On the ISW-cluster cross-correlation in future surveys

We investigate the cosmological information contained in the cross-correlation between the Integrated Sachs-Wolfe (ISW) of the Cosmic Microwave Background (CMB) anisotropy pattern and galaxy clusters from future wide surveys. Future surveys will provide cluster catalogues with a number of objects comparable with galaxy catalogues currently used for the detection of the ISW signal by cross-correlation with the CMB anisotropy pattern. By computing the angular power spectra of clusters and the corresponding cross-correlation with CMB, we perform a signal-to-noise ratio (SNR) analysis for the ISW detection as expected from the eROSITA and the Euclid space missions. We discuss the dependence of the SNR of the ISW-cluster cross-correlation on the specifications of the catalogues and on the reference cosmology. We forecast that the SNRs for ISW-cluster cross-correlation are alightly smaller compared to those which can be obtained from future galaxy surveys but the signal is expected to be detected at high significance, i.e. more than $> 3\,\sigma$. We also forecast the joint constraints on parameters of model extensions of the concordance $\Lambda$CDM cosmology by combining CMB and the ISW-cluster cross-correlation.Comment: 12 pages, 10 figures. Matches version accepted in MNRA

Different titanium surfaces modulate the bone phenotype of SaOS-2 osteoblast-like cells.

Commercially pure titanium implants presenting a relatively smooth, machined surface or a roughned endosseous surface show a large percentage of clinical successes. Surface properties of dental implants seem to be important with respect to bone cells response. Implant topography appears to modulate cell growth and differentiation of osteoblasts affecting the bone healing around the titanium implant. The aim of the present study was to examine the effects of three different titanium surfaces on cell morphology, adhesion and bone phenotypic expression of human osteoblast-like cells, SaOS-2. SaOS-2 cells were cultured on commercially pure titanium disks of 1 cm in diameter with three different surface roughness: smooth (S), sandblasted (SB) and titanium plasma sprayed (TPS). Differences in the cell morphology were found on the three surfaces showing an uniform monolayer of shaped cells on the S surfaces, and clusters of multilayered cells with an irregular shape on the rough surfaces. The adhesion of SaOS-2 cells, as measured after 3h of culture, was not affected by surface roughness. ECM components such as collagen I (CoI), fibronectin (FN), vitronectin (VN) and tenascin (TN) were secreted and organized only on SB and TPS surfaces while on S surfaces they remained in the cytoplasm. Osteopontin and BSP-II were largely detected on SB and TPS surfaces, while only minimal production was observed on S surfaces. These data show that titanium surface roughness affects bone differentiation of osteoblast like-cells, SaOS-2, indicating that surface properties may be able to modulate the osteoblast phenotype. These observations also suggest that the bone healing response around dental implants can be affected by surface topography

Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance

Successful data-driven science requires complex data engineering pipelines to clean, transform, and alter data in preparation for machine learning, and robust results can only be achieved when each step in the pipeline can be justified, and its effect on the data explained. In this framework, our aim is to provide data scientists with facilities to gain an in-depth understanding of how each step in the pipeline affects the data, from the raw input to training sets ready to be used for learning. Starting from an extensible set of data preparation operators commonly used within a data science setting, in this work we present a provenance management infrastructure for generating, storing, and querying very granular accounts of data transformations, at the level of individual elements within datasets whenever possible. Then, from the formal definition of a core set of data science preprocessing operators, we derive a provenance semantics embodied by a collection of templates expressed in PROV, a standard model for data provenance. Using those templates as a reference, our provenance generation algorithm generalises to any operator with observable input/output pairs. We provide a prototype implementation of an application-level provenance capture library to produce, in a semi-automatic way, complete provenance documents that account for the entire pipeline. We report on the ability of our implementations to capture provenance in real ML benchmark pipelines and over TCP-DI synthetic data. We finally show how the collected provenance can be used to answer a suite of provenance benchmark queries that underpin some common pipeline inspection questions, as expressed on the Data Science Stack Exchange.Comment: 37 pages, 27 figures, submitted to a journa

Impact-based flash-flood forecasting system: Sensitivity to high resolution numerical weather prediction systems and soil moisture

