Pressure Collapse of the Magnetic Ordering in MnSi via Thermal Expansion

The itinerant quasi-ferromagnetic metal MnSi has been studied by detailed thermal expansion measurements under pressures and magnetic fields. A sudden decrease of the volume at the critical pressure Pc ~1.6 GPa has been observed and is in good agreement with the pressure variation of the volume fraction of the spiral magnetic ordering. This confirms that the magnetic order disappears by a first order phase transition. The energy change estimated by the volume discontinuity on crossing Pc is of similar order as the Zeeman energy of the transition from the spiral ground state to a polarized paramagnetic one under magnetic field. In contrast to the strong pressure dependence of the transition temperature, the characteristic fields are weakly pressure dependent, indicating that the strength of the ferromagnetic and the Dzyaloshinskii-Moriya interactions do not change drastically around Pc. The evaluated results of the thermal expansion coefficient and the magnetostriction are analyzed thermodynamically. The Sommerfeld coefficient of the linear temperature term of the specific heat is enhanced just below Pc. The magnetic field-temperature phase diagrams in the ordered and paramagnetic phases are also compared. Comparison is made with other heavy fermion compounds with first order phase transition at 0 K.Comment: 9 pages, 13 figures, accepted to be published in JPS

The Database of European Forest Insect and Disease Disturbances: DEFID2

[EN] Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of bio-diversity, could be increasingly compromised. Despite the relevance of these detri-mental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including se-verity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite- based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and dam-age metrics derived from them using the LandTrendr spectral–temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and pos-sible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics, and enhance their representation in land-climate models. Further data sharing is en-couraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc- opend ata/FOREST/DISTURBANCES/DEFID2/SIEC Joint Research Centre; European Commission, Grant/Award Number: 101059498; European Research Council, Grant/Award Number: 101039567; Ministry of Research, Innovation and Digitalization of Romania; LifeWatch— POC project, Grant/Award Number: 327/390003/06-11-202

Identification and Validation of Novel Cerebrospinal Fluid Biomarkers for Staging Early Alzheimer's Disease

Ideally, disease modifying therapies for Alzheimer disease (AD) will be applied during the 'preclinical' stage (pathology present with cognition intact) before severe neuronal damage occurs, or upon recognizing very mild cognitive impairment. Developing and judiciously administering such therapies will require biomarker panels to identify early AD pathology, classify disease stage, monitor pathological progression, and predict cognitive decline. To discover such biomarkers, we measured AD-associated changes in the cerebrospinal fluid (CSF) proteome.CSF samples from individuals with mild AD (Clinical Dementia Rating [CDR] 1) (n = 24) and cognitively normal controls (CDR 0) (n = 24) were subjected to two-dimensional difference-in-gel electrophoresis. Within 119 differentially-abundant gel features, mass spectrometry (LC-MS/MS) identified 47 proteins. For validation, eleven proteins were re-evaluated by enzyme-linked immunosorbent assays (ELISA). Six of these assays (NrCAM, YKL-40, chromogranin A, carnosinase I, transthyretin, cystatin C) distinguished CDR 1 and CDR 0 groups and were subsequently applied (with tau, p-tau181 and Aβ42 ELISAs) to a larger independent cohort (n = 292) that included individuals with very mild dementia (CDR 0.5). Receiver-operating characteristic curve analyses using stepwise logistic regression yielded optimal biomarker combinations to distinguish CDR 0 from CDR>0 (tau, YKL-40, NrCAM) and CDR 1 from CDR<1 (tau, chromogranin A, carnosinase I) with areas under the curve of 0.90 (0.85-0.94 95% confidence interval [CI]) and 0.88 (0.81-0.94 CI), respectively.Four novel CSF biomarkers for AD (NrCAM, YKL-40, chromogranin A, carnosinase I) can improve the diagnostic accuracy of Aβ42 and tau. Together, these six markers describe six clinicopathological stages from cognitive normalcy to mild dementia, including stages defined by increased risk of cognitive decline. Such a panel might improve clinical trial efficiency by guiding subject enrollment and monitoring disease progression. Further studies will be required to validate this panel and evaluate its potential for distinguishing AD from other dementing conditions

Wayfinding in scene space: modelling transfers in public transport

One of the characteristics of public transport is the need for transfers. During transfers, travellers are pedestrian wayfinders and have to find their way from the place of arrival to the place of departure of another means of transport. Wayfinding in public transport takes place in two types of spaces: network space and scene space. Network space includes the transport network. Scene space consists of the halls, squares, and platforms at interchange nodes; it lacks an obvious network structure. Published timetables allow pre-trip wayfinding in network space, but wayfinding in scene space requires interaction with the actual environment, using the information provided therein. The theory of image schemata (cognitive patterns that structure our perceptions and actions) suggests that structural information is immediately usable. Other types of information, notably signage, require conscious effort to use. This research is about transfers in railway stations, i.e., wayfinding in scene space. I hypothesise that structural information provided by the architectural layout is enough to guide travellers through railway stations. Computational modelling is used to test this hypothesis. Image schemata form the cognitive basis for a formal model of scene space, called Schematic Geometry. A software agent is developed next and used to simulate wayfinding tasks in Schematic Geometry models of two railway stations. Results indicate that structural information supports wayfinding, but is not always enough to find optimal routes. Previews of parts of the environment are found to be highly effective wayfinding aids that build on human object recognition rather than on sign reading. Conclusions are that humans integrate information from various sources and of different types to achieve good wayfinding performance; well designed architecture can further support wayfinding by providing structural clues and previews. This thesis contributes to our understanding of wayfinding, especially the information needs for wayfinding in scene space, and provides a cognitively motivated but formal model of scene space, Schematic Geometry

Partial Ordering

Partial orders are special relations are special sets. are structurally the same as directed acyclic graphs. Synonyms: partial order, partially ordered set, poset, or simply order. Partial orders can be used to formally capture many informal concepts such as parthood (“the hall is part of the house”), precedence (“first peel the orange, then eat it”), inferiority (“3 is less than 5”), dependence (“before assembling the car, build the engine”), etc. Properties of relations A relation A ⊆ A × B “from A to B ” is the mathematical way to express connections among the elements of two sets A and B. We only consider the case A = B; then R ⊆ A × A is a “relation on set A”. We write xRy as an abbreviation for (x, y) ∈ R. Some typical properties of binary relations are (for all x, y, z in A): reflexive xRx irreflexive x�Rx symmetric xRy → y Rx asymmetric xRy → y �R

A Hybrid Spatial Model for Representing Indoor Environments

In this article we propose a hybrid spatial model for indoor environments. The model consists of hierarchically structured graphs with typed edges and nodes. The model is hybrid in the sense that nodes and edges can be labelled with qualitative as well as quantitative information. The graphs support wayfinding and, in addition, provide helpful information for generating human-oriented descriptions of an indoor (and outdoor) path