Small-scale Changes Research Articles

Bat-Associated Pathogenic Leptospira spp. from Forest Fragments in Southwestern Brazilian Amazonia

Bats are known as potential carriers of different pathogens; these animals have been identified worldwide as an important reservoir of different species of Leptospira. Therefore, there has been an increasing interest in studying leptospirosis in neotropical bats in the Amazon. This region is a fertile ground for zoonotic diseases, given the intense process of deforestation, urbanization, opening of new agricultural frontiers, predatory hunting, effects of climate change, and loss of biodiversity. Based on this, the aim of the present study was to investigate the frequency of infection associated with the genetic characterization of pathogenic Leptospira spp. in bats inhabiting diverse landscapes in the southwestern region of the Amazon. To conduct the study, mist nets were installed to capture bats. Kidney samples were submitted to LipL32-polymerase chain reaction and secY gene sequencing. Our results showed that 21% of neotropical evaluated bats in Southwestern Amazon were infected with Leptospira spp. Positive animals were found in rural, urban, periurban, and control areas. Sanguinivores had the highest frequency of positives, followed by insectivores and frugivorous bats. The species of L. interrogans and a potential new Leptospira species were identified. The frequency of Leptospira in bats was not influenced by landscape type, suggesting these pathogens may not be affected by landscape changes. The findings suggest that bats may serve as potential reservoirs of Leptospira in diverse landscapes. The presence of Leptospira in bats appears to be independent of the type of land use, implying that these pathogens may not be affected by small-scale changes in the environment.

Predicting land use change around railway stations: An enhanced CA-Markov model

Predicting land use change around railway stations is crucial for facilitating the coordinated development of transport and land use. Previous studies have seldom focused on simulating and predicting small-scale land use changes at a railway station. Therefore, this study employs an enhanced Cellular Automata-Markov (CA-Markov) model, aiming to achieve simulations and predictions with heightened precision. Firstly, two additional driving factors, namely accessibility to railway stations and the kernel density of points of interest (POIs), are incorporated into the CA-Markov model. Secondly, the validation of the enhanced model is achieved through simulating land use changes around Dujiangyan Station. Finally, this model is applied to predict land use around Mianzhu South Station in 2026, and optimization strategies for railway station areas are proposed. The results indicate an 83.43-hectare reduction in farmland area, accompanied by a moderate increase in 35.8 hectares of forest land and 41.52 hectares of residential land. This enhanced model provides valuable technical support for strategic planning in railway station areas.

Visualizing small-scale subsurface NH3 and pH dynamics surrounding nitrogen fertilizer granules and impacts on nitrification activity

In agricultural soils, nitrogen (N) fertilizer is typically applied as ammonium salts or urea, and undergoes microbially mediated oxidation. However, insights regarding substrate concentrations nitrifiers are exposed to in the zones immediately surrounding N fertilizer granules remain unexamined, as well as how this affects the activity or inhibition of nitrifier groups adapted to different ranges of ammonia (NH3) concentrations. To examine millimeter scale changes in soil chemistry after sub-surface fertilizer granule application with high spatiotemporal resolution, we applied a newly developed NH3 and pH planar optical sensor (optode) system. With this system, we visualized in situ subsurface NH3 production, diffusion, and associated pH shifts in an agricultural soil following the application (from 5 min up to 65.5 h) of ammonium chloride (NH4Cl) or urea granules in a laboratory study. Ammonia from both NH4Cl and urea granules diffused up to 1.5 and 2 cm and reached maximum concentrations of >49 and >130 ppmv, respectively. Spatially informed destructive subsampling (0.5–2 cm from granules) revealed that nitrate accumulation was greatest closest (0.5–1 cm) to the ammonium chloride granules, while nitrite was not detected. In contrast, urea application resulted in both nitrite and nitrate accumulation, with the highest concentrations detected furthest (1.5–2 cm) from urea granules. Urea hydrolysis also caused a significant localized pH increase, while ammonium chloride caused a circular elevated pH zone migrating outwards leaving a decreased pH at the center. Transcription of the ammonia-oxidizing bacterial amoA gene was highest in areas furthest (1.5–2 cm) from the urea granules, while there were no significant differences in amoA transcription with increasing distance from the NH4Cl granules. Ammonia-oxidizing archaea and comammox amoA transcripts were not detected. This study is the first to directly visualize small-scale subsurface changes in NH3 concentration and pH after fertilizer granule application and relate these to nitrification activity.

