Keep fit (a bit) - ESWC SSchool 14 - Student project

•

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eswcsummerschool

Science

Keep Fit(a Bit) in Kalamaki
First web based* attempt to make Kalamaki a „Smart City“
* to be extended to an app-based version after fundings ;)
Proudly presented by FitBeople:
Emna
Elias
Iacopo
Maxim

The Story of Fred
•
Fred lives in Dublin
•
Dublin is a smart city *
•
Fred is a sports enthusiast
•
Observes his energy consumption/gain
•
Fred is going on holidays to Kalamaki
•
Of course Fred wants to stay fit
•
But...
How to stay fit
In Kalamaki?

What is a smart city?
Source: http://www.urenio.org/wp-content/uploads/2011/01/ibm_smart_cities_new.jpg
Food

Goal: „Personalized health planner“
Personalized healt
planner
Age, Height, Weight, GenderPosition in Kalamaki
Integrated view of:
Locations of Restaurants
Dishes of restaurants
Energy of dishes
Price of dishes
Walking distances between different places
Overview of own energy balance

What did we do?
•
Data collection
•
RDF data (Total steps per day -FitBit API)
•
Non-digital data (restaurant menus)
•
HTML data (calories of dishes)
•
Geographic data (OSM)

What did we do?
•
Data integration
•
RDFisation of non-digital data andother data
•
Stored it in (local) triple store
•
SPARQL querys over multiple datasets
•
Implementation of web-based prototype
•
Computations of calories
•
Integration with backend
•
Graphical user interface

Future steps
•
Publishing Kalamaki data on OSM (Restaurants, Prices, Calories, etc.)
•
Generalization/integration of real smart city
•
Social features
•
Share activities and consumption
•
Comparewith other users
•
Exchange „lifestyle“ a) „I lost ...kg by doing ...“ b) „Wow, I live there too, I‘ll do the same thing“
•
Including weather data
•
Including health data (illnesses, deseases, alergies)

Thank you!
The first team ever, enabling Kalamaki a „smart city“!

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Context. WASP-76 b has been a recurrent subject of study since the detection of a signature in high-resolution transit spectroscopy data indicating an asymmetry between the two limbs of the planet. The existence of this asymmetric signature has been confirmed by multiple studies, but its physical origin is still under debate. In addition, it contrasts with the absence of asymmetry reported in the infrared (IR) phase curve. Aims. We provide a more comprehensive dataset of WASP-76 b with the goal of drawing a complete view of the physical processes at work in this atmosphere. In particular, we attempt to reconcile visible high-resolution transit spectroscopy data and IR broadband phase curves. Methods. We gathered 3 phase curves, 20 occultations, and 6 transits for WASP-76 b in the visible with the CHEOPS space telescope. We also report the analysis of three unpublished sectors observed by the TESS space telescope (also in the visible), which represents 34 phase curves. Results. WASP-76 b displays an occultation of 260±11 and 152±10 ppm in TESS and CHEOPS bandpasses respectively. Depending on the composition assumed for the atmosphere and the data reduction used for the IR data, we derived geometric albedo estimates that range from 0.05 ± 0.023 to 0.146 ± 0.013 and from <0.13 to 0.189 ± 0.017 in the CHEOPS and TESS bandpasses, respectively. As expected from the IR phase curves, a low-order model of the phase curves does not yield any detectable asymmetry in the visible either. However, an empirical model allowing for sharper phase curve variations offers a hint of a flux excess before the occultation, with an amplitude of ∼40 ppm, an orbital offset of ∼−30◦ , and a width of ∼20◦ . We also constrained the orbital eccentricity of WASP-76 b to a value lower than 0.0067, with a 99.7% confidence level. This result contradicts earlier proposed scenarios aimed at explaining the asymmetry observed in high-resolution transit spectroscopy. Conclusions. In light of these findings, we hypothesise that WASP-76 b could have night-side clouds that extend predominantly towards its eastern limb. At this limb, the clouds would be associated with spherical droplets or spherically shaped aerosols of an unknown species, which would be responsible for a glory effect in the visible phase curves.

Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b

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HotJupiters are amongthebest-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5–12µ 5–12µ 5–12µm with JWST’s Mid-Infrared Instrument (MIRI). 1524 ±35 1524 ±35 and 863±23 The spectra reveal a large day–night temperature contrast (with average brightness temperatures of 1524 ± 35 863 ±23 863 ±23Kelvin, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase curve shape and emission spectra strongly suggest the presence of nightside clouds which become optically thick to thermal emission at pressures greater than ∼100mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Con3trary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2σ upper limit of 1–6 parts per million, depending on model assumptions).

Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b

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Mustard, as a crop, is susceptible to a variety of pests that can affect its growth and yield. Here’s a rundown of some common pests that target mustard plants: Aphids: These small, sap-sucking insects can cause significant damage by feeding on the leaves and stems. Aphids also excrete a sticky substance known as honeydew, which can lead to the growth of sooty mold on the plants. Flea Beetles: These tiny beetles jump like fleas when disturbed and chew small holes in the leaves. They are particularly damaging in the early growth stages of the plant. Cabbage Loopers: The larvae of a type of moth, these caterpillars are known for their distinctive looping movement. They chew large holes in the leaves and can defoliate plants if present in large numbers. Diamondback Moth Larvae: Another caterpillar pest, these larvae chew small holes in the leaves and can cause extensive damage, especially when infestations are heavy. Whiteflies: These are tiny, winged insects that feed on plant sap and can quickly become a problem in greenhouse or close planting conditions. Like aphids, they also secrete honeydew. Cutworms: These are the larvae of certain types of moths and are known for cutting young plants at the stem base at ground level. They are most destructive during the night. Root Maggots: The larvae of root maggot flies, these pests attack the roots of mustard plants, causing wilting and potentially killing young plants. Harlequin Bugs: These are colorful stink bugs that suck the sap from mustard plant stems and leaves, causing the leaves to become stippled, wilt, and eventually die if the infestation is severe. Mustard Sawfly: The larvae of the mustard sawfly can cause considerable defoliation, as they feed voraciously on the leaves. Clubroot: Caused by a fungus-like organism, clubroot affects the roots, causing them to swell and distort. While technically a disease, it is often associated with pest management because controlling it involves similar preventative strategies. Control Measures: Managing pests in mustard involves a combination of cultural, biological, and chemical methods. Crop rotation, resistant varieties, timely sowing, maintaining plant health, and using natural predators like ladybugs and parasitic wasps can help keep pest populations under control. Chemical pesticides should be used as a last resort due to their potential impact on the environment and non-target species.

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Wepresent Atacama Large Millimeter/submillimeter Array 12-m, 7-m, and Total Power Array observations of the FUOrionis outbursting system, covering spatial scales ranging from 160 to 25,000 au. The high-resolution interferometric data reveal an elongated 12CO(2–1) feature previously observed at lower resolution in 12CO(3–2). Kinematic modeling indicates that this feature can be interpreted as an accretion streamer feeding the binary system. The mass infall rate provided by the streamer is significantly lower than the typical stellar accretion rates (even in quiescent states), suggesting that this streamer alone is not massive enough to sustain the enhanced accretion rates characteristic of the outbursting class prototype. The observed streamer may not be directly linked to the current outburst, but rather a remnant of a previous, more massive streamer that may have contributed enough to the disk mass to render it unstable and trigger the FU Orionis outburst. The new data detect, for the first time, a vast, slow-moving carbon monoxide molecular outflow emerging from this object. To accurately assess the outflow properties (mass, momentum, and kinetic energy), we employ 13CO(2–1) data to correct for optical depth effects. The analysis indicates that the outflow corresponds to swept-up material not associated with the current outburst, similar to the slow molecular outflows observed around other FUor and Class I protostellar objects.