In recent years, continuous improvements have been made in weather forecasting and flood prediction with great benefit from Early Warning Systems (EWSs). Despite the continuous quest for innovation from the scientific and user communities, EWSs remain based mostly on hazard forecast, and the information on possible consequences and potential impacts is generally missing. In this work, a methodology for quantitative real-time impact assessment for flash floods is presented. The methodology uses a multi-model ensemble approach and considers soil moisture uncertainty. Moreover, the flood forecasting chain, which normally provides only the discharge probability of exceeding a given threshold, is extended to include a fully 2D hydraulic model and a damage estimation model to quantitatively assess impacts in terms of economic losses and the people involved. The procedure was tested on recent flood events occurring in Genoa in northwestern Italy. This paper discusses the potential challenges and opportunities offered by this approach in the decision-making workflow in an operational context

A NEW STRATEGIC WAVE MEASUREMENT STATION OFF NAPLES PORT MAIN BREAKWATER

The accuracy of directional wave spectra sensors is crucial for obtaining accurate forecasts of ocean and coastal wave conditions for scientific and engineering applications. In this paper, a newly designed, low-cost GPS-based wave buoy, called the Directional Wave Spectra Drifter (DWSD), is presented. A field test campaign was conducted at the Gulf of Naples, Italy with the goal of comparing the directional wave properties obtained with the DWSD and with a nearly co-located bottom-mounted Acoustic Doppler Current Profiler (ADCP) from Teledyne RD-Instruments. The comparison shows a very good agreement between the two methodologies. The reliability of this innovative instrument and its low costs allow a large variety of applications, including the implementation of a global, satellite-linked, real-time open-ocean network of drifting directional wave spectra sensors and monitoring the sea-state in harbors to aid ship transit and for planning coastal and offshore constructions. The DWSD is currently in use to better constrain the wave energy climatology with the goal of optimizing the design of a full-scale prototype Wave Energy Converter (WEC) in the port of Naples, Italy

Regional stratigraphy of the south polar layered deposits (Promethei Lingula, Mars): “Discontinuity-bounded” units in images and radargrams

The Mars South Polar Layered Deposits (SPLD) are the result of depositional and erosional events, which are marked by different stratigraphic sequences and erosional surfaces. To unambiguously define the stratigraphic units at regional scale, we mapped the SPLD on the basis of observed discontinuities (i.e., unconformities, correlative discontinuities and conformities), as commonly done in terrestrial modern stratigraphy. This methodology is defined as “Discontinuity-Bounded Units” or allostratigraphy, and is complemented by geomorphological mapping. Our study focuses on Promethei Lingula (PL) and uses both high-resolution images (CTX, HiRISE) and radargrams (SHARAD) to combine surface and sub-surface observations and obtain a 3D geological reconstruction of the SPLD. One regional discontinuity (named AUR1) was defined within the studied stratigraphic succession and is exposed in several non-contiguous outcrops around PL as well as observed at depth within the ice sheet. This is the primary contact between two major depositional sequences, showing a different texture at CTX resolution. The lower sequence is characterized mainly by a “ridge and trough” morphology (Ridge and Trough Sequence; RTS) and the upper sequence shows mainly by a “stair-stepped” morphology (Stair-Stepped Sequence; SSS). On the basis of the observations, we defined two regional “discontinuity-bounded” units in PL, respectively coinciding with RTS and SSS sequences. Our stratigraphic reconstruction provides new hints on the major scale events that shaped this region. Oscillations in Martian axial obliquity could have controlled local climate conditions in the past, affecting the PL geological record

Recurrent transient global amnesia as presenting symptoms of CADASIL

Despite transient global amnesia is considered unusual in Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and causal relation is still unclear, this report suggests to consider CADASIL in those patients with recurrent transient global amnesia, especially when MRI shows multifocal hyperintensities affecting the cerebral white matter or when it is followed by cognitive decline

Sensor Fusion for Video Surveillance

In this paper, a multisensor data fusion system for object tracking is presented. It is able to track in real-time multiple targets in outdoor environments. The system can take advantage of the redundant information coming from different sensors monitoring the same scene. The measurements (positions of the targets) obtained from the available sources are fused together to obtain a more accurate estimate. Data fusion is performed considering sensor reliability at every time instant. A confidence measure has been employed to weight sensor data in the fusion process. Compared to single camera systems, the adopted approach has produced more accurate and continuous trajectories, reducing calibration and segmentation errors