Exploratory and seasonal movements of adult common shelducks in the eastern Wadden Sea

Habitat conditions surrounding individual birds are key components determining their fitness, notably by influencing effective foraging, escape from predators, and adaptation to changing environmental conditions. Birds living in dynamic habitats are particularly likely to have a high need to explore; however, spatial and temporal patterns of exploratory movements are poorly understood. We investigated the exploratory movements of adult common shelducks (hereafter Shelducks, Tadorna tadorna) in the Wadden Sea, which provides a dynamic habitat for birds. We captured nine shelducks in adjacent breeding areas and attached GPS satellite telemetry devices for 5–18 months, mostly covering the post-breeding period. We analyzed bird-movement patterns based on mean daily locations and behavioral change point analysis. All individuals explored on a median of 22% of tracking days (range = 6–39%). Individuals usually explored new areas for a short time before switching to stay in these areas for longer periods. Exploratory movements were particularly frequent before the start of the flightless period during molting. During this time, shelducks explored the traditional molting area in the Elbe estuary intensively. However, birds did not explore places within the area subsequently used for molting for longer or more often than other places. The molting area was used for a median of 59 days, i.e., about twice as long as required for the flightless period, suggesting that this area was explored not only to select a suitable molting place, but also for other purposes. Only two shelducks performed longer-distance exploration movements, i.e., > 45 km from their sedentary areas. We therefore concluded that exploratory movements by adult shelducks may enable the birds to adapt to small-scale changes in habitat conditions.

Cell Line-Dependent Adhesion and Inhibition of Proliferation on Carbon-Based Nanofilms.

Disorganisation of the extracellular matrix (ECM) is strongly connected to tumor progression. Even small-scale changes can significantly influence the adhesion and proliferation of cancer cells. Therefore, the use of biocompatible nanomaterials capable of supporting and partially replenishing degraded ECM might be essential to recover the niche after tumor resection. The objective of this study was to evaluate the influence of graphene, graphene oxide, fullerene, and diamond nanofilms on breast cancer and glioblastoma grade IV cell lines. Nanomaterials were characterized using SEM and TEM techniques; zeta potential analysis was also performed. Nanofilms of graphene, fullerene, and diamond nanoparticles were also characterized using AFM. The toxicity was tested on breast cancer MDA.MB.231 and glioblastoma grade IV U-87 MG cell lines, using LDH assay and by counting stained dead cells in bioprinted 3D models. The following parameters were analyzed: proliferation, adhesion to the nanofilm, and adhesion to particular ECM components covered with diamond nanoparticles. Our studies demonstrated that nanofilms of graphene and diamond nanoparticles are characterized by cell-specific toxicity. Those nanomaterials were non-toxic to MDA.MB.231 cells. After applying bioprinted 3D models, diamond nanoparticles were not toxic for both cell lines. Nanofilms made of diamond nanoparticles and graphene inhibit the proliferation of MDA.MB.231 cells after 48 and 72 hours. Increased adhesion on nanofilm made of diamond nanoparticles was only observed for MDA.MB.231 cells after 30 and 60 minutes from seeding the cells. However, analysis of adhesion to certain ECM components coated with diamond nanoparticles revealed enhanced adhesion to tenascin and vitronectin for both tested cell lines. Our studies show that nanofilm made of diamond nanoparticles is a non-toxic and pro-adhesive nanomaterial that might stabilize and partially replenish the niche after breast tumor resection as it enhances the adhesion of breast cancer cells and inhibits their proliferation.