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Context. Determining the size distribution of asteroids is key to understanding the collisional history and evolution of the inner Solar System. Aims. We aim to improve our knowledge of the size distribution of small asteroids in the main belt by determining the parallaxes of newly detected asteroids in the Hubble Space Telescope (HST) archive and subsequently their absolute magnitudes and sizes. Methods. Asteroids appear as curved trails in HST images because of the parallax induced by the fast orbital motion of the spacecraft. Taking into account the trajectory of this latter, the parallax effect can be computed to obtain the distance to the asteroids by fitting simulated trajectories to the observed trails. Using distance, we can obtain the absolute magnitude of an object and an estimation of its size assuming an albedo value, along with some boundaries for its orbital parameters. Results. In this work, we analyse a set of 632 serendipitously imaged asteroids found in the ESA HST archive. Images were captured with the ACS/WFC and WFC3/UVIS instruments. A machine learning algorithm (trained with the results of a citizen science project) was used to detect objects in these images as part of a previous study. Our raw data consist of 1031 asteroid trails from unknown objects, not matching any entries in the Minor Planet Center (MPC) database using their coordinates and imaging time. We also found 670 trails from known objects (objects featuring matching entries in the MPC). After an accuracy assessment and filtering process, our analysed HST asteroid set consists of 454 unknown objects and 178 known objects. We obtain a sample dominated by potential main belt objects featuring absolute magnitudes (H) mostly between 15 and 22 mag. The absolute magnitude cumulative distribution logN(H > H0) ∝ αlog(H0) confirms the previously reported slope change for 15 < H < 18, from α ≈ 0.56 to α ≈ 0.26, maintained in our case down to absolute magnitudes of around H ≈ 20, and therefore expanding the previous result by approximately two magnitudes. Conclusions. HST archival observations can be used as an asteroid survey because the telescope pointings are statistically randomly oriented in the sky and cover long periods of time. They allow us to expand the current best samples of astronomical objects at no extra cost in regard to telescope time.

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The presentation first gives the brief introduction about the animal communication covering the reasons for communication. It then describes the important types of animal communication emphasizing the important points regarding auditory and visual communication. With respect to auditory communication, it covers the uses of it and mechanisms of auditory communication along with examples. Later the presentation discusses the various forms of visual communication such as gestures, postures, facial expressions, color changes , bioluminescent communication. It then describes the visual communication in bees in the form of bee dance . In bee dance it gives a brief overview of round dance , sickle dance and waggle dance .

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Jupiter’s moon Io hosts extensive volcanism, driven by tidal heating. The isotopic composition of Io's inventory of volatile chemical elements, including sulfur and chlorine, reflects its outgassing and mass loss history, and thus records information about its evolution. We used millimeter observations of Io’s atmosphere to measure sulfur isotopes in gaseous SO2 and SO, and chlorine isotopes in gaseous NaCl and KCl. We find 34S/32S = 0.0595 ± 0.0038 (equivalent to δ34S = +347 ± 86‰), which is highly enriched compared to average Solar System values and indicates that Io has lost 94 to 99% of its available sulfur. Our measurement of 37Cl/35Cl = 0.403 ± 0.028 (δ37Cl = +263 ± 88‰) shows that chlorine is similarly enriched. These results indicate that Io has been volcanically active for most (or all) of its history, with potentially higher outgassing and mass-loss rates at earlier times.

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Keep fit (a bit) - ESWC SSchool 14 - Student project

1. Keep Fit(a Bit) in Kalamaki First web based* attempt to make Kalamaki a „Smart City“ * to be extended to an app-based version after fundings ;) Proudly presented by FitBeople: Emna Elias Iacopo Maxim

2. The Story of Fred • Fred lives in Dublin • Dublin is a smart city * • Fred is a sports enthusiast • Observes his energy consumption/gain • Fred is going on holidays to Kalamaki • Of course Fred wants to stay fit • But... How to stay fit In Kalamaki?

3. What is a smart city? Source: http://www.urenio.org/wp-content/uploads/2011/01/ibm_smart_cities_new.jpg Food

4. Goal: „Personalized health planner“ Personalized healt planner Age, Height, Weight, GenderPosition in Kalamaki Integrated view of: Locations of Restaurants Dishes of restaurants Energy of dishes Price of dishes Walking distances between different places Overview of own energy balance

5. What did we do? • Data collection • RDF data (Total steps per day -FitBit API) • Non-digital data (restaurant menus) • HTML data (calories of dishes) • Geographic data (OSM)

6. What did we do? • Data integration • RDFisation of non-digital data andother data • Stored it in (local) triple store • SPARQL querys over multiple datasets • Implementation of web-based prototype • Computations of calories • Integration with backend • Graphical user interface

7. Demo

8. Future steps • Publishing Kalamaki data on OSM (Restaurants, Prices, Calories, etc.) • Generalization/integration of real smart city • Social features • Share activities and consumption • Comparewith other users • Exchange „lifestyle“ a) „I lost ...kg by doing ...“ b) „Wow, I live there too, I‘ll do the same thing“ • Including weather data • Including health data (illnesses, deseases, alergies)

9. Thank you! The first team ever, enabling Kalamaki a „smart city“!

Keep fit (a bit) - ESWC SSchool 14 - Student project

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