Ontmoeting met dementie

Dementie, een belangrijk maatschappelijk thema, waar K38 via kunst aandacht aan besteedt. Studenten van Academie Minerva hebben wekelijks, drie maanden lang, in het Groningse Odensehuis mensen met dementie geportretteerd. Deze expositie vormt een neerslag van hun ontmoeting

Quantum filter reduction for measurement-feedback control via unsupervised manifold learning

We derive simple models for the dynamics of a single atom coupled to a cavity field mode in the absorptive bistable parameter regime by projecting the time evolution of the state of the system onto a suitably chosen nonlinear low-dimensional manifold, which is found by use of local tangent space alignment. The output field from the cavity is detected with a homodyne detector allowing observation of quantum jumps of the system between states with different average numbers of photons in the cavity. We find that the models, which are significantly faster to integrate numerically than the full stochastic master equation, largely reproduce the dynamics of the system, and we demonstrate that they are sufficiently accurate to facilitate feedback control of the state of the system based on the predictions of the models alone.Comment: 15 pages, 6 figure

The structures and total (minor + major) merger histories of massive galaxies up to z = 3 in the HST GOODS NICMOS Survey: A possible solution to the size evolution problem

We investigate the total major (> 1:4 by stellar mass) and minor (> 1:100 by stellar mass) merger history of a population of 80 massive (M_* > 10^11 M_sol) galaxies at high redshifts (z = 1.7 - 3). We utilize extremely deep and high resolution HST H-band imaging from the GOODS NICMOS Survey (GNS), which corresponds to rest-frame optical wavelengths at the redshifts probed. We find that massive galaxies at high redshifts are often morphologically disturbed, with a CAS deduced merger fraction f_m = 0.23 +/- 0.05 at z = 1.7 - 3. We find close accord between close pair methods (within 30 kpc apertures) and CAS methods for deducing major merger fractions at all redshifts. We deduce the total (minor + major) merger history of massive galaxies with M_* > 10^9 M_sol galaxies, and find that this scales roughly linearly with log-stellar-mass and magnitude range. We test our close pair methods by utilizing mock galaxy catalogs from the Millennium Simulation. We compute the total number of mergers to be (4.5 +/- 2.9) / from z = 3 to the present, to a stellar mass sensitivity threshold of ~ 1:100 (where \tau_m is the merger timescale in Gyr which varies as a function of mass). This corresponds to an average mass increase of (3.4 +/- 2.2) x 10^11 M_sol over the past 11.5 Gyrs due to merging. We show that the size evolution observed for these galaxies may be mostly explained by this merging.Comment: 19 pages, 10 figures, re-submitted to ApJ after a positive referee report, originally submitted on Sept 20 201

Gas Accretion as a Dominant Formation Mode in Massive Galaxies from the GOODS NICMOS Survey

The ability to resolve all processes which drive galaxy formation is one of the most fundamental goals in extragalactic astronomy. While star formation rates and the merger history are now measured with increasingly high certainty, the role of gas accretion from the intergalactic medium in supplying gas for star formation still remains largely unknown. We present in this paper indirect evidence for the accretion of gas into massive galaxies with initial stellar masses M_*>10^{11} M_sol and following the same merger adjusted co-moving number density at lower redshifts during the epoch 1.5 < z < 3, using results from the GOODS NICMOS Survey (GNS). We show that the measured gas mass fractions of these massive galaxies are inconsistent with the observed star formation history for the same galaxy population. We further demonstrate that this additional gas mass cannot be accounted for by cold gas delivered through minor and major mergers. We also consider the effects of gas outflows and gas recycling due to stellar evolution in these calculations. We argue that to sustain star formation at the observed rates there must be additional methods for increasing the cold gas mass, and that the likeliest method for establishing this supply of gas is by accretion from the intergalactic medium. We calculate that the average gas mass accretion rate into these massive galaxies between 1.5 < z < 3.0, is \dot{M} = 96+/-19 M_sol/yr after accounting for outflowing gas. We show that during this epoch, and for these very massive galaxies, 49+/-20% of baryonic mass assembly is a result of gas accretion and unresolved mergers. However, 66+/-20% of all star formation in this epoch is the result of gas accretion. This reveals that for the most massive galaxies at 1.5< z< 3 gas accretion is the dominant method for instigating new stellar mass assembly.Comment: MNRAS in press, 11 pages, 5 figure

Satellite Imagery to Map Topsoil Organic Carbon Content over Cultivated Areas: An Overview

There is a need to update soil maps and monitor soil organic carbon (SOC) in the upper horizons or plough layer for enabling decision support and land management, while complying with several policies, especially those favoring soil carbon storage. This review paper is dedicated to the satellite-based spectral approaches for SOC assessment that have been achieved from several satellite sensors, study scales and geographical contexts in the past decade. Most approaches relying on pure spectral models have been carried out since 2019 and have dealt with temperate croplands in Europe, China and North America at the scale of small regions, of some hundreds of km(2): dry combustion and wet oxidation were the analytical determination methods used for 50% and 35% of the satellite-derived SOC studies, for which measured topsoil SOC contents mainly referred to mineral soils, typically cambisols and luvisols and to a lesser extent, regosols, leptosols, stagnosols and chernozems, with annual cropping systems with a SOC value of similar to 15 g.kg(-1) and a range of 30 g.kg(-1) in median. Most satellite-derived SOC spectral prediction models used limited preprocessing and were based on bare soil pixel retrieval after Normalized Difference Vegetation Index (NDVI) thresholding. About one third of these models used partial least squares regression (PLSR), while another third used random forest (RF), and the remaining included machine learning methods such as support vector machine (SVM). We did not find any studies either on deep learning methods or on all-performance evaluations and uncertainty analysis of spatial model predictions. Nevertheless, the literature examined here identifies satellite-based spectral information, especially derived under bare soil conditions, as an interesting approach that deserves further investigations. Future research includes considering the simultaneous analysis of imagery acquired at several dates i.e., temporal mosaicking, testing the influence of possible disturbing factors and mitigating their effects fusing mixed models incorporating non-spectral ancillary information