Exploitation of SAS interferometric phase statistics for coherent change detection

AbstractCoherent change detection (CCD) takes advantage of the interferometric processing of synthetic aperture sonar (SAS) images and enables the detection of small scale changes to the scene between image pairs. This paper builds upon interferometric phase statistics developed for synthetic aperture radar and presents a method to differentiate between possible sources of decorrelation. A single‐pass pair of SAS images is categorized into four zones based on acoustic amplitude and coherence properties. Results suggest that regions of low coherence caused by a scene change can be differentiated from regions of low coherence due to other sources of decorrelation. Phase statistics could provide a technique to reduce the false alarm rate in CCD. Further studies are required to validate the approach for repeat‐pass SAS imagery and consider the effects of temporal decorrelation and misregistration errors on the phase distributions.

Meeting The Demands Of PhD Supervision By Changing Supervision Practice - A Supervisor's Reflection On Didactic Change

This article presents a PhD supervisor’s reflections on a didactic change in supervision. The change included adding digital collaborative supervision activities to meet expectations, demands, and prerequisites for PhD supervision. Small-scale changes in supervisor didactic practices, such as online monthly group meetings and online retreats, can be useful for the progress of PhD students and for improving the working situation for supervisors. Collaboration is a key feature that ensures shared responsibility, meaningful focus, and better use of both traditional and new supervision meetings and activities. Furthermore, PhD students appear to have positive outcomes regarding social life, academic belonging, academic skills, academic leadership, and academic friendship. The findings from this small, pragmatic quality improvement project provide useful insights for PhD supervision. Reflections on a supervisor’s experience from a didactic change with digital, collaborative supervision can provide useful learning relevant to other PhD supervisors, PhD students, and graduate schools.

Stable orientations of small-scale floating cylinders

A coin always floats in stable equilibrium with its longitudinal axis normal to the air–liquid interface. In contrast, a long thin cylindrical pin floats with its longitudinal axis parallel to the air–liquid interface. In this context, we present a theoretical investigation of the stability of small-scale hydrophobic cylinders floating in vertical and horizontal orientations at various aspect ratios (length/diameter). The study is limited to cylinders denser than water floating at the air–water interface. Our analysis shows that, unlike large-scale vertically floating cylinders, the stability of vertically orientated small-scale cylinders increases with an increase in aspect ratio. A similar trend is observed in the stability of small-scale horizontal cylinders. We also explain the underlying mechanics that leads to a rise in the stability of floating cylinders with an increase in aspect ratio. Unlike large-scale floating cylinders with uniform density, we show that the effect of governing forces (weight, buoyancy and surface tension) in small-scale cylinders changes from a stabilising to a destabilising force with a change in the aspect ratio. For example, in the case of a vertically floating cylinder, the buoyancy force acts as a stabilising force at a small aspect ratio whereas, at large aspect ratios, the buoyancy force has a destabilising influence. Likewise, the body's weight has a destabilising influence at a small aspect ratio and stabilising effect at a large aspect ratio. The reason behind this transformation is that, above a particular aspect ratio, the centre of gravity of small-scale floating cylinders lies below the centre of buoyancy.

Effects of a short-term temperature increase on arthropod communities associated with pastures.

The impact of climate change on islands is expected to cause dramatic consequences on native biodiversity. However, limited data are available for arthropod communities in island agroecosystems. In this study, we simulate a small-scale climatic change (average of +1.2°C), using Open Top Chambers (OTCs) in forage crops in the Azores Archipelago (Portugal) and test the responses of arthropod communities associated with intensively-managed pastures. At three sites, twenty 1 x 1 m plots were established: 10 treatment plots with OTCs and 10 control plots. Arthropods were sampled with pitfall traps on two sampling events (winter and summer of 2020). When considering all species collected, arthropods' abundance was lower in OTCs. Specific taxa, namely spiders and beetles, showed a fast response to the OTCs' presence. The assemblage of non-indigenous spiders well adapted to pastures showed a significant difference in diversity with a slightly greater richness, but lower abundance inside the warmer plots. However, the presence of OTCs resulted in a decrease in beetle richness and abundance. This decline may be attributed to the multiple effects of warming. Therefore, it is imperative to conduct further investigations to elucidate the ecological processes that underlie the observed patterns.

