742875 research outputs found
Sort by
N-body simulations meet ML for structure detection and analysis
No full textRecent advances in memory and processing power on small-scale computers enable new algorithms tailored to their capabilities. In astrophysics, two key tools benefit greatly: N-body simulations, which model systems of many interacting bodies and are used to study large-scale structure formation, test dark matter models, and analyze galaxy mergers and halos; and structure detection, which identifies galaxies, dark matter halos, filaments, walls, voids, and star-forming regions within the cosmic web.This thesis has two main parts. The first introduces QUANTIZER, a new N-body simulation designed specifically for small-scale devices. The second enhances 1-DREAM, a toolkit of machine-learning algorithms. These updates include an innovative core design for the N-body code and ideas drawn from swarm intelligence, evolutionary computation, and probabilistic modeling. As a result, 1-DREAM more effectively detects, extracts, and models one-dimensional structures in complex datasets. We tested these methods on simulations of the cosmic web, galaxy collisions, synthetic datasets, and other systems, comparing their performance with established tools to evaluate accuracy and efficiency across varied scenarios.After strengthening both methodologies, we unified them into a single framework. QUANTIZER was used to simulate galaxy collisions, while 1-DREAM analyzed the resulting stellar streams and their evolution. This combined approach enables the study of astrophysical structures not only in space but also through time, offering a clearer and more dynamic view of their development. It reveals subtle patterns previously inaccessible and supports a deeper understanding of complex cosmic behavior
Corrigendum to: “Synergistic antifungal effects of the preservative ammonium propionate and medium chain fatty acids against dormant and germinating conidia, germ tubes and hyphae of Aspergillus chevalieri, a feed spoilage fungus” (International Journal of Food Microbiology, (2024), 422, C, (110802)
No full textThe authors are happy to insert the following link. To obtain the large-scale EM-data presented in this paper at full resolution (nanotomy) please click to following link: http://www.nanotomy.org/OA/Dijksterhuis2024IJFM/index.html. The authors are indebted to make the data as transparent as possible and would like to use this opportunity to offer this possibility.</p
The role of defenders' and victims' popularity in the effectiveness of defending in bullying interactions:A longitudinal social network study
No full textPeer defending is widely promoted as a strategy to reduce bullying, but few studies have investigated whether having more defenders decreases victimization over time from the victim's perspective. This social network study examined the longitudinal association between nominating more defenders and subsequent victimization among (early) adolescents and tested whether this relation is moderated by the popularity status of the defender and the victim. The sample included 1450 participants from 93 secondary school classes (grades 4–9) in Finland (52.51% female; Mage = 12.38 years, SDage = 1.56). Results from longitudinal social network analyses showed that contrary to expectations, having more defenders did not reduce victimization over time. Moreover, the popularity of the defender or the victim did not moderate this effect. Results did not differ by grade. These findings suggest that defending alone may not protect students from ongoing victimization and highlight the need for broader, multi-level intervention strategies.</p
Age disparities in SGLT2 inhibitor prescription among people with type 2 diabetes: The role of frailty and sex
No full textBackgroundOlder adults with type 2 diabetes (T2DM) are less likely to receive sodium–glucose cotransporter-2 (SGLT2) inhibitors, despite their proven cardio-renal benefits and safety. Whether this age-related gap is driven by frailty, sex, or other factors remains unclear.MethodsThis observational study analysed data from adults registered in primary care during 2023, using the Groningen Initiative to Analyse Type 2 Diabetes Treatment (GIANTT) database. Eligibility for SGLT2 inhibitor treatment was determined based on the Dutch College of General Practitioners (NHG) guideline for T2DM. Prescription rates were assessed across demographics, comorbidities, and preceding medication use. Multivariable logistic regression models were used to assess the association of age and identify factors associated with SGLT2 inhibitor prescriptions.ResultsAmong 10 241 adults with T2DM, 41% (n = 4223) were eligible for SGLT2 inhibitor prescription. The prescription rate in the overall population was 15.2% and among eligible people was 25.5%. In people eligible for SGLT2 inhibitors, prescription rates were markedly lower with increasing age, with 37.6% in those aged <60 years, 32.1% in 60–69 years, 27.2% in 70–79 years, and only 13.7% in those aged ≥80 years. In multivariable analysis, compared with those aged <60 years, individuals aged 70–79 and ≥80 were associated with significantly decreased likelihood of SGLT2 inhibitor prescription, independent of frailty and other relevant covariates [odds ratio (OR): 0.56, 95%CI: 0.43–0.72] and (OR: 0.22, 95%CI: 0.16–0.30), respectively. Age disparities in SGLT2 inhibitor prescription were evident across subgroups, including different levels of frailty and both sexes, with disparities particularly pronounced in females compared with males (pinteraction = 0.01). Females had lower prescription rates than males across age groups and levels of frailty.ConclusionsSGLT2 inhibitor prescription rates among Dutch adults with T2DM were low, with persistent age- and sex-related disparities independent of frailty, highlighting the need for equitable prescribing
Multi-Stimulus Triggered Programmable Transformation of Molecular Motor Based Chiral Supramolecular Polymers in Water
No full textA notable characteristic of living organisms is their capacity to adapt to environmental changes and transform external signals into distinct responsiveness, facilitating the execution of diverse functions with motility as a key parameter. To better mimic such lifelike behavior, researchers have developed various supramolecular assembled systems with responsive behavior toward a variety of stimuli. However, exploiting motion along length scales and achieving collective control over the responsiveness to multiple stimuli in supramolecular systems is still challenging. Here we present the development of molecular motor based supramolecular polymers that are responsive toward multi-stimulus and exhibit multi-state assembly and chirality. Taking advantages of aldehyde functionalized motors, we realized photo-responsive supramolecular polymers featuring boosted photo-efficiency, near quantitative photoconversions, programmable behavior and responsiveness to multiple stimuli in a reversible manner in aqueous media. The various stimuli including light and different chemicals could act on the motor building blocks and subsequently trigger the transformation of the supramolecular polymers toward reversible polymerization, direct post-functionalization and chirality modulation. The interplay between the rotary molecular motion and the supramolecular systems assembly process, taking advantage of different external stimuli to govern the assembly state, provides a basis for multi-responsive supramolecular materials.</p
