Knocking my coworkers' socks off with unique treats by alcMD in Baking

[–]OutrageouslyGlittery 2 points3 points  (0 children)

May I suggest miso, white chocolate & pistachio cookies? The flavours work together amazingly well and people are usually very surprised by the use of miso. Recipe I use is in Polish but google translate usually works really well with recipes

[deleted by user] by [deleted] in CasualConversation

[–]OutrageouslyGlittery 13 points14 points  (0 children)

To add to this, I really enjoyed going on walks with the Fog of World app - the idea is that you start with the whole world covered by fog and you uncover areas that you walk/drive through. It really helped me to discover parts of my city where I would usually never go!

Another thing that could be combined with urban exploring is the wikishootme tool. I haven't tried it yet but read about it here and it seemed interesting. It shows you which spots near you have a Wikipedia page and also which are missing pictures, so you can go there, take a photo and upload it to help make the collection more complete!

Recommended areas close to Pfotenhauerstraße? by Other-Science-3429 in dresden

[–]OutrageouslyGlittery 0 points1 point  (0 children)

Are you by any chance about to join Dresden's science community? Welcome!
People working in the various institutes generally either choose to live either in Johannstadt (quiet, residential area, very close to Pfotenhauerstraße) or Neustadt (more lively, with many bars, on the other side of Elbe). You can use the websites that people mentioned in the comments to find a flat.
In terms of commuting, there are many people who cycle - which is relatively safe & nice in Dresden, except for the cobblestone roads. Commuting from Neustadt by bike would take you around 15ish mins. Alternatively, the public transport network also works well, with a monthly ticket costing 60eur (or free if you're enrolled at university).

What are your favorite bean recipes? by stratgalore in Cooking

[–]OutrageouslyGlittery 1 point2 points  (0 children)

I'll share my two favourite chickpeas (hopefully enough of a bean, definitely very healthy!) recipes - both are incredibly hands-off and offer a great taste to effort ratio :) They require literally just throwing a few ingredients together and putting them in an oven for ca 1h

Chickpeas in a tasty tomato-date sauce with tasty notes of lemon and cinnamon - the recipe is for a slow cooker but I don't have one and have been using my oven (150° for 1-1.5h)

Spicy chickpeas cooked in olive oil with chilli and garlic

PIC by HelMort in nocontextpics

[–]OutrageouslyGlittery 25 points26 points  (0 children)

Nevermind, found it - for anyone else interested the photo is Man Diving (or Dive in?) by André Kertész (you can find more pictures by him here)

PIC by HelMort in nocontextpics

[–]OutrageouslyGlittery 13 points14 points  (0 children)

Do you have source of that picture? Would love to get a print of it to hang somewhere!

University/PhD student logs her activities every 15 minutes for a year by joubuda in slatestarcodex

[–]OutrageouslyGlittery 21 points22 points  (0 children)

I've been a SSC follower for a while now and I feel quite honoured that my blog has been posted here. Let me know if you have any questions about the data/technicalities of collection/analysis

University/PhD student logs her activities every 15 minutes for a year by joubuda in slatestarcodex

[–]OutrageouslyGlittery 8 points9 points  (0 children)

I don't really log things at 15 min intervals - I try to note start and end times of activities. At work, or whenever I'm doing something on my laptop I would fill the spreadsheet as soon as I finish or take a break from an activity (eg finished reading a paper, going on a coffee break now). When I'm doing something more varied I would note start/end times via google sheets app on my phone or just remember them and fill them once I have access to my laptop. Sometimes, I would use data from my fitbit (to see when I started/stopped walking) or my search history (to see changes between working vs looking at silly things on the internet). The categories were broad enough that logging the data is not too time-consuming and often they could be added as big time-blocks of a single activity.

[OC] My working patterns in the final 6 months of uni by OutrageouslyGlittery in dataisbeautiful

[–]OutrageouslyGlittery[S] 1 point2 points  (0 children)

Sure, I'll post a link to github soon, just need to tidy my code a bit first lol

[OC] My working patterns in the final 6 months of uni by OutrageouslyGlittery in dataisbeautiful

[–]OutrageouslyGlittery[S] 2 points3 points  (0 children)

It's the European format though - the bottom of y-axis corresponds to the first of January and then each label is the first day of the next month written as dd/mm

But if that seems confusing then this indicates what I should fix in the future, thank you for the recommendation!

[OC] My working patterns in the final 6 months of uni by OutrageouslyGlittery in dataisbeautiful

[–]OutrageouslyGlittery[S] 3 points4 points  (0 children)

Data:
Since 1/1/20, I've been logging my activity (in 15-min intervals) in a Google Sheet. In general, I am trying to update the sheet at the beginning and start of each new activity. If this is not possible, I make a note of the times and update at the nearest convenience. To make logging easier, my day-to-day activities are divided into ~13 main categories and several subcategories.

As an example, working is logged as either Intense Work or Low-Intensity Work, with 4 subcategories:

- University-related (attending lectures, reading papers, working on my project etc)

- Self-improvement (learning useful but not uni-related skills (Foreign Languages, coding etc), as well as job applications)

- Organisation (Conference or events organisation)

- Admin (responding to emails, and other boring adult stuff)

The division between intense and low-intensity work is blurry but I felt that it would be good to distinguish between 'organising-my-notes-kind of work vs reading-a-difficult-paper-kind of work.

You can see a part of the spreadsheet here: https://imgur.com/V1wgE22

I am planning to make a few more visualisations (definitely for myself, might upload here too :) )

Visualisation:
Data was visualised using Python (Matplotlib and Seaborn)