Sensitivity of phase difference between short-range acoustic multipaths to changes in sound speed and source depth

Ocean acoustic tomography often relies on precise clocks and knowledge of the range between acoustic instruments to estimate ocean-driven sound speed changes. In this study, we explore an alternative method utilizing the difference in the carrier phase between two broadband pulse arrivals to estimate small-scale changes in source depth and sound speed. By leveraging acoustic multipathing, this phase difference approach obviates the need to know the acoustic propagation's precise range and absolute travel time. Observations from a mid-frequency (1–10 kHz) acoustic experiment at short ranges (2–3 km) demonstrate the sensitivity of the difference in the 4 kHz carrier phase between two arrivals to changes in both source depth and sound speed. The difference in the arrival phase is modeled using measurements of the time-varying source depth and sound speed. The comparison between the modeled and observed arrival phase differences reveals a significant agreement, supporting the potential of using phase difference as a reliable estimator for perturbations in either source depth or sound speed for short-range acoustic propagation.

A Complexity-Based Plan for Evaluating Transformation

Abstract This article presents a case for more rigorous application of complexity science in our efforts to evaluate activity that seeks to bring about transformative change. It builds on the work that is already going on in the evaluation community. Three constructs from complexity science are employed – sensitive dependence, emergence, and social attractors. The paper argues that if–then logic is recommended for small-scale change within transformation efforts, but that to evaluate transformation writ large, data from if–then evaluation must be embedded in, and interpreted in terms of, complex behavior. Methodologies for evaluating within this framework are presented. The argument is linked to a definition of transformation that is multidimensional, non-linear, and measurable. The paper is built around a generic model of transformational change and shows how that model can be customized for specific transformation scenarios. It also shows how evaluation with respect to complexity can be accomplished with methodologies that are well known and well-practiced in the evaluation community.

Multimodal image matching: A scale-invariant algorithm and an open dataset

Multimodal image matching is a core basis for information fusion, change detection, and image-based navigation. However, multimodal images may simultaneously suffer from severe nonlinear radiation distortion (NRD) and complex geometric differences, which pose great challenges to existing methods. Although deep learning-based methods had shown potential in image matching, they mainly focus on same-source images or single types of multimodal images such as optical-synthetic aperture radar (SAR). One of the main obstacles is the lack of public data for different types of multimodal images. In this paper, we make two major contributions to the community of multimodal image matching: First, we collect six typical types of images, including optical-optical, optical-infrared, optical-SAR, optical-depth, optical-map, and nighttime, to construct a multimodal image dataset with a total of 1200 pairs. This dataset has good diversity in image categories, feature classes, resolutions, geometric variations, etc. Second, we propose a scale and rotation invariant feature transform (SRIF) method, which achieves good matching performance without relying on data characteristics. This is one of the advantages of our SRIF over deep learning methods. SRIF obtains the scales of FAST keypoints by projecting them into a simple pyramid scale space, which is based on the study that methods with/without scale space have similar performance under small scale change factors. This strategy largely reduces the complexity compared to traditional Gaussian scale space. SRIF also proposes a local intensity binary transform (LIBT) for SIFT-like feature description, which can largely enhance the structure information inside multimodal images. Extensive experiments on these 1200 image pairs show that our SRIF outperforms current state-of-the-arts by a large margin, including RIFT, CoFSM, LNIFT, and MS-HLMO. Both the created dataset and the code of SRIF will be publicly available in https://github.com/LJY-RS/SRIF.

A Stretchable, Conductive Thread-Based Sensor Towards Wearable Monitoring of Muscle Atrophy.

We present the first wearable sensor designed for frequent monitoring of muscle atrophy and validate performance upon canonical phantoms. Our approach relies on Faraday's law of induction and exploits the dependence of magnetic flux density on cross-sectional area. We employ wrap-around transmit and receive coils that stretch to fit changing limb sizes using conductive threads (e-threads) in a novel zig zag pattern. Changes in the loop size result in changes in the magnitude and phase of the transmission coefficient between loops. Simulation and in vitro measurement results are in excellent agreement. As a proof-of-concept, a cylindrical calf model for an average-sized subject is considered. The frequency of 60 MHz is selected via simulation for optimal limb size resolution in magnitude and phase while remaining in the inductive mode of operation. We can monitor muscle volume loss of up to 51%, with an approximate resolution of 0.17 dB and 1.58° per 1% volume loss. In terms of muscle circumference, we achieve resolution of 0.75 dB and 6.7° per centimeter. Thus, we can monitor small-scale changes in overall limb size. This is the first known approach for monitoring muscle atrophy with a sensor designed to be worn. Additionally, this work brings forward innovations in creating stretchable electronics from e-threads (as opposed to inks, liquid metal, or polymer). The proposed sensor will provide improved monitoring for patients suffering from muscle atrophy. The stretching mechanism can be seamlessly integrated into garments which creates unprecedented opportunities for future wearable devices.

