What is the subspecies name for the standard race choices in the D&D 3.5 Players Handbook? What is appearance do these subspecies, and a few others?

I am playing D&D on a Neverwinter Nights Enhanced Edition module using the D&D 3.5 ruleset. Please note that this is not a Neverwinter Nights game question. This is a D&D 3.5 lore question.

I am having difficultly finding the subspecies name for the standard race choices offered in the Players Handbook. I am also having difficulty finding descriptions and images of their appearance online. I am avoiding 4e or 5e images and information because some of the lore has changed.

Here is my list of questions. Hair and skin is all I need for description. If you can have a picture link that would be very helpful. I will also gladly look at any online resource that answers my questions and saves people time from writing out their answers.

What is the standard elf race subspecies name in D&D 3.5? What is their suggested appearance?

What is the standard gnome race subspecies name in D&D 3.5? What is their suggested appearance?

What is the standard dwarf race subspecies name in D&D 3.5? What is their suggested appearance?

What is the standard halfling subspecies name race in D&D 3.5? What is their suggested appearance?

What does a deep dwarf look like?

What does a wild elf look like?

What does a wood elf look like?

What does a gray elF look like?

What does a forest gnome look like?

What does a lightfoot halfling look like?

What does a tallfellow halfling look like?

What is a tribal orc? What does it look like?

What is a deep orc? What does it look like?

What do you call a greedy algorithm that solves a combinatorial problem by optimizing the best k>1 choices altogether?

Suppose you have a problem which goal is to find the permutation of some set $ S$ given in input that minimizes an objective function $ f$ (for example the Traveling Salesman problem).

A trivial algorithm $ E(S)$ that find the exact solution enumerates all the permutations and outputs the one that minimizes $ f$ . Its time complexity is $ O(n!)$ where $ n$ is the size of $ S$ .

A trivial greedy algorithm $ G(S)$ that finds an approximation of the solution is:

 out[0] = select a good starting item from S according to some heuristic h_1. S = S - {out[0]} for i=1 to n-1 do:     out[i] = select the next best element using some heuristic h_2     S = S - {out[i]} return out 

Where $ h_1$ and $ h_2$ are two heuristics. Its complexity in time is $ O(n^2)$ assuming that $ h_2$ runs in constant time.

Sometimes I mix the two techniques (enumeration and greedy) by selecting at each step the best $ k$ items (instead of the best one) and enumerating all their permutations to find the one that locally minimizes $ f$ . Then I choose the best $ k$ items among the remaining $ n-k$ items and so on.

Here is the pseudocode (assuming $ n$ is a multiple of $ k$ ):

 for i in 0 to n/k do:     X = select the best k items of S according to some heuristic h     S = S - X     out[i*k ... (i+1)*k-1] = E(X) return out 

Where $ E(X)$ is algorithm that find the exact solution applied on a subset $ X \subset S$ rather than on the whole $ S$ . This last algorithm finds an approximate solution and has a time complexity of $ O(\frac{n}{k}(n \log k + k! ))$ assuming that $ h$ can be computed in constant time. This complexity can be comparable to $ O(n^2)$ if $ k$ is small although according to my experience the performances can be way better than the greedy approach.

I don’t think I invented this kind of optimization technique: do you know its name? Can you please include some theoretical references?

I know for sure it is not beam search, because beam search never mixes the best $ k$ solutions found at each step.

Thank you.

Player action choices on official adventure books

I’ve been running a few officially published adventure books during the last few months, but I never know how to convey the possible actions the players can take and I feel they lose a lot of possibilities because I’m not giving them enough knowledge and just letting them decide whatever they want to do without previous feedback.

For example, during one of the adventures, the players find a desecrated altar, and the book states the players can either pray with a DC 15 (religion) check or splash three flasks of holy water on the altar to cleanse it.

Should I even tell them, or is it just for my eyes in case they try to do it? And, in case they should know they can do it, how should I let them know? Should I simply tell them?

Can a sorcerer make independent spell-effect choices for a Twinned spell?

Can a sorcerer make independent spell-effect choices for a Twinned spell?

For instance, the Polymorph spell can be used on willing and unwilling targets; the unwilling can make a Wisdom save to avoid the effects.

The sorcerer’s Twinned Spell metamagic option creates a second instance of the same spell on 2 viable targets within range.

Does Twinned Spell force me to polymorph both targets into the same thing, or do I get to choose what each instance of polymorph does independently?

In this case I am trying to turn my friend into a T-rex, and an enemy into a goldfish.

