You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 regional_sales
【Schema】
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Customer Names:TEXT, Examples: [Avon Corp, WakeFern , Elorac, Corp])
]
# Table: Sales Team
[
(SalesTeamID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Sales Team:TEXT, Examples: [Adam Hernandez, Keith Griffin, Jerry Green]),
(Region:TEXT, Examples: [Northeast, West, South])
]
# Table: Sales Orders
[
(OrderNumber:TEXT, Primary Key, Examples: [SO - 0001000, SO - 0001001, SO - 0001002]),
(Sales Channel:TEXT, Examples: [In-Store, Online, Distributor]),
(WarehouseCode:TEXT, Examples: [WARE-UHY1004, WARE-NMK1003, WARE-PUJ1005]),
(ProcuredDate:TEXT, Examples: [12/31/17, 4/10/18, 7/19/18]),
(OrderDate:TEXT, Examples: [5/31/18, 6/1/18, 6/2/18]),
(ShipDate:TEXT, Examples: [6/14/18, 6/22/18, 6/21/18]),
(DeliveryDate:TEXT, Examples: [6/19/18, 7/2/18, 7/1/18]),
(CurrencyCode:TEXT, Examples: [USD]),
(_SalesTeamID:INTEGER, Examples: [6, 14, 21]),
(_CustomerID:INTEGER, Examples: [15, 20, 16]),
(_StoreID:INTEGER, Examples: [259, 196, 213]),
(_ProductID:INTEGER, Examples: [12, 27, 16]),
(Order Quantity:INTEGER, Examples: [5, 3, 1]),
(Discount Applied:REAL, Examples: [0.075, 0.05, 0.1]),
(Unit Price:TEXT, Examples: [1,963.10, 3,939.60, 1,775.50]),
(Unit Cost:TEXT, Examples: [1,001.18, 3,348.66, 781.22])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Product Name:TEXT, Examples: [Cookware, Photo Frames, Table Lamps])
]
# Table: Regions
[
(StateCode:TEXT, Primary Key, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Region:TEXT, Examples: [South, West, Northeast])
]
# Table: Store Locations
[
(StoreID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(City Name:TEXT, Examples: [Birmingham, Huntsville, Mobile]),
(County:TEXT, Examples: [Shelby County/Jefferson County]),
(StateCode:TEXT, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Type:TEXT, Examples: [City, Town, CDP]),
(Latitude:REAL, Examples: [33.52744, 34.69901, 30.69436]),
(Longitude:REAL, Examples: [-86.79905, -86.67298, -88.04305]),
(AreaCode:INTEGER, Examples: [205, 256, 251]),
(Population:INTEGER, Examples: [212461, 190582, 194288]),
(Household Income:INTEGER, Examples: [89972, 78554, 76170]),
(Median Income:INTEGER, Examples: [31061, 48775, 38776]),
(Land Area:INTEGER, Examples: [378353942, 552604579, 361044263]),
(Water Area:INTEGER, Examples: [6591013, 3452021, 105325210]),
(Time Zone:TEXT, Examples: [America/Chicago, America/Phoenix, America/Los Angeles])
]
【Foreign keys】
Sales Orders._ProductID=Products.ProductID
Sales Orders._StoreID=Store Locations.StoreID
Sales Orders._CustomerID=Customers.CustomerID
Sales Orders._SalesTeamID=Sales Team.SalesTeamID
Store Locations.StateCode=Regions.StateCode

    【Question】
    Count the number of orders made from the store in city with population of 3000000 to 4000000. number of order refers to OrderNumber; population of 3000000 to 4000000 refers to Population BETWEEN 3000000 AND 4000000

    【Evidence】
    number of order refers to OrderNumber; population of 3000000 to 4000000 refers to Population BETWEEN 3000000 AND 4000000

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T2.Population BETWEEN 3000000 AND 4000000