The effect of small-scale changes in wealth on risk attitudes: an experimental study

PurposeThis study aims to examine the effects of prior small-scale changes to wealth on subsequent risky choices.Design/methodology/approachThe paper opted for a laboratory experiment in which subjects perform two sequences of risky tasks. In between these two sets, the author transfers money for real for a randomly selected half of the subjects. Data on choices before and after the transfer of money are used to estimate risk attitudes and analyze whether the transfer of money affected attitudes to risk.FindingsThe author finds that the money gain does not change subjects' risk preferences – neither in a within- nor in a between-subject design. This suggests that individuals' risky choices are consistent with their constant absolute (CARA) risk aversion preferences, a result that supports a key assumption in recent literature on the calibration critique of decision theories and the view that individuals engage in narrow framing.Research limitations/implicationsBecause of the relatively small transfer of money, the research results may lack generalizability.Practical implicationsThe paper includes implications for the reference-dependent and other theories that explain how prior outcomes affect risk-taking behavior in sequential problems.Social implications The results are relevant to the research community studying risk-taking behavior as the results shed new light on a well-known result put forward by a seminal paper by Thaler.Originality/valueThis paper fills in an identified gap in the literature which is the need to test the house-money effect in a more realistic setting (over repeated risk-elicitation tasks, with money given outside the lotteries and in a within-subject design).

Exploring the Influence of Small-Scale Geographical and Seasonal Variations Over the Microbial Diversity in a Poly-extreme Athalosaline Wetland

Microorganisms are the most diverse life form on the planet and are critical for maintaining the geochemical cycles, especially in extreme environments. Bacterial communities are dynamic and respond directly to changes in abiotic conditions; among these communities, poly-extremophiles are particularly sensitive to perturbations due to their high specialization. Salar de Huasco is a high-altitude wetland located on the Chilean Altiplano exhibiting several conditions considered extreme for life, including negative water balance, extreme variations in temperature and pH values, high UV radiation, and the presence of various toxic metal(oids). However, previous reports have revealed a diverse bacterial community that has adapted to these conditions, here, we aimed to determine whether microbial community diversity and composition changed in response to geographical and seasonal variations. We found that there are significant differences in diversity, abundance, and composition in bacterial taxa that could be attributed to local geographical and seasonal variations, which in turn, can be associated with microbial traits. In conclusion, in this poly-extreme environment, small-scale changes can trigger significant changes in the microbial communities that maintain basic biogeochemical cycles. Further in depth analysis of microbial functionality and geo-ecological dynamics are necessary to better understand the relationships between seasonal changes and bacterial communities.