A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols

Soil spectral libraries (SSLs) are important big-data archives (spectra associated with soil properties) that are analyzed via machine-learning algorithms to estimate soil attributes. Since different spectral measurement protocols are applied when constructing SSLs, it is necessary to examine harmonization techniques to merge the data. In recent years, several techniques for harmonization have been proposed, among which the internal soil standard (ISS) protocol is the most largely applied and has demonstrated its capacity to rectify systematic effects during spectral measurements. Here, we postulate that a spectral transfer function (TF) can be extracted between existing (old) SSLs if a subset of samples from two (or more) different SSLs are remeasured using the ISS protocol. A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. These SSLs had already been measured using different protocols without any ISS treatment the Brazilian (BSSL, generated in 2019) and the European (LUCAS, generated in 2009-2012) SSLs. To verify the TF's ability to improve the spectral assessment of soil attributes after harmonizing the different SSLs' protocols, RF spectral-based models for estimating organic carbon (OC) in soil were developed. The results showed high spectral similarities between the ISS and the ISS-TF spectral observations, indicating that post-ISS rectification is possible. Furthermore, after merging the SSLs with the TFs, the spectral-based assessment of OC was considerably improved, from R2 = 0.61, RMSE (g/kg) = 12.46 to R2 = 0.69, RMSE (g/kg) = 11.13. Given our results, this paper enhances the importance of soil spectroscopy by contributing to analyses in remote sensing, soil surveys, and digital soil mapping

A Deep Probe of the Galaxy Stellar Mass Functions at z~1-3 with the GOODS NICMOS Survey

We use a sample of 8298 galaxies observed in the HST GOODS NICMOS Survey (GNS) to construct the galaxy stellar mass function as a function of both redshift and stellar mass up to z=3.5 and down to masses of Mstar=10^8.5 Msun at z~1. We discover that a significant fraction of all massive Mstar>10^11 Msun galaxies are in place up to the highest redshifts we probe, with a decreasing fraction of lower mass galaxies present at all redshifts. This is an example of `galaxy mass downsizing', and is the result of massive galaxies forming before lower mass ones, and not just simply ending their star formation earlier as in traditional downsizing scenarios. We find that the faint end slope is significantly steeper than what is found in previous investigations. We demonstrate that this steeper mass function better matches the stellar mass added due to star formation, thereby alleviating some of the mismatch between these two measures of the evolution of galaxy mass. We furthermore examine the stellar mass function divided into blue/red systems, as well as for star forming and non-star forming galaxies. We find a similar mass downsizing present for both blue/red and star-forming/non-star forming galaxies, and that the low mass galaxies are mostly all blue, and are therefore creating the steep mass functions. We furthermore show that, although there is a downsizing such that high mass galaxies are nearer their z=0 values at high redshift, this turns over at masses Mstar~10^10 Msun, such that the lowest mass galaxies are more common than galaxies at slight higher masses, creating a `dip' in the observed galaxy mass function. We argue that the galaxy assembly process may be driven by different mechanisms at low and high masses, and that the efficiency of the galaxy formation process is lowest at masses Mstar~10^10 Msun at 1<z<3. (Abridged)Comment: 16 pages, 11 figures, MNRAS, accepte

Timed written picture naming in 14 european languages

We describe the Multilanguage Written Picture Naming Dataset. This gives trial-level data and time and agreement norms for written naming of the 260 pictures of everyday objects that compose the colorized Snodgrass and Vanderwart picture set (Rossion & Pourtois in Perception, 33, 217\u2013236, 2004). Adult participants gave keyboarded responses in their first language under controlled experimental conditions (N = 1,274, with subsamples responding in Bulgarian, Dutch, English, Finnish, French, German, Greek, Icelandic, Italian, Norwegian, Portuguese, Russian, Spanish, and Swedish). We measured the time to initiate a response (RT) and interkeypress intervals, and calculated measures of name and spelling agreement. There was a tendency across all languages for quicker RTs to pictures with higher familiarity, image agreement, and name frequency, and with higher name agreement. Effects of spelling agreement and effects on output rates after writing onset were present in some, but not all, languages. Written naming therefore shows name retrieval effects that are similar to those found in speech, but our findings suggest the need for cross-language comparisons as we seek to understand the orthographic retrieval and/or assembly processes that are specific to written output

Stromal Hedgehog signalling is downregulated in colon cancer and its restoration restrains tumour growth

A role for Hedgehog (Hh) signalling in the development of colorectal cancer (CRC) has been proposed. In CRC and other solid tumours, Hh ligands are upregulated; however, a specific Hh antagonist provided no benefit in a clinical trial. Here we use Hh reporter mice to show that downstream Hh activity is unexpectedly diminished in a mouse model of colitis-associated colon cancer, and that downstream Hh signalling is restricted to the stroma. Functionally, stroma-specific Hh activation in mice markedly reduces the tumour load and blocks progression of advanced neoplasms, partly via the modulation of BMP signalling and restriction of the colonic stem cell signature. By contrast, attenuated Hh signalling accelerates colonic tumourigenesis. In human CRC, downstream Hh activity is similarly reduced and canonical Hh signalling remains predominantly paracrine. Our results suggest that diminished downstream Hh signalling enhances CRC development, and that stromal Hh activation can act as a colonic tumour suppressor