Are Checkboxes or Chips the best UX for large number of choices?

I have a design requirement to list all the industry sectors and the user must choose one or more industry sectors which apply. Here is a list of all the industry sectors:

A. Agriculture, forestry and fishing B. Mining and quarrying C. Manufacturing D. Electricity, gas, steam and air conditioning supply E. Water supply; sewerage, waste management and remediation activities F. Construction G. Wholesale and retail trade; repair of motor vehicles and motorcycles H. Transportation and storage I. Accommodation and food service activities J. Information and communication K. Financial and insurance activities L. Real estate activities M. Professional, scientific and technical activities N. Administrative and support service activities O. Public administration and defence; compulsory social security P. Education Q. Human health and social work activities R. Arts, entertainment and recreation S. Other service activities T. Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use U. Activities of extraterritorial organizations and bodies 

Would these better be represented as material ui chips or checkboxes?

chips

checkbox

Font and Color choices on Full-Page backgrounds

I am an amateur web developer, and am teaching myself React. Currently, I have been building a personal website hosted on github pages –

https://roy-05.github.io/website/#/

As I want to complete the mobile design first, please switch over to mobile view (iPhone 6/7/8) in devTools –

Q) As you can see the text is not really appealing or “eye-catching”. What kind of design choices do more experienced people like yourselves go through in choosing the right font/style, and colors to make the page vibrant and aesthetic against a colored background?

Please do not hesitate to criticize and highlight the site’s shortcomings.

Hash table with $n(1+\epsilon)$ space using power of $d$ choices and cuckoo hashing

I’m trying to construct a hash table in which we store $ n$ items using $ n(1+\epsilon)$ space. Lookups should be worst case $ O(1)$ and insertion/deletion should be $ O(1)$ in expectation.

Thoughts: The idea is to have a main table that is size $ n$ . We use the power of $ d$ choices to find a cell for a given item. Let the max capacity per cell in the main table be a constant $ c$ . We hash the item with $ d$ different hash functions and place the item in the cell with the most room. If that fails (that is, no cells have room), we move the item to an overflow table that is size $ n\epsilon$ for $ 0 < \epsilon < 1$ . The overflow table will use Cuckoo hashing. I need to find a $ d$ and $ c$ for which this works.

Cuckoo hashing works well when the load factor is under $ 1/2$ . That means with $ n\epsilon$ space, we should never move more than $ \frac{n\epsilon}{2}$ items from the main table into the overflow table. We need to pick $ d$ such that the number of collisions greater than $ c$ is at most $ \frac{n\epsilon}{2}$ .

I’m not sure where to go from here (or if I’m on the right track). Any help is appreciated.

How to show list of available choices on a sharepoint form

I have a simple sharepoint form added called ‘laptop borrowing request’ which has employee name, date and laptop as fields. Laptop is a choice column: surface, thinkad and laptop. There are only three devices physically present at client.

Now the following seems difficult to implement for me: 1. Let’s say if couple of users have put in request and they have acquired possession of thinkpad and laptop ,so only surface is available to request.

If the next person puts in a request for thinkpad, how do I show that its not available or restrict to put in a request for thinkpad.

Please share thoughts if any, thanks. I am working SP online modern.

Getting choices from choice field in Online using JSOM

I am trying to get all of the choices from a choice site column in SharePoint online. Using the following code I get to the success method but it errors out saying ‘field’ is undefined. I don’t understand why this doesn’t work because I have defined field in the fields() method

hostweburl = decodeURIComponent(getQueryStringParameter("SPHostUrl")); appweburl = decodeURIComponent(getQueryStringParameter("SPAppWebUrl"));      function fields() {         var context = new SP.ClientContext(appweburl);         var factory = new SP.ProxyWebRequestExecutorFactory(appweburl);         context.set_webRequestExecutorFactory(factory);          var appContextSite = new SP.AppContextSite(context, hostweburl);         var web = appContextSite.get_web();         context.load(web);          var siteColumns = web.get_fields();         var field = context.castTo(siteColumns.getByInternalNameOrTitle('InternalFieldName'), SP.FieldChoice);          context.load(field);         context.executeQueryAsync(Function.createDelegate(this, this.onSuccessMethod), Function.createDelegate(this, this.onFailureMethod));     }      function onSuccessMethod(sender, args) {         var choices = field.get_choices();         alert("Choices: (" + choices.length + ") - " + choices.join(", "));     }      function onFailureMethod(sender, args) {         alert('Request failed. ' + args.get_message() + '\n' + args.get_stackTrace());     }