Mapping the Late Miocene Pyrenean Forests of the La Cerdanya Basin, Spain

The Late Miocene palaeofloras of the La Cerdanya Basin represent a unique look into the Pyrenean Miocene forested areas of the Iberian Peninsula at a time when the European warm and humid climate was experiencing progressive cooling and aridification. Macrofossils (leaves, seeds, fruits and cones) and miospores from several outcrops revealed the composition and abundances of the different plant species present in the area during the Tortonian and early Messinian geological stages (ca. 11.1–5.7 Ma). These fossils were found in the sediment deposits of an ancient lake system situated in the southwestern part of the basin. Previous studies indicated the presence of highly diversified mixed mesophytic forests with broadleaved evergreen and deciduous trees and conifers. However, the spatial structure and distribution of these forest types remains unknown. In the present work, the biomization method was used to infer the different late Miocene vegetation types from the basin. The extent of these vegetation types was calculated using a methodology for mapping vegetation units from fossil and biome data. While previous attempts at mapping Miocene vegetation units had a broad geographical scale, the present work aimed to map the extent of the vegetation units at a small scale, recreating local and specific vegetation changes in an abrupt basin. Results showed similarly high scores between for four biome types, which represent the different types of vegetation that coexisted in the basin during the Tortonian and the early Messinian: warm-temperate evergreen broadleaf and mixed woodlands (WTEM biome), temperate deciduous forests (TEDE) and cool conifer forests (COMX and COEG). Their extent was depicted in two vegetation maps, which account for differences in palaeoaltitude and palaeoclimate. These forests occupied different vegetation belts, which shifted upwards and downwards with climatic variations and the progressive uplift of the Pyrenees during the late Miocene. Azonal riparian forests and wetland vegetation occupied the more humid areas in the centre of the basin. Nonetheless, dry conditions during the early Messinian and decrease in the lake area degraded the wetland environments, which were partially replaced by broadleaved evergreen mixed woodlands.

High-resolution imaging of solar pores

Context. Light bridges are bright, long, and narrow features that are typically connected to the formation or decay processes of sunspots and pores. Aims. The interaction of magnetic fields and plasma flows is investigated in the trailing part of an active region, where pores and magnetic knots evolve into a complex sunspot. The goal is to identify the photospheric and chromospheric processes, which transform the mainly vertical magnetic fields of pores into a sunspot with multiple umbral cores, light bridges, and rudimentary penumbrae. Methods. Conducting observations with a broad variety of telescopes and instruments provides access to different atmospheric layers and the changing morphology of features connected to strong magnetic fields. While the Helioseismic and Magnetic Imager (HMI) of the Solar Dynamics Observatory (SDO) provides full-disk continuum images and line-of-sight magnetograms, the fine structure and flows around a pore can be deduced from high-resolution observations in various wavelengths as provided by the Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). Horizontal proper motions are evaluated applying local correlation tracking (LCT) to the available time series, whereas the connectivity of sunspot features can be established using the background-subtracted activity maps (BaSAMs). Results. Photospheric flow maps indicate radial outflows, where the light bridge connects to the surrounding granulation, whereas inflows are present at the border of the pores. In contrast, the chromospheric flow maps show strong radial outflows at superpenumbral scales, even in the absence of a penumbra in the photosphere. The region in between the two polarities is characterized by expanding granules creating strong divergence centers. Variations in BaSAMs follow locations of significant and persistent changes in and around pores. The resulting maps indicate low variations along the light bridge, as well as thin hairlines connecting the light bridge to the pores and strong variations at the border of pores. Various BaSAMs demonstrate the interaction of pores with the surrounding supergranular cell. The Hα line-of-sight velocity maps provide further insights into the flow structure, with twisted motions along some of the radial filaments around the pore with the light bridge. Furthermore, flows along filaments connecting the two polarities of the active region are pronounced in the line-of-sight velocity maps. Conclusions. The present observations reveal that even small-scale changes of plasma motions in and around pores are conducive to transform pores into sunspots. In addition, chromospheric counterparts of penumbral filaments appear much earlier than the penumbral filaments in the photosphere. Penumbra formation is aided by a stable magnetic feature that anchors the advection of magnetic flux and provides a connection to the surrounding supergranular cell, whereas continuously emerging flux and strong light bridges are counteragents that affect the appearance and complexity of sunspots and their penumbrae.

A cross-sectional study of explainable machine learning in Alzheimer's disease: diagnostic classification using MR radiomic features.

