formation of primordial black holes (PBHs). The estimation of PBH masses allows us to consider these PBHs as dark matter candidates. Full article

We present a method for quantifying ultrashort pulse-shape instability in a train of pulses using multi-shot second-harmonic-generation frequency-resolved optical gating (SHG FROG). All versions of multi-shot FROG have previously shown the ability to qualitatively distinguish stable from unstable pulse trains, as systematic differences appear between measured and retrieved FROG traces when instability is present. This has proved possible because the recently introduced retrieved-amplitude N-grid algorithmic (RANA) approach provides highly reliable pulse retrieval, even for unstable pulse trains and in the presence of noise, thereby eliminating the possibility that algorithm stagnation, which also yields such systematic differences, could be confused for such instability. In other words, RANA’s excellent performance ensures that any non-random discrepancies between measured and retrieved FROG traces reflect physical pulse-shape instability rather than algorithmic stagnation. To quantify such instability, we now introduce an instability parameter, $R$. It involves an extension of the well-known statistical “Runs” test, which has been used for decades to test for systematic error in fits to one-dimensional (1D) data. A runs test counts the “runs”—consecutive points in the plot of the difference between the data and fit with the same sign (+ or −), yielding an evaluation of the goodness of the fit, largely independent of random error. Specifically, the more runs, the better the fit. However, because FROG traces are functions of two variables, we must extend the usual 1D runs test to two dimensions, that is, to enumerate the 2D runs—“hills” and “valleys” in the difference between measured and retrieved 2D FROG traces. Many small 2D runs indicate only random noise-like differences, that is, a good fit, and, hence, a stable pulse train, whereas few large runs reflect systematic error, that is, a poor fit, and, hence, pulse-shape instability. Finally, because random noise could contribute numerous meaningless runs in the wings of a FROG trace, where the intensity is near zero, we must also weight each hill and valley by its average measured trace intensity in order to minimize its effects. We show that R is intuitive and reasonable and, in addition, is independent of pulse complexity and trace size. As a result, it provides a clear metric of pulse-shape stability vs. instability. Full article

The functionality of ionomeric membranes is influenced by small changes of several parameters. Aqueous network formation by phase separation between the hydrophilic and hydrophobic parts of the polymer is one critical factor for water and ion transport. In particular, the transport of highly charged ions like ${\mathrm{V}}^{3+}$ is not well understood. The unsteady diffusion in Nafion, a sulfonic acid based cation exchange polymer, using ${\mathrm{V}}^{3+}$ profiles obtained with micro X-ray fluorescence ($0.5 \mathsf{\mu }$m spot over a $180 \mathsf{\mu }$m scan) yields a diffusion coefficient of $4\times {10}^{-13} {\mathrm{m}}^2{\mathrm{s}}^{-1}$ at ${\lambda }_{H_{2}O/S{O}_3}=12$ and at ca. $20 °$C. It is confirmed that the concentration profile can be described by an error function formalism. The diffusivity, determined from the entire profile, represents mainly the transport into a vanadium free environment with very low ionic strength as the membrane was conditioned in ultra-pure water. The macroscopic ion transport is influenced by local molecular interactions, interconnection of water pockets and long range ionic interactions. The local interactions of ${\mathrm{V}}^{3+}$ were studied using molecular dynamics (MDs) simulations. The MD simulation studies diffusion at a constant ion concentration and short length scale (ca. 30 nm). It gives insights on the effects of dissolved ${\mathrm{V}}^{3+}$ ions on the local structure. Radial distribution functions reveal that at low hydration, the vanadium ions have an ordering effect on water molecules. The diffusion coefficient of ${\mathrm{V}}^{3+}$ is determined on a molecular level from the mean-square displacement yielding $2.5\times {10}^{-10} {\mathrm{m}}^2{\mathrm{s}}^{-1}$ for ${\mathrm{V}}^{3+}$ ions at a membrane water content of ${\lambda }_{H_{2}O/S{O}_3}$ = 6. The phenomenon in which the diffusivity decreases over longer length scales was documented before for water and ${\mathrm{H}}^{+}$ in Nafion; however, this was by only about one order of magnitude. The experimental microscopic approach described by us is universally applicable, e.g., to environments of higher ionic strength, ions with different charges, and different types of ion-exchange membranes. Longer diffusion times allow us to distinguish between different concentration regimes. Full article

The accelerating energy transition and digital transformation have increased the importance of understanding the drivers of energy-related entrepreneurship and investment across countries. This study aims to investigate how digitalisation and entrepreneurial ecosystem development influence the number and funding of energy-related start-ups, with particular attention to stage-specific effects, lagged dynamics, and non-linear relationships in a cross-country panel setting. The analysis is based on panel data from the European Commission (DESI), the International Energy Agency, and StartupBlink, covering 25 countries (2017–2022) and a global sample (2019–2023), and is estimated using Poisson pseudo-maximum likelihood models with fixed effects, lagged variables, and non-linear specifications in R. The findings show that digitalisation has a limited, selective relationship with energy-related entrepreneurship, whereas entrepreneurial ecosystem development plays a more consistent role. Digital connectivity is associated mainly with improved early-stage funding conditions, whereas broader digitalisation indicators do not systematically explain start-up formation. Stronger entrepreneurial ecosystems are linked to both higher green start-up activity and a shift in investment from early-stage ventures to more mature digital energy firms. The non-linear results further suggest diminishing returns to ecosystem development in later-stage green funding, indicating potential saturation effects in highly developed ecosystems. These findings suggest that policies aimed at accelerating sustainable energy entrepreneurship should go beyond general digitalisation strategies and focus more directly on strengthening inclusive entrepreneurial ecosystems, improving access to finance across the start-up lifecycle, and preventing excessive investment concentration in already mature ventures. Full article