<sup>40</sup>Ar/<sup>39</sup>Ar chronology of sea-level change before and during the interglacial maxima of Marine Isotope Stage 13
No full textMarine Isotope Stage (MIS) 13 represents the most recent “lukewarm” interglacial within the sequence of glacial and interglacial periods that has characterized global climate over the past million years. It comprises two interglacial maxima (MIS 13.3 and MIS 13.1) and follows MIS 14.2, which is generally regarded as a weakly developed glacial period. New and existing data from the 40Ar/39Ar-dated aggradational successions of the Paleotiber drainage system provide precise constraints on the timing and nature of sea-level change before and during MIS 13. Gravel deposition and/or river incision allow identifying two sea-level lowstands, followed by glacial terminations VIb and VIa, which culminated at 533.7 ± 1.6 ka and 515.7 ± 1.3 ka and led to sea-level highstands of different magnitude and duration during interglacial maxima MIS 13.3 and MIS 13.1, respectively. MIS 13.1 featured higher sea level and lasted almost twice as long as MIS 13.3, reflecting an antiphase relationship between obliquity and precession that likely maintained warm northern high latitudes and sustained ice-sheet melting. A warmer and less glaciated Northern Hemisphere at the end of the MIS 13 interglacial supports the view that the transition from “lukewarm” to “super-interglacials” at the Mid-Brunhes Transition was preceded by a long-term shift toward warmer conditions and reduced residual continental ice in the Northern Hemisphere, reaching a maximum during MIS 13.</p
Single-photon loading of polar molecules into an optical trap
No full textWe propose a scheme to transfer molecules from a slow beam into an optical trap using only a single-photon absorption and emission cycle. The efficiency of such a scheme is numerically explored for BaF using realistic experimental parameters. The technique makes use of the state-dependent potential in an external electric field to trap molecules from an initial velocity of order 10m/s. A rapid optical transition at the point where the molecules come to a standstill in the electric field potential irreversibly transfers them into a ∼7mK optical lattice trap. For a pulsed Stark decelerated beam, we estimated the per-shot efficiency to be ∼0.52% or up to ∼104molecules, with a potential factor of 2 improvement when the fields are synchronously modulated with the arriving velocity components. The irreversibility of the scheme allows for larger numbers to be built up over time. Since this scheme does not rely on a closed cycling transition for laser cooling, it broadens the range of molecules that can be used for research on cold molecular chemistry, quantum information, and fundamental interactions in optical traps
The influence of cellular energy status, microtubules, and crowding on mitochondrial motion
No full textEukaryotic cells rely on a tightly regulated system to transport vesicles and organelles within the cell, as thermal diffusionbecomes inefficient for larger cargo. This transport system is composed of the cytoskeleton, a polymer mesh extendingthroughout the cell, together with different types of motor proteins that attach to and walk along the cytoskeleton, therebycarrying the cargo along with them. Here we used mitochondria in human cells as a model system for cargo transported bymotor proteins, followed their motion using microscopy, and analysed the trajectories. Consistent with previous studies, weobserved that the mitochondria often remain within a limited region, rattling around, for long periods of time, before finallytaking a longer jump. To elucidate the mechanisms behind this behaviour we subsequently perturbed the system. Depletionof cell energy substantially prolonged the waiting time before taking a jump, but also decreased the jump lengths and, to alesser extent, the extent of the rattling. Disruption of the microtubule network showed a more modest effect on the motion,the largest effect being an approximate doubling of the waiting time before making a jump. Similarly, increasing intracellularcrowding by osmotically compressing the cells also had a rather small effect on mitochondrial motion. Again, there was anapproximate doubling of the waiting time before making a longer jump, coupled to a more modest decrease in the extentof the rattling. Overall, our data give quantitative insights into the mechanisms underlying motor protein-driven motion and,in particular, highlights the waiting time before making a longer jump as a key parameter
Redefining Therapies for Drug-Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design
No full textABSTRACT Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern, particularly due to the emergence of multidrug-resistant and extensively drug-resistant strains. The persistence and propagation of TB are favored by the pathogen's sophisticated virulence mechanisms, its ability to evade immune responses, and the formation of latent infections within granulomas. Current therapeutic regimens are limited by long treatment durations, drug resistance, and significant socioeconomic burdens. Antimicrobial peptides (AMPs) have emerged as promising alternatives because of their broad-spectrum activity and reduced likelihood of resistance development. Nevertheless, their clinical application is hindered by rapid proteolytic degradation, low specificity and limited bioavailability. Recent advances in nanotechnology have facilitated the encapsulation and targeted delivery of AMPs, improving their therapeutic potential against TB. Furthermore, the integration of computational approaches—such as molecular docking and molecular dynamics (MD) simulations—has enabled the rational design and optimization of AMPs, expediting the discovery of novel anti-TB agents. This review summarizes the pathogenesis and resistance mechanisms of Mtb, highlights the current landscape and limitations of AMP-based therapies, and discusses the role of nanotechnology and in silico tools in the development of new treatment strategies for TB