Alzheimer's disease (AD) even nowadays remains a complex neurodegenerative disease and its diagnosis relies mainly on cognitive tests which have many limitations. On the other hand, qualitative imaging will not provide an early diagnosis because the radiologist will perceive brain atrophy on a late disease stage. Therefore, the main objective of this study is to investigate the necessity of quantitative imaging in the assessment of AD by using machine learning (ML) methods. Nowadays, ML methods are used to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers in the assessment of AD. In this study radiomic features from both entorhinal cortex and hippocampus were extracted from 194 normal controls (NC), 284 mild cognitive impairment (MCI) and 130 AD subjects. Texture analysis evaluates statistical properties of the image intensities which might represent changes in MRI image pixel intensity due to the pathophysiology of a disease. Therefore, this quantitative method could detect smaller-scale changes of neurodegeneration. Then the radiomics signatures extracted by texture analysis and baseline neuropsychological scales, were used to build an XGBoost integrated model which has been trained and integrated. The model was explained by using the Shapley values produced by the SHAP (SHapley Additive exPlanations) method. XGBoost produced a f1-score of 0.949, 0.818, and 0.810 between NC vs. AD, MC vs. MCI, and MCI vs. AD, respectively. These directions have the potential to help to the earlier diagnosis and to a better manage of the disease progression and therefore, develop novel treatment strategies. This study clearly showed the importance of explainable ML approach in the assessment of AD.

Cosmo-tomography toward PKS 1830−211: Variability of the quasar and of its foreground molecular absorption monitored with ALMA

Context. Time variability of astronomical sources provides crude information on their typical size and on the implied physical mechanisms. PKS 1830−211 is a remarkable radio-bright lensed quasar with a foreground molecular absorber in the lens galaxy at z = 0.89. Small-scale morphological changes in the core–jet structure of the quasar – which is magnified by the lensing – result in a varying illumination of the absorber screen, which in turn causes variations in the absorption profile. Aims. We aim to study the time variations of the system (the two main lensed images of the quasar and the two corresponding sightlines in the absorber) in order to obtain constraints on both the quasar activity and small-scale structures in the interstellar medium of the absorber. Methods. We used ALMA to monitor the submillimeter continuum emission of PKS 1830−211, together with the absorption spectra of the H2O and CH molecules, with 17 visits spread over six months in 2016. Complementing this, we used available ALMA data to investigate changes in the system in the period 2012−2022. Results. From the continuum data, we followed the evolution of the flux density, flux-density ratio, spectral index, and differential polarization between the two lensed images of the quasar; all quantities show significant variations related to the intrinsic activity of the quasar. We propose a simple parametric model of a core plus a ballistic plasmon to account for the continuum evolution, from which we constrain a time delay of 25 ± 3 days between main lensed images. The spectral lines reveal significant variations in the foreground absorption profile. A principal component analysis highlights apparent wavy time variations, possibly linked to the helical jet precession period of the quasar. From the deep averaged spectra towards the southwest image, we detect the absorption of the rare isotopolog 13CH and estimate an abundance ratio of 12CH/13CH ∼ 150. We also measure the oxygen isotopic ratios, 16O/18O = 65.3 ± 0.7 and 18O/17O = 11.5 ± 0.5 in the z = 0.89 absorber. Finally, we find a remarkable continuous shallow trough in the water absorption spanning a velocity interval of nearly 500 km s−1. This broad absorption could be the signature of an extra-planar molecular component. Conclusions. All together, the system formed by the quasar PKS 1830−211 and its foreground lens–absorber acts as a powerful gravitational microscope, providing us with the possibility to dissect small-scale structures in both the ISM of the foreground absorber and the jet of the background quasar.

Adaptive zero-learning medical image fusion

Medical fusion image can integrate complementary information from multi-modal medical images, so that more comprehensive and accurate image results could be obtained. This paper proposes a new two-scale zero-learning medical images fusion method combined with pre-trained Res2Net and an adaptive guided filter. Firstly, this method utilizes the guided filter to decompose a medical image into a base layer representing large-scale intensity variations, and a detail layer containing small scale changes. Considering the influence of the parameters of the guided filter on the fusion images and the time-consuming on parameter selection, an adaptive guided filter based on the multi-modal medical image features is proposed. Then, detail layers are fused by an elementwise-sum strategy for retaining more detail information of source images. And the base layers are to fused with deep feature maps extracted from a pre-trained neural network Res2Net. Finally, the fused detail and basic layer will be reconstructed to obtain medical fusion image. The proposed method is demonstrated its superiority by ablation studies, and compared with 7 typical and advanced image fusion methods in visual effect and evaluation index. The experimental results show that the proposed image fusion method outperforms other methods in retaining effective detailed information and image clarity.